One-day protocol for 18F-FDG and 13N-ammonia PET/CT with uptake decoupling score in differentiating untreated low-grade glioma from inflammation | Revista Española de Medicina Nuclear e Imagen Molecular (English Edition)

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Chang, Y. Donglan, S. Xinchong, L. Ganhua, Z. Bing, L. Yao, Z. Rutong, H. Qiao, Z. Xiangsong" "autores" => array:9 [ 0 => array:3 [ "nombre" => "Y." "apellidos" => "Chang" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "1" "identificador" => "fn0005" ] ] ] 1 => array:3 [ "nombre" => "Y." "apellidos" => "Donglan" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] 1 => array:2 [ "etiqueta" => "1" "identificador" => "fn0005" ] ] ] 2 => array:3 [ "nombre" => "S." "apellidos" => "Xinchong" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "L." "apellidos" => "Ganhua" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Z." 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"apellidos" => "Xiangsong" "email" => array:1 [ 0 => "xiaolong-4310@163.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Department of Nuclear Medicine, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Medical Engineering, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author at: Department of Nuclear Medicine, the First Affiliated Hospital of Sun Yat-Sen University. Zhongshan Er Road 58#, Guangzhou, China." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Protocolo de un día para la TEP/TC con amoníaco 18F-FDG y 13N con puntuación de desacoplamiento de la captación para diferenciar el glioma de bajo grado no tratado de la inflamación" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1288 "Ancho" => 1508 "Tamanyo" => 112433 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Receiver operating characteristic analysis for detecting lesions with <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG tumor-to-normal tissue (T/N) ratio, <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia T/N ratio, and decoupling score. The decoupling score showed the best performance, with a cutoff value of 2.31 (area under the curve, AUC: 0.77), whereas the cutoff values for T/N ratio of <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia uptake were 0.73 (AUC: 0.48) and 0.97 (AUC: 0.68), respectively." ] ] ] "textoCompleto" => "IntroductionLow-grade gliomas (LGGs; World Health Organization [WHO] grades I and II) are a diverse group of primary brain tumors that often arise in young, otherwise healthy patients; these commonly follow an indolent course and exhibit long-term survival, which contrasts with the prognosis of high-grade gliomas.<a class="elsevierStyleCrossRefs" href="#bib0005">1,2</a> Accurate diagnosis and grading are critical for management of LGGs.<a class="elsevierStyleCrossRef" href="#bib0015">3</a> Although histopathological examination of tissue remains the gold standard for diagnosis and grading of LGGs, preoperative imaging is essential to distinguish between inflammation and tumor. However, gliomas are often histologically heterogeneous, with evolving anaplastic areas within a low-grade tumor; moreover, contrast-enhancement on CT or MRI does not provide a good marker for anaplastic tissue detection.<a class="elsevierStyleCrossRef" href="#bib0020">4</a> The development of radiolabeled tracers has enabled metabolic and molecular imaging to play a major role in the management of gliomas, such as PET. To successfully use PET data in glioma treatment, PET can be integrated in the planning of image-guided biopsy, resection, and radiosurgery.<a class="elsevierStyleCrossRef" href="#bib0020">4</a> Additionally, amino acid tracers have a high sensitivity for detection of LGGs.<a class="elsevierStyleCrossRef" href="#bib0025">5</a> Notably, fluorothymidine is useful in grading gliomas, as is dynamic PET using fluoroethyltyrosine (FET) for tumor grading;<a class="elsevierStyleCrossRefs" href="#bib0030">6–8</a> however, these tracers are either complicated to synthesize, with low yields, or require a complex acquisition protocol.In a previous study, we found that 13N-ammonia PET was superior to 18F-FDG PET and contrast-enhanced MRI for grading of untreated gliomas and that it could be used for the detection of high-grade gliomas and recurrent astrocytomas.<a class="elsevierStyleCrossRefs" href="#bib0045">9–11</a> Thus far, differentiation between neoplastic and non-neoplastic lesions has been evaluated in several studies.<a class="elsevierStyleCrossRefs" href="#bib0060">12,13</a> However, our recent study found that 13N-ammonia was effective in distinguishing high-grade gliomas from low-grade gliomas and inflammation, but its role in differential diagnose of low-grade gliomas and brain inflammatory lesions was limited.<a class="elsevierStyleCrossRef" href="#bib0070">14</a> This might be attributed to difficulty in discriminating between brain inflammation lesions (BILs) and LGGs by using conventional imaging modalities; furthermore, there are no established quantification approaches for image analysis using 13N-ammonia and 18F-FDG.In this retrospective study, we performed voxel-wise analysis of 18F-FDG and 13N-ammonia PET in tumor and inflammation-infiltrative brain lesions, in an attempt to discriminate between benign lesions and LGGs using decoupling score.Materials and methodsPatientsThis study was performed between july 2011 and may 2016. A total of 28 patients with a final diagnosis of LGG (13 female and 15 male patients; mean age, 36.53 ± 14.59 years; age range, 14–67 years) and 16 patients with a final diagnosis of BIL (8 female and 8 male patients; mean age, 46.38 ± 16.49 years; range, 23–73 years) were included in this study. Patients with any previous treatments were excluded (e.g., corticosteroids, surgery, chemotherapy, radiotherapy, or gamma-knife therapy).<a class="elsevierStyleCrossRef" href="#bib0045">9</a> All patients underwent 13N-ammonia PET/CT and 18F-FDG PET/CT on the same day (FDG PET/CT was performed after ammonia PET/CT, with a minimum interval of 2 h). In 34 patients, pathological diagnosis was obtained by tumor resection or biopsy after PET examination. Four patients had grade I glioma, according to the WHO classification, whereas 24 had WHO grade II glioma (19 were astrocytoma, 4 were oligodendroglioma, and 1 was oligoastrocytoma). The remaining patients had BILs (3 were brain abscess, 2 were demyelination, and 1 was fungal infection). In 10 patients, the results of pathological examination could not be obtained; thus, the diagnosis of inflammation was based on radiological (CT and MRI) and clinical investigation. The patients’ characteristics are summarized in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>The study of 13N-ammonia imaging has been approved by the ethics committee of our hospital. Although formal consent was not required for this retrospective study, all subjects agreed to participate in this study after receiving an explanation of detailed study purpose and imaging procedure.PET data acquisitionTracers were produced at our center by using standard techniques and commercially available system for isotope generation (Cyclone-10, Ion Beam Applications; Louvain-La-Neuve, Belgium). PET/CT imaging was performed with a Gemini GXL 16 scanner (Philips, Amsterdam, Netherlands) in a 3-dimensional (3D) acquisition mode. The specific imaging protocol for the brain was selected as field of view (FOV) 180 mm, and the transaxial spatial resolution was 2 mm full width at half maximum (FWHM) at the center of the FOV for 18F-FDG. The spatial resolution of 13N-ammonia imaging was lower than that of 18F-FDG because of the difference in positron energy. PET images were reconstructed by the Line of Response RAMLA algorithm with low-dose CT images for attenuation correction, resulting in 3D images comprising 128 × 128 × 90 voxels of 2.0 × 2.0 × 2.0 mm<a class="elsevierStyleCrossRef" href="#bib0015">3</a>.<a class="elsevierStyleCrossRefs" href="#bib0045">9,10</a>All subjects fasted for at least 8 h before PET/CT imaging. Ammonia and FDG PET/CT studies were performed on the same day, as described above. The 10-min PET acquisition began 5 min after an intravenous injection of 13N-ammonia (555–740 MBq) or 45–60 min after an intravenous injection of 18F-FDG (5.18 MBq/kg).Data analysisOne experienced nuclear medicine physician, who was blinded to the clinical and structural imaging findings, evaluated the PET/CT images. PET images were converted to NII format and co-registered using SPM software (Functional Imaging Laboratory, Wellcome Trust Centre for Neuroimaging, Institute of Neurology, UCL, London, UK). The registration of the images was confirmed visually.Lesion uptake was evaluated by semiquantitative analysis. Regions of interest (ROIs) for each lesion were outlined in the area with the highest activity, and the location of the lesion was determined by using CT image guidance to avoid misplacement. For lesions that did not show higher uptake than the surrounding tissue, ROIs were defined on CT images after co-registering the PET and CT images. All ROIs of each tumor were placed carefully to avoid areas of necrosis, hemorrhage, or normal tissue; in addition, the first and the last slices of each tumor were not used, to avoid the volume effect. For reference tissue, ROIs were selected at the uninvolved contralateral hemisphere of the same slice of the lesion ROI, including both gray and white matter. The average standardized uptake value (SUV) of all regions was used to calculate the tumor to normal tissue (T/N) ratio, enabling reconstruction of a T/N ratio image.All datasets (standard anatomical images and PET data) were exported to in-house software written in MATLAB 7.6 (MathWorks, Natick, MA, USA) for further analysis.Decoupling score calculationAs illustrated in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, a linear relationship between 13N-ammonia uptake and 18F-FDG uptake in normal brain was observedas follows:<elsevierMultimedia ident="eq0005"></elsevierMultimedia>where (13N-ammonia) and (18F-FDG) represent the T/N ratios of 13N-ammonia and 18F-FDG PET, respectively.<elsevierMultimedia ident="fig0005"></elsevierMultimedia>Subsequently, calculate the deviation of each data point (i) from the expected linear regression fit as follows:<elsevierMultimedia ident="eq0010"></elsevierMultimedia>where (13N-ammonia) and (18F-FDG) represent the T/N ratios of 13N-ammonia and 18F-FDG PET, respectively.The decoupling score of each data point was defined as follows:<elsevierMultimedia ident="eq0015"></elsevierMultimedia>where µ and σ represent the mean and standard deviation of deviation (i) for the ROI located in the normal brain. This score (i) could be used to quantify the difference between 13N-ammonia uptake and 18F-FDG uptake in brain lesions.<a class="elsevierStyleCrossRefs" href="#bib0075">15,16</a>Statistical analysisStatistical analysis was conducted on the platform of PASW Statistics 18.0 (IBM, Armonk, NY, USA). Sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) with 95% confidence intervals (CI) were calculated for each tracer with T/N ratios. Student’s t-test was used to compare T/N ratios and decoupling scores of each tracer between LGGs and BILs. Receiver operating characteristic (ROC) analysis was used to establish a cut-off value for the decoupling score, and the area under the curve (AUC) was calculated to evaluate differential efficacy. Results were considered significant at the level of p < 0.05.ResultsDecoupling map reconstruction in LGG and BILAccording to visual analysis, decoupling scores were markedly increased in the tumors, compared to surrounding normal brain tissues; this allowed precise delineation of the extent of tumor (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>). Conversely, decoupling scores of BILs were similar to or lower than those of surrounding normal brain tissue (<a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>). In 18F-FDG or 13N-ammonia T/N ratio maps, LGGs and BILs did not exhibit fixed patterns of expression and were higher or lower than surrounding normal brain tissues. Tumor boundaries were always more clearly delineated in the decoupling map than in the T/N ratio map.<elsevierMultimedia ident="fig0010"></elsevierMultimedia>T/N ratios in LGG and BILThe T/N ratios of 18F-FDG were lower than those of 13N-ammonia in LGGs (mean ± standard deviation, 0.76 ± 0.23 vs. 1.00 ± 0.18, t = −6.718, p < 0.001). However, no significant difference was observed between 18F-FDG and 13N-ammonia in BILs (0.88 ± 0.52 vs. 0.84 ± 0.22, t = 0.330, p = 0.746). The T/N ratios of 18F-FDG uptake were not useful for differentiating LGGs from BILs (LGG vs. BIL: 0.76 ± 0.23 vs. 0.88 ± 0.52, t = −0.836, p = 0.413), whereas the T/N ratios of 13N-ammonia (LGG vs. BIL: 1.00 ± 0.18 vs. 0.84 ± 0.22, t = 2.519, p = 0.018) uptake were better performance than those of 18F-FDG in differentiating LGGs from BILs.ROC analysis yielded optimal T/N cut-off values of 0.73 for 18F-FDG and 0.97 for 13N-ammonia for differentiating between LGGs and BILs; the respective AUCs were 0.48 and 0.68. For prediction of LGGs using these optimal cut-off values, the respective sensitivity, specificity, accuracy, PPV, and NPV were 53.6% (15/28), 62.5% (10/16), 56.8% (25/44), 71.4% (15/21), and 43.5% (10/23) for 18F-FDG; they were 50.0% (14/28), 75.0% (12/16), 59.1% (26/44), 77.8% (14/18), and 46.2% (12/26) for 13N-ammonia.Decoupling score in LGGs and BILsThe average decoupling scores of 18F-FDG and 13N-ammonia were calculated for both LGGs and BILs; these were 2.48 ± 0.62 and 1.72 ± 0.61, respectively, demonstrating a significant difference (t = 3.252, p = 0.003). The optimal T/N cut-off value for the decoupling score to differentiate between LGG and BIL, as determined by ROC curve analysis, was 2.31 (AUC, 0.77) (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>). For the diagnosis of LGG using the optimal cut-off values, the respective sensitivity, specificity, accuracy, PPV, and NPV were 60.7% (17/28), 93.8% (15/16), 72.7% (32/44), 94.4% (17/18), and 57.7% (15/26). <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> summarizes the PET results of T/N ratios and decoupling scores for 13N-ammonia and 18F-FDG PET uptake studies.<elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia>DiscussionAlthough molecular diagnostics (e.g., chromosomal and gene array technologies) are becoming increasingly beneficial for understanding tumor genetic heterogeneity, <a class="elsevierStyleCrossRef" href="#bib0085">17</a> these approaches always require invasive tissue analysis and therefore cannot fully replace non-invasive diagnostics. MRI, with or without gadolinium, remains the gold standard for noninvasive diagnosis and follow-up of patients with gliomas.<a class="elsevierStyleCrossRefs" href="#bib0005">1,3,4</a> In patients with a suspected brain tumor, anatomic imaging sequences typically include T1- and T2-weighted MR sequences, as well as fluid attenuation inversion recovery MR sequences; T1- weighted imaging is performed after administration of gadolinium-based contrast.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> However, this technique only indirectly reflects the biological activity of the tumor by detecting destruction of the blood-brain barrier.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> Therefore, routine MRI lacks accuracy in terms of non-invasive assessment, especially for LGGs and BILs. Although advanced MR techniques (e.g., perfusion imaging, diffusion-weighted imaging, diffusion tensor imaging, and MR spectroscopy) provide some metabolic and functional information for differentiating gliomas from non-neoplastic brain lesions,<a class="elsevierStyleCrossRefs" href="#bib0100">20–22</a> they also involve some limitations.<a class="elsevierStyleCrossRef" href="#bib0095">19</a> These drawbacks include: partial volume effects, non-standardized acquisition, and a postprocessing protocol that is non-specific for LGGs. Herein, the molecular information provided by PET is valuable in its ability to supplement additional imaging data.<a class="elsevierStyleCrossRef" href="#bib0020">4</a>18F-FDG and amino-acid tracers, such as 11C-methionine (11C-MET), 18F-FET, and 18F-FDOPA, provide corresponding metabolic data that enable precise assessment of glioma extension, detection of anaplastic areas, and postoperative follow-up.<a class="elsevierStyleCrossRefs" href="#bib0115">23–25</a> These methods have high sensitivity, as well as positive results, in both acute and chronic inflammation. Previously, we reported that 13N-ammonia, combined with 18F-FDG, exhibits great potential for the diagnosis, grading, and postoperative follow-up of intracranial lesions.<a class="elsevierStyleCrossRefs" href="#bib0045">9–11</a> Moreover, we analyzed the application of 13N-ammonia in the diagnosis of glioma and inflammatory lesions, concluding that 13N-ammonia could distinguish high-grade gliomas from low-grade gliomas and inflammations, but could not distinguish low-grade gliomas from inflammatory lesions.<a class="elsevierStyleCrossRef" href="#bib0070">14</a> Therefore, we used a new voxel-wise analysis to process 13N-ammonia and 18F-FDG uptake in both LGGs and inflammatory lesions.Our previous reports showed that 13N-ammonia uptake was higher than 18F-FDG uptake in high-grade gliomas and meningiomas,<a class="elsevierStyleCrossRefs" href="#bib0045">9,26</a> while 13N-ammonia uptake was lower than 18F-FDG uptake in brain abscesses and primary central nervous system lymphomas.<a class="elsevierStyleCrossRefs" href="#bib0050">10,27</a> However, LGGs and BILs showed heterogeneous uptake in both 13N-ammonia and 18F-FDG. As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>b, lesions (WHO grade Ⅱ oligodendroglioma) showed lower 18F-FDG and 13N-ammonia uptake than normal brain tissues. The average T/N ratios of 18F-FDG and 13N-ammonia uptake, obtained from 16 layers of lesions, were 0.55 and 0.93, respectively. These results were not helpful in the diagnosis of the lesions. Conversely, a remarkably high decoupling score was observed in the lesions in the decoupling map, which could be helpful for diagnosis. Similarly, as shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>a, lesions (WHO grade Ⅱ astrocytoma) showed lower 18F-FDG uptake, but higher 13N-ammonia uptake and decoupling score, compared to normal brain tissues. Furthermore, as shown in <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>, lesions (inflammation) showed higher 18F-FDG uptake, but lower 13N-ammonia uptake and decoupling score, compared to normal brain tissues. ROC analysis revealed the optimal performance of the decoupling score at a cut-off value of 2.31 (sensitivity, 60.7%; specificity, 93.8%), with an AUC of 0.77. This result indicated that the decoupling score is a better surrogate indicator for discriminating between LGGs and BILs, compared to 13N-ammonia and 18F-FDG PET alone.Many studies have shown that amino acid tracers were used in the management of patients with low-grade gliomas, but few have directly compared their differential efficacy to differentiate LGGs and inflammation. Kracht et al. reported 11C-MET PET in 13 LGGs and 3 nontumor lesions patients with 87% sensitivity and 89% specificity of 1.3-fold 11C-MET uptake relative to normal brain tissue.<a class="elsevierStyleCrossRef" href="#bib0025">5</a>18F-FET PET also appeared to be superior to FDG-PET for biopsy planning in non-contrast-enhancing brain tumurs, 69% LGGs (49/71) had been found increased 18F-FET uptake in Jansen NL study, 8/9 LGGs had increased 18F-FET uptake in Plotkin M study.<a class="elsevierStyleCrossRefs" href="#bib0115">23,24</a>18F-DOPA was also useful to discriminate low-grade gliomas from high-grade gliomas in 2.16 SUVmax with 60% sensitivity and 100% specificity.<a class="elsevierStyleCrossRef" href="#bib0125">25</a> Compared with the above amino acid tracers, the decoupling score of 18F-FDG and 13N-ammonia method has higher specificity (93.8%) to differentiate LGGs and BILs.Some previous studies<a class="elsevierStyleCrossRefs" href="#bib0075">15,16</a> have reported that 18F-FDG-11C-methionine uptake decoupling score reflects glioma cell infiltration to assess glioma invasion. Similarly, a linear relationship could be inferred between 13N-ammonia uptake and 18F-FDG uptake in the normal brain, such that 18F-FDG can be used as a reference index for 13N-ammonia uptake in normal brain tissues. The decoupling score calculated at each voxel represents the magnitude of the disrupted correlation of 18F-FDG and 13N-ammonia at each location of the brain.According to Cooper,<a class="elsevierStyleCrossRef" href="#bib0140">28</a> ammonia can act as a source of glutamine in the glutamine cycle. Although inactive neovasculature provides a limited quantity of glutamine for trapping in LGGs,<a class="elsevierStyleCrossRef" href="#bib0145">29</a> deviation between 18F-FDG and 13N-ammonia uptake will be markedly evident in reconstructed images, in the event of tumor infiltration. Extreme decoupling of 18F-FDG and 13N-ammonia uptake was observed in LGGs, suggesting that the difference in 18F-FDG and 13N-ammonia uptake could be expressed as the decoupling score. This difference implies that the decoupling score is based on tumor infiltration into brain tissue, although the relationship between inflammation and gliomas is rather complex.<a class="elsevierStyleCrossRef" href="#bib0150">30</a> As reported in some literature, tumor was usually accompanied by inflammation, but the microenvironment of glioma contains many coordination mechanisms that are different from inflammation, include various glioma-secreted signaling factors such as cytokines, chemokines, and growth factors.<a class="elsevierStyleCrossRef" href="#bib0150">30</a> As also, 13N-ammonia is involved in the glioma cells glutamine cycle, 18F-FDG is involved in the glioma cells glucose cycle. It may be due to the difference in the intracellular metabolic patterns of the two imaging agents in inflammation and glioma, which ultimately leads to the difference in the decoupling scores, and the mechanism needs further research.When 11C-MET coupled with 18F-FDG is used to diagnose gliomas, patients are required to visit the hospital 2 times. In the current one-day protocol, after 13N-ammonia PET is acquired, intravenous injection of 18F-FDG is administered after a 3-h interval. Notably, because of the short half-life of 13N and the urine excretion mechanism, 13N-ammonia is already cleared from the body. Therefore, it would not affect the two PET tracers; this enables same-day evaluation of 13N-ammonia and 18F-FDG PET. Finally, this approach was beneficial to the patients, who were not required to travel to our PET center 2 times. In addition, according to the present study,<a class="elsevierStyleCrossRef" href="#bib0155">31</a> the patient effective dose for 13N-ammonia brain PET/CT (active from 555 to 740 MBq) was 4.35–5.57 mSv, which is below the 5.2 ± 0.5 mSv dose for 11C-MET. This radiation dose is below the threshold established by the International Commission on Radiological Protection (ICRP); therefore, excess radiation dose caused by 13N-ammonia is not a concern with our new approach.In this study, we have presented decoupling score as a new voxel-wise method for evaluating 18F-FDG and 13N-ammonia uptake in LGGs. Although registration-based voxel-by-voxel analysis has shown promising results and comprises a new analytical method for the prediction of LGGs and inflammatory lesions, there are some inherent limitations in this study. First, the present study used small sample sizes of patients with LGGs or BILs; thus, these results should be further validated in prospective studies with a larger sample size. Second, clinical follow-up, rather than histopathology, was used in some patients with BILs. Finally, 13N-ammonia had an extremely short half-life (approximately 10 min); thus, a cyclotron is needed on-site for clinical use of 13N-ammonia.ConclusionsIn conclusion, a one-day protocol for 18F-FDG and 13N-ammonia PET/CT with uptake decoupling score was implemented to analyze deviation of 18F-FDG and 13N-ammonia uptake in treatment-naïve LGGs and BILs. The present results showed that the 18F-FDG–13N-ammonia decoupling score was superior for detecting LGGs, compared to 18F-FDG or 13N-ammonia uptake alone. Thus, this method seems feasible, and may constitute an analytical approach for semi-quantitative image analysis to discriminate between LGGs and BILs." "textoCompletoSecciones" => array:1 [ "secciones" => array:11 [ 0 => array:3 [ "identificador" => "xres1311963" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Purpose" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1211112" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1311964" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0006" "titulo" => "Propósito" ] 1 => array:2 [ "identificador" => "abst0013" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0014" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0018" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1211113" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:5 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Patients" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "PET data acquisition" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "Data analysis" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Decoupling score calculation" ] 4 => array:2 [ "identificador" => "sec0035" "titulo" => "Statistical analysis" ] ] ] 6 => array:3 [ "identificador" => "sec0040" "titulo" => "Results" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0045" "titulo" => "Decoupling map reconstruction in LGG and BIL" ] 1 => array:2 [ "identificador" => "sec0050" "titulo" => "T/N ratios in LGG and BIL" ] 2 => array:2 [ "identificador" => "sec0055" "titulo" => "Decoupling score in LGGs and BILs" ] ] ] 7 => array:2 [ "identificador" => "sec0060" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0065" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "xack452187" "titulo" => "Acknowledgements" ] 10 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2019-04-18" "fechaAceptado" => "2019-08-27" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1211112" "palabras" => array:5 [ 0 => "One-Day protocol" 1 => "13N-ammonia" 2 => "18F-FDG" 3 => "Voxel-Wise analysis" 4 => "Low-Grade gliomas" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1211113" "palabras" => array:5 [ 0 => "protocolo de un día" 1 => "13N-amonio" 2 => "18F-FDG" 3 => "análisis de voxel" 4 => "gliomas de bajo grado" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "PurposeAccurate identification of low-grade gliomas (LGGs; World Health Organization grades I and II) and their differentiation from brain inflammation lesions (BILs) remains difficult; however, it is essential for treatment. This study assessed whether a one-day protocol for voxel-wise 18F-FDG and 13N-ammonia PET/CT with uptake decoupling analysis could differentiate LGGs from BILs. Materials and methodsTwenty-eight patients with LGGs and 16 patients with BILs underwent 18F-FDG and 13N-ammonia PET/CT on the same day before any type of therapy. The decoupling score and tumor-to-normal tissue (T/N) ratio of 18F-FDG and 13N-ammonia were calculated at each location. Student’s t-test was used to compare values, and ROC curve analysis was used to establish a cut-off value for the T/N ratio and decoupling score. Area under the curve (AUC) was calculated to evaluate differential efficacy. ResultsSignificant differences were observed in 13N-ammonia T/N ratio (p = 0.018) and decoupling score (p = 0.003) between LGGs and BILs; however, the 18F-FDG T/N ratio did not show any differences (p = 0.413). Optimal cut-off values for 18F-FDG T/N ratio, 13N-ammonia T/N ratio, and decoupling score were 0.73, 0.97, and 2.31, respectively, with corresponding AUCs of 0.48, 0.68, and 0.77. The respective sensitivity, specificity, and accuracy parameters using these cut-off values were 53.6%, 62.5%, and 56.8%, respectively, for 18F-FDG; 50.0%, 75.0%, and 59.1%, respectively, for 13N-ammonia; and 60.7%, 93.8%, and 72.7%, respectively, for decoupling score. Conclusions18F-FDG/13N-ammonia uptake decoupling score can be used to discriminate between LGGs and BILs. Use of a decoupling map of these two tracers can improve visual analysis and diagnostic accuracy." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Purpose" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "PropósitoLa identificación precisa de los gliomas de bajo grado (LGGs; grados I y II de la Organización Mundial de la Salud) y su diferenciación de las lesiones por inflamación cerebral (BILs) sigue siendo difícil; sin embargo, es esencial para el tratamiento. Este estudio evaluó si un protocolo de un día para la TEP/TC con amoníaco 18F-FDG y 13Namoníaco con análisis de desacoplamiento de la captación podría diferenciar los LGG de los BIL. Materiales y métodosVeintiocho pacientes con GLG y 16 pacientes con BIL se sometieron a TEP/TC con 18F-FDG y 13N-amoníaco el mismo día antes de cualquier tipo de terapia. La puntuación de desacoplamiento y la relación tumor/tejido normal (T/N) de 18F-FDG y 13N-amoníaco se calcularon en cada localización. Se utilizó la prueba t de Student para comparar valores, y el análisis de la curva ROC para establecer un valor de corte para la relación T/N y la puntuación de desacoplamiento. Se calculó la CUA para evaluar la eficacia diferencial. ResultadosSe observaron diferencias significativas en la relación T/N de 13N-amoníaco (p=0,018) y en la puntuación de desacoplamiento (p=0,003) entre los LGG y los BIL; sin embargo, la relación T/N de 18F-FDG no mostró ninguna diferencia (p=0,413). Los valores de corte óptimos para la relación T/N de 18F-FDG, la relación T/N de 13N-amoníaco y la puntuación de desacoplamiento fueron 0,73, 0,97 y 2,31, respectivamente, con AUC correspondientes de 0,48, 0,68 y 0,77. Los respectivos parámetros de sensibilidad, especificidad y precisión que utilizan estos valores de corte fueron 53,6%, 62,5% y 56,8%, respectivamente, para 18F-FDG; 50,0%, 75,0% y 59,1%, respectivamente, para la amoníaco 13N; y 60,7%, 93,8% y 72,7%, respectivamente, para la puntuación de desacoplamiento. ConclusionesLa puntuación de desacoplamiento de la captación de amoníaco 18FFDG/ 13N se puede utilizar para discriminar entre LGG y BIL. El uso de un mapa de desacoplamiento de estos dos trazadores puede mejorar el análisis visual y la precisión del diagnóstico." "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0006" "titulo" => "Propósito" ] 1 => array:2 [ "identificador" => "abst0013" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0014" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0018" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "Please cite this article as: Yi C, Quirce R, Yu D, Shi X, Luo G, Zhang B, Lu Y, Zeng R, He Q, Zhang X. Protocolo de un día para la TEP/TC con amoníaco 18F-FDG y 13N con puntuación de desacoplamiento de la captación para diferenciar el glioma de bajo grado no tratado de la inflamación. Rev Esp Med Nucl Imagen Mol. 2020;39:68–74." ] 1 => array:3 [ "etiqueta" => "1" "nota" => "Chang Yi and Donglan Yu contributed equally to this work." "identificador" => "fn0005" ] ] "multimedia" => array:8 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 991 "Ancho" => 2508 "Tamanyo" => 347855 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Patient examples: region of interest (ROI) near the midline of the brain shows the lesion, ROI in the cerebral cortex shows normal tissue. a. A 30-year-old woman with grade II astrocytoma in the thalamus. <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG tumor-to-normal tissue (T/N) ratio map shows decreased uptake of <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG in the lesion, while <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia T/N ratio map shows increased uptake of <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia in the same lesion. Decoupling score map shows high decoupling scores in this lesion. Decoupling scores in each voxel were calculated using the expected linear regression line of <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia within normal brain. b. A 45-year-old woman with grade II oligodendrogliomas in the right frontal lobe next to the longitudinal fissure. Decreased uptake of both <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia was observed for this lesion in T/N ratio maps, which were not helpful for the diagnosis of the lesions. The decoupling score map showed high decoupling scores in the lesion." ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 1855 "Ancho" => 2925 "Tamanyo" => 491248 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Representative case of a 54-year-old man with a brain inflammation lesion. a. The region of interest shows the lesion in computed tomography images. b and c. Markedly increased uptake of <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG (b) and decreased uptake of <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia (c) were present in tumor-to-normal tissue (T/N) ratio maps. d. Correlation was determined between <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia uptake within normal brain. e. The lesion in the decoupling map appears lower than surrounding normal brain tissue." ] ] 2 => array:8 [ "identificador" => "fig0015" "etiqueta" => "Fig. 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 1288 "Ancho" => 1508 "Tamanyo" => 112433 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "Receiver operating characteristic analysis for detecting lesions with <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG tumor-to-normal tissue (T/N) ratio, <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia T/N ratio, and decoupling score. The decoupling score showed the best performance, with a cutoff value of 2.31 (area under the curve, AUC: 0.77), whereas the cutoff values for T/N ratio of <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia uptake were 0.73 (AUC: 0.48) and 0.97 (AUC: 0.68), respectively." ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Diagnosis \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No. of patients \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Age (Years) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No. of Sex (M/F) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No. of diagnoses(histologic/follow-up) \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40.11 ± 15.86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23/21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34/10 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Inflammation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46.38 ± 16.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8/8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6/10 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Encephalitis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38.00 ± 13.74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2/2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−/4 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Brain abscess \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.67 ± 12.34 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2/1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demyelination \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41.25 ± 13.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3/5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2/6 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fungal infection \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1/- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LGGs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36.53 ± 14.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15/13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade I \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.00 ± 3.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3/1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39.30 ± 13.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12/12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Astrocytoma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">39.30 ± 15.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11/8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Oligodendrogliomas \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.50 ± 9.68 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1/3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4/− \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Oligoastrocytomas \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">46 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">-/1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1/− \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2248631.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Patient characteristics." ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Diagnosis</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">FDG T/N ratio (average)</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NH3 T/N ratio (average)</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Decoupling score (average)</th></tr><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.80 ± 0.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02˜3.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 ± 0.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07˜3.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.20 ± 0.71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−8.82˜9.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Inflammation \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.88 ± 0.52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02˜3.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.84 ± 0.22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07˜3.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.72 ± 0.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−8.82˜5.44 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Encephalitis \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.64 ± 0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.24˜1.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.75 ± 0.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.20˜1.38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.58 ± 0.76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.51˜4.25 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Brain abscess \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.95 ± 0.32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02˜2.16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.83 ± 0.26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07˜1.50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.37 ± 0.76 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−1.39˜4.05 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demyelination \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.05 ± 0.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04˜3.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.93 ± 0.24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.11˜3.20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.98 ± 0.55 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−8.82˜5.44 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fungal infection \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.13˜1.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.16˜1.26 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−0.62˜3.06 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">LGGs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.76 ± 0.23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.10˜1.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.00 ± 0.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.30˜2.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.48 ± 0.62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.58˜9.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade I \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.91 ± 0.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.27˜1.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.05 ± 0.21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.51˜1.43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.36 ± 0.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.28˜5.18 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Grade II \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.73 ± 0.22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.10˜1.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.99 ± 0.17 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.30˜2.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.50 ± 0.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.58˜9.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Astrocytoma \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.77 ± 0.22 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.19˜1.82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.02 ± 0.18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.30˜2.72 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.57 ± 0.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">−4.58˜9.38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Oligodendrogliomas \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.55 ± 0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.10˜1.28 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.85 ± 0.10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.31˜1.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.15 ± 0.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.29˜6.74 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Oligoastrocytomas \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.81 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.38˜1.24 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.98 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.56˜1.36 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.49 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.72˜5.17 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2248630.png" ] ] ] ] "descripcion" => array:1 [ "en" => "PET results of T/N ratios and decoupling score for <a class="elsevierStyleCrossRef" href="#bib0065">13</a>N-ammonia and <a class="elsevierStyleCrossRef" href="#bib0090">18</a>F-FDG PET." ] ] 5 => array:5 [ "identificador" => "eq0005" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:1 [ "Quimica" => "(13N-ammonia) = α (18F-FDG) + β" ] ] 6 => array:6 [ "identificador" => "eq0010" "etiqueta" => "(1)" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Deviation(i)=N13-ammonia-αF18-FDG-βα2-1" "Fichero" => "STRIPIN_si3.jpeg" "Tamanyo" => 2843 "Alto" => 40 "Ancho" => 245 ] ] 7 => array:6 [ "identificador" => "eq0015" "etiqueta" => "(2)" "tipo" => "MULTIMEDIAFORMULA" "mostrarFloat" => false "mostrarDisplay" => true "Formula" => array:5 [ "Matematica" => "Score(i)=Deviation(i)-μσ" "Fichero" => "STRIPIN_si4.jpeg" "Tamanyo" => 1966 "Alto" => 32 "Ancho" => 173 ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:31 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Low-grade gliomas" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "D.A. Forst" 1 => "B.V. Nahed" 2 => "J.S. Loeffler" 3 => "T.T. Batchelor" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Oncologist" "fecha" => "2014" "volumen" => "19" "paginaInicial" => "403" "paginaFinal" => "413" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "Cancer Genome Atlas Research Network" 1 => "D.J. Brat" 2 => "R.G. Verhaak" 3 => "K.D. Aldape" 4 => "W.K. Yung" 5 => "S.R. Salama" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1056/NEJMoa1402121" "Revista" => array:6 [ "tituloSerie" => "N Engl J Med" "fecha" => "2015" "volumen" => "372" "paginaInicial" => "2481" "paginaFinal" => "2498" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26061751" "web" => "Medline" ] ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Primary brain tumours in adults" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "D. Ricard" 1 => "A. Idbaih" 2 => "F. Ducray" 3 => "M. Lahutte" 4 => "K. Hoang-Xuan" 5 => "J.Y. 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Original Article

One-day protocol for 18F-FDG and 13N-ammonia PET/CT with uptake decoupling score in differentiating untreated low-grade glioma from inflammation

Protocolo de un día para la TEP/TC con amoníaco 18F-FDG y 13N con puntuación de desacoplamiento de la captación para diferenciar el glioma de bajo grado no tratado de la inflamación

Y. Changa,1, Y. Donglanb,1, S. Xinchonga, L. Ganhuaa, Z. Binga, L. Yaoc, Z. Rutongc, H. Qiaoa, Z. Xiangsonga,

Corresponding author

xiaolong-4310@163.com

Corresponding author at: Department of Nuclear Medicine, the First Affiliated Hospital of Sun Yat-Sen University. Zhongshan Er Road 58#, Guangzhou, China.

a Department of Nuclear Medicine, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

b Department of Medical Engineering, the First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China

c School of Data and Computer Science, Sun Yat-Sen University, Guangzhou, China

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          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic analysis for detecting lesions with <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG tumor-to-normal tissue &#40;T&#47;N&#41; ratio&#44; <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia T&#47;N ratio&#44; and decoupling score&#46; The decoupling score showed the best performance&#44; with a cutoff value of 2&#46;31 &#40;area under the curve&#44; AUC&#58; 0&#46;77&#41;&#44; whereas the cutoff values for T&#47;N ratio of <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia uptake were 0&#46;73 &#40;AUC&#58; 0&#46;48&#41; and 0&#46;97 &#40;AUC&#58; 0&#46;68&#41;&#44; respectively&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Low-grade gliomas &#40;LGGs&#59; World Health Organization &#91;WHO&#93; grades I and II&#41; are a diverse group of primary brain tumors that often arise in young&#44; otherwise healthy patients&#59; these commonly follow an indolent course and exhibit long-term survival&#44; which contrasts with the prognosis of high-grade gliomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;2</span></a> Accurate diagnosis and grading are critical for management of LGGs&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> Although histopathological examination of tissue remains the gold standard for diagnosis and grading of LGGs&#44; preoperative imaging is essential to distinguish between inflammation and tumor&#46; However&#44; gliomas are often histologically heterogeneous&#44; with evolving anaplastic areas within a low-grade tumor&#59; moreover&#44; contrast-enhancement on CT or MRI does not provide a good marker for anaplastic tissue detection&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> The development of radiolabeled tracers has enabled metabolic and molecular imaging to play a major role in the management of gliomas&#44; such as PET&#46; To successfully use PET data in glioma treatment&#44; PET can be integrated in the planning of image-guided biopsy&#44; resection&#44; and radiosurgery&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> Additionally&#44; amino acid tracers have a high sensitivity for detection of LGGs&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> Notably&#44; fluorothymidine is useful in grading gliomas&#44; as is dynamic PET using fluoroethyltyrosine &#40;FET&#41; for tumor grading&#59;<a class="elsevierStyleCrossRefs" href="#bib0030"><span class="elsevierStyleSup">6&#8211;8</span></a> however&#44; these tracers are either complicated to synthesize&#44; with low yields&#44; or require a complex acquisition protocol&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">In a previous study&#44; we found that <span class="elsevierStyleSup">13</span>N-ammonia PET was superior to <span class="elsevierStyleSup">18</span>F-FDG PET and contrast-enhanced MRI for grading of untreated gliomas and that it could be used for the detection of high-grade gliomas and recurrent astrocytomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9&#8211;11</span></a> Thus far&#44; differentiation between neoplastic and non-neoplastic lesions has been evaluated in several studies&#46;<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12&#44;13</span></a> However&#44; our recent study found that <span class="elsevierStyleSup">13</span>N-ammonia was effective in distinguishing high-grade gliomas from low-grade gliomas and inflammation&#44; but its role in differential diagnose of low-grade gliomas and brain inflammatory lesions was limited&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> This might be attributed to difficulty in discriminating between brain inflammation lesions &#40;BILs&#41; and LGGs by using conventional imaging modalities&#59; furthermore&#44; there are no established quantification approaches for image analysis using <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">In this retrospective study&#44; we performed voxel-wise analysis of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia PET in tumor and inflammation-infiltrative brain lesions&#44; in an attempt to discriminate between benign lesions and LGGs using decoupling score&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Patients</span><p id="par0020" class="elsevierStylePara elsevierViewall">This study was performed between july 2011 and may 2016&#46; A total of 28 patients with a final diagnosis of LGG &#40;13 female and 15 male patients&#59; mean age&#44; 36&#46;53&#8239;&#177;&#8239;14&#46;59 years&#59; age range&#44; 14&#8211;67 years&#41; and 16 patients with a final diagnosis of BIL &#40;8 female and 8 male patients&#59; mean age&#44; 46&#46;38&#8239;&#177;&#8239;16&#46;49 years&#59; range&#44; 23&#8211;73 years&#41; were included in this study&#46; Patients with any previous treatments were excluded &#40;e&#46;g&#46;&#44; corticosteroids&#44; surgery&#44; chemotherapy&#44; radiotherapy&#44; or gamma-knife therapy&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> All patients underwent <span class="elsevierStyleSup">13</span>N-ammonia PET&#47;CT and <span class="elsevierStyleSup">18</span>F-FDG PET&#47;CT on the same day &#40;FDG PET&#47;CT was performed after ammonia PET&#47;CT&#44; with a minimum interval of 2&#8239;h&#41;&#46; In 34 patients&#44; pathological diagnosis was obtained by tumor resection or biopsy after PET examination&#46; Four patients had grade I glioma&#44; according to the WHO classification&#44; whereas 24 had WHO grade II glioma &#40;19 were astrocytoma&#44; 4 were oligodendroglioma&#44; and 1 was oligoastrocytoma&#41;&#46; The remaining patients had BILs &#40;3 were brain abscess&#44; 2 were demyelination&#44; and 1 was fungal infection&#41;&#46; In 10 patients&#44; the results of pathological examination could not be obtained&#59; thus&#44; the diagnosis of inflammation was based on radiological &#40;CT and MRI&#41; and clinical investigation&#46; The patients&#8217; characteristics are summarized in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0025" class="elsevierStylePara elsevierViewall">The study of <span class="elsevierStyleSup">13</span>N-ammonia imaging has been approved by the ethics committee of our hospital&#46; Although formal consent was not required for this retrospective study&#44; all subjects agreed to participate in this study after receiving an explanation of detailed study purpose and imaging procedure&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">PET data acquisition</span><p id="par0030" class="elsevierStylePara elsevierViewall">Tracers were produced at our center by using standard techniques and commercially available system for isotope generation &#40;Cyclone-10&#44; Ion Beam Applications&#59; Louvain-La-Neuve&#44; Belgium&#41;&#46; PET&#47;CT imaging was performed with a Gemini GXL 16 scanner &#40;Philips&#44; Amsterdam&#44; Netherlands&#41; in a 3-dimensional &#40;3D&#41; acquisition mode&#46; The specific imaging protocol for the brain was selected as field of view &#40;FOV&#41; 180&#8239;mm&#44; and the transaxial spatial resolution was 2&#8239;mm full width at half maximum &#40;FWHM&#41; at the center of the FOV for <span class="elsevierStyleSup">18</span>F-FDG&#46; The spatial resolution of <span class="elsevierStyleSup">13</span>N-ammonia imaging was lower than that of <span class="elsevierStyleSup">18</span>F-FDG because of the difference in positron energy&#46; PET images were reconstructed by the Line of Response RAMLA algorithm with low-dose CT images for attenuation correction&#44; resulting in 3D images comprising 128&#8239;&#215;&#8239;128&#8239;&#215;&#8239;90 voxels of 2&#46;0&#8239;&#215;&#8239;2&#46;0&#8239;&#215;&#8239;2&#46;0 mm<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a>&#46;<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9&#44;10</span></a></p><p id="par0035" class="elsevierStylePara elsevierViewall">All subjects fasted for at least 8&#8239;h before PET&#47;CT imaging&#46; Ammonia and FDG PET&#47;CT studies were performed on the same day&#44; as described above&#46; The 10-min PET acquisition began 5&#8239;min after an intravenous injection of <span class="elsevierStyleSup">13</span>N-ammonia &#40;555&#8211;740&#8239;MBq&#41; or 45&#8211;60&#8239;min after an intravenous injection of <span class="elsevierStyleSup">18</span>F-FDG &#40;5&#46;18&#8239;MBq&#47;kg&#41;&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Data analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">One experienced nuclear medicine physician&#44; who was blinded to the clinical and structural imaging findings&#44; evaluated the PET&#47;CT images&#46; PET images were converted to NII format and co-registered using SPM software &#40;Functional Imaging Laboratory&#44; Wellcome Trust Centre for Neuroimaging&#44; Institute of Neurology&#44; UCL&#44; London&#44; UK&#41;&#46; The registration of the images was confirmed visually&#46;</p><p id="par0045" class="elsevierStylePara elsevierViewall">Lesion uptake was evaluated by semiquantitative analysis&#46; Regions of interest &#40;ROIs&#41; for each lesion were outlined in the area with the highest activity&#44; and the location of the lesion was determined by using CT image guidance to avoid misplacement&#46; For lesions that did not show higher uptake than the surrounding tissue&#44; ROIs were defined on CT images after co-registering the PET and CT images&#46; All ROIs of each tumor were placed carefully to avoid areas of necrosis&#44; hemorrhage&#44; or normal tissue&#59; in addition&#44; the first and the last slices of each tumor were not used&#44; to avoid the volume effect&#46; For reference tissue&#44; ROIs were selected at the uninvolved contralateral hemisphere of the same slice of the lesion ROI&#44; including both gray and white matter&#46; The average standardized uptake value &#40;SUV&#41; of all regions was used to calculate the tumor to normal tissue &#40;T&#47;N&#41; ratio&#44; enabling reconstruction of a T&#47;N ratio image&#46;</p><p id="par0050" class="elsevierStylePara elsevierViewall">All datasets &#40;standard anatomical images and PET data&#41; were exported to in-house software written in MATLAB 7&#46;6 &#40;MathWorks&#44; Natick&#44; MA&#44; USA&#41; for further analysis&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Decoupling score calculation</span><p id="par0055" class="elsevierStylePara elsevierViewall">As illustrated in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#44; a linear relationship between <span class="elsevierStyleSup">13</span>N-ammonia uptake and <span class="elsevierStyleSup">18</span>F-FDG uptake in normal brain was observedas follows&#58;<elsevierMultimedia ident="eq0005"></elsevierMultimedia>where &#40;<span class="elsevierStyleSup">13</span>N-ammonia&#41; and &#40;<span class="elsevierStyleSup">18</span>F-FDG&#41; represent the T&#47;N ratios of <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG PET&#44; respectively&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">Subsequently&#44; calculate the deviation of each data point &#40;i&#41; from the expected linear regression fit as follows&#58;<elsevierMultimedia ident="eq0010"></elsevierMultimedia>where &#40;<span class="elsevierStyleSup">13</span>N-ammonia&#41; and &#40;<span class="elsevierStyleSup">18</span>F-FDG&#41; represent the T&#47;N ratios of <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG PET&#44; respectively&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">The decoupling score of each data point was defined as follows&#58;<elsevierMultimedia ident="eq0015"></elsevierMultimedia>where &#181; and &#963; represent the mean and standard deviation of deviation &#40;i&#41; for the ROI located in the normal brain&#46; This score &#40;i&#41; could be used to quantify the difference between <span class="elsevierStyleSup">13</span>N-ammonia uptake and <span class="elsevierStyleSup">18</span>F-FDG uptake in brain lesions&#46;<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#44;16</span></a></p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">Statistical analysis was conducted on the platform of PASW Statistics 18&#46;0 &#40;IBM&#44; Armonk&#44; NY&#44; USA&#41;&#46; Sensitivity&#44; specificity&#44; negative predictive value &#40;NPV&#41;&#44; and positive predictive value &#40;PPV&#41; with 95&#37; confidence intervals &#40;CI&#41; were calculated for each tracer with T&#47;N ratios&#46; Student&#8217;s t-test was used to compare T&#47;N ratios and decoupling scores of each tracer between LGGs and BILs&#46; Receiver operating characteristic &#40;ROC&#41; analysis was used to establish a cut-off value for the decoupling score&#44; and the area under the curve &#40;AUC&#41; was calculated to evaluate differential efficacy&#46; Results were considered significant at the level of p&#8239;&#60;&#8239;0&#46;05&#46;</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Results</span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Decoupling map reconstruction in LGG and BIL</span><p id="par0075" class="elsevierStylePara elsevierViewall">According to visual analysis&#44; decoupling scores were markedly increased in the tumors&#44; compared to surrounding normal brain tissues&#59; this allowed precise delineation of the extent of tumor &#40;<a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>&#41;&#46; Conversely&#44; decoupling scores of BILs were similar to or lower than those of surrounding normal brain tissue &#40;<a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#41;&#46; In <span class="elsevierStyleSup">18</span>F-FDG or <span class="elsevierStyleSup">13</span>N-ammonia T&#47;N ratio maps&#44; LGGs and BILs did not exhibit fixed patterns of expression and were higher or lower than surrounding normal brain tissues&#46; Tumor boundaries were always more clearly delineated in the decoupling map than in the T&#47;N ratio map&#46;</p><elsevierMultimedia ident="fig0010"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">T&#47;N ratios in LGG and BIL</span><p id="par0080" class="elsevierStylePara elsevierViewall">The T&#47;N ratios of <span class="elsevierStyleSup">18</span>F-FDG were lower than those of <span class="elsevierStyleSup">13</span>N-ammonia in LGGs &#40;mean&#8239;&#177;&#8239;standard deviation&#44; 0&#46;76&#8239;&#177;&#8239;0&#46;23 vs&#46; 1&#46;00&#8239;&#177;&#8239;0&#46;18&#44; t&#8239;&#61;&#8239;&#8722;6&#46;718&#44; p&#8239;&#60;&#8239;0&#46;001&#41;&#46; However&#44; no significant difference was observed between <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia in BILs &#40;0&#46;88&#8239;&#177;&#8239;0&#46;52 vs&#46; 0&#46;84&#8239;&#177;&#8239;0&#46;22&#44; t&#8239;&#61;&#8239;0&#46;330&#44; p&#8239;&#61;&#8239;0&#46;746&#41;&#46; The T&#47;N ratios of <span class="elsevierStyleSup">18</span>F-FDG uptake were not useful for differentiating LGGs from BILs &#40;LGG vs&#46; BIL&#58; 0&#46;76&#8239;&#177;&#8239;0&#46;23 vs&#46; 0&#46;88&#8239;&#177;&#8239;0&#46;52&#44; t&#8239;&#61;&#8239;&#8722;0&#46;836&#44; p&#8239;&#61;&#8239;0&#46;413&#41;&#44; whereas the T&#47;N ratios of <span class="elsevierStyleSup">13</span>N-ammonia &#40;LGG vs&#46; BIL&#58; 1&#46;00&#8239;&#177;&#8239;0&#46;18 vs&#46; 0&#46;84&#8239;&#177;&#8239;0&#46;22&#44; t&#8239;&#61;&#8239;2&#46;519&#44; p&#8239;&#61;&#8239;0&#46;018&#41; uptake were better performance than those of <span class="elsevierStyleSup">18</span>F-FDG in differentiating LGGs from BILs&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">ROC analysis yielded optimal T&#47;N cut-off values of 0&#46;73 for <span class="elsevierStyleSup">18</span>F-FDG and 0&#46;97 for <span class="elsevierStyleSup">13</span>N-ammonia for differentiating between LGGs and BILs&#59; the respective AUCs were 0&#46;48 and 0&#46;68&#46; For prediction of LGGs using these optimal cut-off values&#44; the respective sensitivity&#44; specificity&#44; accuracy&#44; PPV&#44; and NPV were 53&#46;6&#37; &#40;15&#47;28&#41;&#44; 62&#46;5&#37; &#40;10&#47;16&#41;&#44; 56&#46;8&#37; &#40;25&#47;44&#41;&#44; 71&#46;4&#37; &#40;15&#47;21&#41;&#44; and 43&#46;5&#37; &#40;10&#47;23&#41; for <span class="elsevierStyleSup">18</span>F-FDG&#59; they were 50&#46;0&#37; &#40;14&#47;28&#41;&#44; 75&#46;0&#37; &#40;12&#47;16&#41;&#44; 59&#46;1&#37; &#40;26&#47;44&#41;&#44; 77&#46;8&#37; &#40;14&#47;18&#41;&#44; and 46&#46;2&#37; &#40;12&#47;26&#41; for <span class="elsevierStyleSup">13</span>N-ammonia&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Decoupling score in LGGs and BILs</span><p id="par0090" class="elsevierStylePara elsevierViewall">The average decoupling scores of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia were calculated for both LGGs and BILs&#59; these were 2&#46;48&#8239;&#177;&#8239;0&#46;62 and 1&#46;72&#8239;&#177;&#8239;0&#46;61&#44; respectively&#44; demonstrating a significant difference &#40;t&#8239;&#61;&#8239;3&#46;252&#44; p&#8239;&#61;&#8239;0&#46;003&#41;&#46; The optimal T&#47;N cut-off value for the decoupling score to differentiate between LGG and BIL&#44; as determined by ROC curve analysis&#44; was 2&#46;31 &#40;AUC&#44; 0&#46;77&#41; &#40;<a class="elsevierStyleCrossRef" href="#fig0015">Fig&#46; 3</a>&#41;&#46; For the diagnosis of LGG using the optimal cut-off values&#44; the respective sensitivity&#44; specificity&#44; accuracy&#44; PPV&#44; and NPV were 60&#46;7&#37; &#40;17&#47;28&#41;&#44; 93&#46;8&#37; &#40;15&#47;16&#41;&#44; 72&#46;7&#37; &#40;32&#47;44&#41;&#44; 94&#46;4&#37; &#40;17&#47;18&#41;&#44; and 57&#46;7&#37; &#40;15&#47;26&#41;&#46; <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> summarizes the PET results of T&#47;N ratios and decoupling scores for <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG PET uptake studies&#46;</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Discussion</span><p id="par0095" class="elsevierStylePara elsevierViewall">Although molecular diagnostics &#40;e&#46;g&#46;&#44; chromosomal and gene array technologies&#41; are becoming increasingly beneficial for understanding tumor genetic heterogeneity&#44; <a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> these approaches always require invasive tissue analysis and therefore cannot fully replace non-invasive diagnostics&#46; MRI&#44; with or without gadolinium&#44; remains the gold standard for noninvasive diagnosis and follow-up of patients with gliomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0005"><span class="elsevierStyleSup">1&#44;3&#44;4</span></a> In patients with a suspected brain tumor&#44; anatomic imaging sequences typically include T1- and T2-weighted MR sequences&#44; as well as fluid attenuation inversion recovery MR sequences&#59; T1- weighted imaging is performed after administration of gadolinium-based contrast&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> However&#44; this technique only indirectly reflects the biological activity of the tumor by detecting destruction of the blood-brain barrier&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Therefore&#44; routine MRI lacks accuracy in terms of non-invasive assessment&#44; especially for LGGs and BILs&#46; Although advanced MR techniques &#40;e&#46;g&#46;&#44; perfusion imaging&#44; diffusion-weighted imaging&#44; diffusion tensor imaging&#44; and MR spectroscopy&#41; provide some metabolic and functional information for differentiating gliomas from non-neoplastic brain lesions&#44;<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">20&#8211;22</span></a> they also involve some limitations&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> These drawbacks include&#58; partial volume effects&#44; non-standardized acquisition&#44; and a postprocessing protocol that is non-specific for LGGs&#46; Herein&#44; the molecular information provided by PET is valuable in its ability to supplement additional imaging data&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a><span class="elsevierStyleSup">18</span>F-FDG and amino-acid tracers&#44; such as <span class="elsevierStyleSup">11</span>C-methionine &#40;<span class="elsevierStyleSup">11</span>C-MET&#41;&#44; <span class="elsevierStyleSup">18</span>F-FET&#44; and <span class="elsevierStyleSup">18</span>F-FDOPA&#44; provide corresponding metabolic data that enable precise assessment of glioma extension&#44; detection of anaplastic areas&#44; and postoperative follow-up&#46;<a class="elsevierStyleCrossRefs" href="#bib0115"><span class="elsevierStyleSup">23&#8211;25</span></a> These methods have high sensitivity&#44; as well as positive results&#44; in both acute and chronic inflammation&#46; Previously&#44; we reported that <span class="elsevierStyleSup">13</span>N-ammonia&#44; combined with <span class="elsevierStyleSup">18</span>F-FDG&#44; exhibits great potential for the diagnosis&#44; grading&#44; and postoperative follow-up of intracranial lesions&#46;<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9&#8211;11</span></a> Moreover&#44; we analyzed the application of <span class="elsevierStyleSup">13</span>N-ammonia in the diagnosis of glioma and inflammatory lesions&#44; concluding that <span class="elsevierStyleSup">13</span>N-ammonia could distinguish high-grade gliomas from low-grade gliomas and inflammations&#44; but could not distinguish low-grade gliomas from inflammatory lesions&#46;<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> Therefore&#44; we used a new voxel-wise analysis to process <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG uptake in both LGGs and inflammatory lesions&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">Our previous reports showed that <span class="elsevierStyleSup">13</span>N-ammonia uptake was higher than <span class="elsevierStyleSup">18</span>F-FDG uptake in high-grade gliomas and meningiomas&#44;<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9&#44;26</span></a> while <span class="elsevierStyleSup">13</span>N-ammonia uptake was lower than <span class="elsevierStyleSup">18</span>F-FDG uptake in brain abscesses and primary central nervous system lymphomas&#46;<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10&#44;27</span></a> However&#44; LGGs and BILs showed heterogeneous uptake in both <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG&#46; As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>b&#44; lesions &#40;WHO grade &#8545; oligodendroglioma&#41; showed lower <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake than normal brain tissues&#46; The average T&#47;N ratios of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake&#44; obtained from 16 layers of lesions&#44; were 0&#46;55 and 0&#46;93&#44; respectively&#46; These results were not helpful in the diagnosis of the lesions&#46; Conversely&#44; a remarkably high decoupling score was observed in the lesions in the decoupling map&#44; which could be helpful for diagnosis&#46; Similarly&#44; as shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig&#46; 1</a>a&#44; lesions &#40;WHO grade &#8545; astrocytoma&#41; showed lower <span class="elsevierStyleSup">18</span>F-FDG uptake&#44; but higher <span class="elsevierStyleSup">13</span>N-ammonia uptake and decoupling score&#44; compared to normal brain tissues&#46; Furthermore&#44; as shown in <a class="elsevierStyleCrossRef" href="#fig0010">Fig&#46; 2</a>&#44; lesions &#40;inflammation&#41; showed higher <span class="elsevierStyleSup">18</span>F-FDG uptake&#44; but lower <span class="elsevierStyleSup">13</span>N-ammonia uptake and decoupling score&#44; compared to normal brain tissues&#46; ROC analysis revealed the optimal performance of the decoupling score at a cut-off value of 2&#46;31 &#40;sensitivity&#44; 60&#46;7&#37;&#59; specificity&#44; 93&#46;8&#37;&#41;&#44; with an AUC of 0&#46;77&#46; This result indicated that the decoupling score is a better surrogate indicator for discriminating between LGGs and BILs&#44; compared to <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG PET alone&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">Many studies have shown that amino acid tracers were used in the management of patients with low-grade gliomas&#44; but few have directly compared their differential efficacy to differentiate LGGs and inflammation&#46; Kracht et al&#46; reported <span class="elsevierStyleSup">11</span>C-MET PET in 13 LGGs and 3 nontumor lesions patients with 87&#37; sensitivity and 89&#37; specificity of 1&#46;3-fold <span class="elsevierStyleSup">11</span>C-MET uptake relative to normal brain tissue&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a><span class="elsevierStyleSup">18</span>F-FET PET also appeared to be superior to FDG-PET for biopsy planning in non-contrast-enhancing brain tumurs&#44; 69&#37; LGGs &#40;49&#47;71&#41; had been found increased <span class="elsevierStyleSup">18</span>F-FET uptake in Jansen NL study&#44; 8&#47;9 LGGs had increased 18F-FET uptake in Plotkin M study&#46;<a class="elsevierStyleCrossRefs" href="#bib0115"><span class="elsevierStyleSup">23&#44;24</span></a><span class="elsevierStyleSup">18</span>F-DOPA was also useful to discriminate low-grade gliomas from high-grade gliomas in 2&#46;16 SUVmax with 60&#37; sensitivity and 100&#37; specificity&#46;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> Compared with the above amino acid tracers&#44; the decoupling score of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia method has higher specificity &#40;93&#46;8&#37;&#41; to differentiate LGGs and BILs&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Some previous studies<a class="elsevierStyleCrossRefs" href="#bib0075"><span class="elsevierStyleSup">15&#44;16</span></a> have reported that <span class="elsevierStyleSup">18</span>F-FDG-<span class="elsevierStyleSup">11</span>C-methionine uptake decoupling score reflects glioma cell infiltration to assess glioma invasion&#46; Similarly&#44; a linear relationship could be inferred between <span class="elsevierStyleSup">13</span>N-ammonia uptake and <span class="elsevierStyleSup">18</span>F-FDG uptake in the normal brain&#44; such that <span class="elsevierStyleSup">18</span>F-FDG can be used as a reference index for <span class="elsevierStyleSup">13</span>N-ammonia uptake in normal brain tissues&#46; The decoupling score calculated at each voxel represents the magnitude of the disrupted correlation of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia at each location of the brain&#46;</p><p id="par0115" class="elsevierStylePara elsevierViewall">According to Cooper&#44;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> ammonia can act as a source of glutamine in the glutamine cycle&#46; Although inactive neovasculature provides a limited quantity of glutamine for trapping in LGGs&#44;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> deviation between <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake will be markedly evident in reconstructed images&#44; in the event of tumor infiltration&#46; Extreme decoupling of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake was observed in LGGs&#44; suggesting that the difference in <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake could be expressed as the decoupling score&#46; This difference implies that the decoupling score is based on tumor infiltration into brain tissue&#44; although the relationship between inflammation and gliomas is rather complex&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> As reported in some literature&#44; tumor was usually accompanied by inflammation&#44; but the microenvironment of glioma contains many coordination mechanisms that are different from inflammation&#44; include various glioma-secreted signaling factors such as cytokines&#44; chemokines&#44; and growth factors&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> As also&#44; <span class="elsevierStyleSup">13</span>N-ammonia is involved in the glioma cells glutamine cycle&#44; <span class="elsevierStyleSup">18</span>F-FDG is involved in the glioma cells glucose cycle&#46; It may be due to the difference in the intracellular metabolic patterns of the two imaging agents in inflammation and glioma&#44; which ultimately leads to the difference in the decoupling scores&#44; and the mechanism needs further research&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">When <span class="elsevierStyleSup">11</span>C-MET coupled with <span class="elsevierStyleSup">18</span>F-FDG is used to diagnose gliomas&#44; patients are required to visit the hospital 2 times&#46; In the current one-day protocol&#44; after <span class="elsevierStyleSup">13</span>N-ammonia PET is acquired&#44; intravenous injection of <span class="elsevierStyleSup">18</span>F-FDG is administered after a 3-h interval&#46; Notably&#44; because of the short half-life of <span class="elsevierStyleSup">13</span>N and the urine excretion mechanism&#44; <span class="elsevierStyleSup">13</span>N-ammonia is already cleared from the body&#46; Therefore&#44; it would not affect the two PET tracers&#59; this enables same-day evaluation of <span class="elsevierStyleSup">13</span>N-ammonia and <span class="elsevierStyleSup">18</span>F-FDG PET&#46; Finally&#44; this approach was beneficial to the patients&#44; who were not required to travel to our PET center 2 times&#46; In addition&#44; according to the present study&#44;<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a> the patient effective dose for <span class="elsevierStyleSup">13</span>N-ammonia brain PET&#47;CT &#40;active from 555 to 740&#8239;MBq&#41; was 4&#46;35&#8211;5&#46;57 mSv&#44; which is below the 5&#46;2&#8239;&#177;&#8239;0&#46;5&#8239;mSv dose for <span class="elsevierStyleSup">11</span>C-MET&#46; This radiation dose is below the threshold established by the International Commission on Radiological Protection &#40;ICRP&#41;&#59; therefore&#44; excess radiation dose caused by <span class="elsevierStyleSup">13</span>N-ammonia is not a concern with our new approach&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">In this study&#44; we have presented decoupling score as a new voxel-wise method for evaluating <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake in LGGs&#46; Although registration-based voxel-by-voxel analysis has shown promising results and comprises a new analytical method for the prediction of LGGs and inflammatory lesions&#44; there are some inherent limitations in this study&#46; First&#44; the present study used small sample sizes of patients with LGGs or BILs&#59; thus&#44; these results should be further validated in prospective studies with a larger sample size&#46; Second&#44; clinical follow-up&#44; rather than histopathology&#44; was used in some patients with BILs&#46; Finally&#44; <span class="elsevierStyleSup">13</span>N-ammonia had an extremely short half-life &#40;approximately 10&#8239;min&#41;&#59; thus&#44; a cyclotron is needed on-site for clinical use of <span class="elsevierStyleSup">13</span>N-ammonia&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Conclusions</span><p id="par0130" class="elsevierStylePara elsevierViewall">In conclusion&#44; a one-day protocol for <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia PET&#47;CT with uptake decoupling score was implemented to analyze deviation of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia uptake in treatment-na&#239;ve LGGs and BILs&#46; The present results showed that the <span class="elsevierStyleSup">18</span>F-FDG&#8211;<span class="elsevierStyleSup">13</span>N-ammonia decoupling score was superior for detecting LGGs&#44; compared to <span class="elsevierStyleSup">18</span>F-FDG or <span class="elsevierStyleSup">13</span>N-ammonia uptake alone&#46; Thus&#44; this method seems feasible&#44; and may constitute an analytical approach for semi-quantitative image analysis to discriminate between LGGs and BILs&#46;</p></span></span>"
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              "titulo" => "Prop&#243;sito"
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            1 => array:2 [
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              "titulo" => "PET data acquisition"
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              "identificador" => "sec0025"
              "titulo" => "Data analysis"
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              "titulo" => "Decoupling score calculation"
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              "titulo" => "Statistical analysis"
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          "titulo" => "Results"
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            0 => array:2 [
              "identificador" => "sec0045"
              "titulo" => "Decoupling map reconstruction in LGG and BIL"
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            1 => array:2 [
              "identificador" => "sec0050"
              "titulo" => "T&#47;N ratios in LGG and BIL"
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              "identificador" => "sec0055"
              "titulo" => "Decoupling score in LGGs and BILs"
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          "titulo" => "Discussion"
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          "titulo" => "Acknowledgements"
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    "fechaRecibido" => "2019-04-18"
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            0 => "One-Day protocol"
            1 => "<span class="elsevierStyleSup">13</span>N-ammonia"
            2 => "<span class="elsevierStyleSup">18</span>F-FDG"
            3 => "Voxel-Wise analysis"
            4 => "Low-Grade gliomas"
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            0 => "protocolo de un d&#237;a"
            1 => "13N-amonio"
            2 => "18F-FDG"
            3 => "an&#225;lisis de voxel"
            4 => "gliomas de bajo grado"
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    "resumen" => array:2 [
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0011">Purpose</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Accurate identification of low-grade gliomas &#40;LGGs&#59; World Health Organization grades I and II&#41; and their differentiation from brain inflammation lesions &#40;BILs&#41; remains difficult&#59; however&#44; it is essential for treatment&#46; This study assessed whether a one-day protocol for voxel-wise <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia PET&#47;CT with uptake decoupling analysis could differentiate LGGs from BILs&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">Twenty-eight patients with LGGs and 16 patients with BILs underwent <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia PET&#47;CT on the same day before any type of therapy&#46; The decoupling score and tumor-to-normal tissue &#40;T&#47;N&#41; ratio of <span class="elsevierStyleSup">18</span>F-FDG and <span class="elsevierStyleSup">13</span>N-ammonia were calculated at each location&#46; Student&#8217;s t-test was used to compare values&#44; and ROC curve analysis was used to establish a cut-off value for the T&#47;N ratio and decoupling score&#46; Area under the curve &#40;AUC&#41; was calculated to evaluate differential efficacy&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Significant differences were observed in <span class="elsevierStyleSup">13</span>N-ammonia T&#47;N ratio &#40;p&#8239;&#61;&#8239;0&#46;018&#41; and decoupling score &#40;p&#8239;&#61;&#8239;0&#46;003&#41; between LGGs and BILs&#59; however&#44; the <span class="elsevierStyleSup">18</span>F-FDG T&#47;N ratio did not show any differences &#40;p&#8239;&#61;&#8239;0&#46;413&#41;&#46; Optimal cut-off values for <span class="elsevierStyleSup">18</span>F-FDG T&#47;N ratio&#44; <span class="elsevierStyleSup">13</span>N-ammonia T&#47;N ratio&#44; and decoupling score were 0&#46;73&#44; 0&#46;97&#44; and 2&#46;31&#44; respectively&#44; with corresponding AUCs of 0&#46;48&#44; 0&#46;68&#44; and 0&#46;77&#46; The respective sensitivity&#44; specificity&#44; and accuracy parameters using these cut-off values were 53&#46;6&#37;&#44; 62&#46;5&#37;&#44; and 56&#46;8&#37;&#44; respectively&#44; for <span class="elsevierStyleSup">18</span>F-FDG&#59; 50&#46;0&#37;&#44; 75&#46;0&#37;&#44; and 59&#46;1&#37;&#44; respectively&#44; for <span class="elsevierStyleSup">13</span>N-ammonia&#59; and 60&#46;7&#37;&#44; 93&#46;8&#37;&#44; and 72&#46;7&#37;&#44; respectively&#44; for decoupling score&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleSup">18</span>F-FDG&#47;<span class="elsevierStyleSup">13</span>N-ammonia uptake decoupling score can be used to discriminate between LGGs and BILs&#46; Use of a decoupling map of these two tracers can improve visual analysis and diagnostic accuracy&#46;</p></span>"
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      "es" => array:3 [
        "titulo" => "Resumen"
        "resumen" => "<span id="abst0006" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0012">Prop&#243;sito</span><p id="spar0031" class="elsevierStyleSimplePara elsevierViewall">La identificaci&#243;n precisa de los gliomas de bajo grado &#40;LGGs&#59; grados I y II de la Organizaci&#243;n Mundial de la Salud&#41; y su diferenciaci&#243;n de las lesiones por inflamaci&#243;n cerebral &#40;BILs&#41; sigue siendo dif&#237;cil&#59; sin embargo&#44; es esencial para el tratamiento&#46; Este estudio evalu&#243; si un protocolo de un d&#237;a para la TEP&#47;TC con amon&#237;aco 18F-FDG y 13Namon&#237;aco con an&#225;lisis de desacoplamiento de la captaci&#243;n podr&#237;a diferenciar los LGG de los BIL&#46;</p></span> <span id="abst0013" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0016">Materiales y m&#233;todos</span><p id="spar0036" class="elsevierStyleSimplePara elsevierViewall">Veintiocho pacientes con GLG y 16 pacientes con BIL se sometieron a TEP&#47;TC con 18F-FDG y 13N-amon&#237;aco el mismo d&#237;a antes de cualquier tipo de terapia&#46; La puntuaci&#243;n de desacoplamiento y la relaci&#243;n tumor&#47;tejido normal &#40;T&#47;N&#41; de 18F-FDG y 13N-amon&#237;aco se calcularon en cada localizaci&#243;n&#46; Se utiliz&#243; la prueba t de Student para comparar valores&#44; y el an&#225;lisis de la curva ROC para establecer un valor de corte para la relaci&#243;n T&#47;N y la puntuaci&#243;n de desacoplamiento&#46; Se calcul&#243; la CUA para evaluar la eficacia diferencial&#46;</p></span> <span id="abst0014" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0017">Resultados</span><p id="spar0038" class="elsevierStyleSimplePara elsevierViewall">Se observaron diferencias significativas en la relaci&#243;n T&#47;N de 13N-amon&#237;aco &#40;p&#61;0&#44;018&#41; y en la puntuaci&#243;n de desacoplamiento &#40;p&#61;0&#44;003&#41; entre los LGG y los BIL&#59; sin embargo&#44; la relaci&#243;n T&#47;N de 18F-FDG no mostr&#243; ninguna diferencia &#40;p&#61;0&#44;413&#41;&#46; Los valores de corte &#243;ptimos para la relaci&#243;n T&#47;N de 18F-FDG&#44; la relaci&#243;n T&#47;N de 13N-amon&#237;aco y la puntuaci&#243;n de desacoplamiento fueron 0&#44;73&#44; 0&#44;97 y 2&#44;31&#44; respectivamente&#44; con AUC correspondientes de 0&#44;48&#44; 0&#44;68 y 0&#44;77&#46; Los respectivos par&#225;metros de sensibilidad&#44; especificidad y precisi&#243;n que utilizan estos valores de corte fueron 53&#44;6&#37;&#44; 62&#44;5&#37; y 56&#44;8&#37;&#44; respectivamente&#44; para 18F-FDG&#59; 50&#44;0&#37;&#44; 75&#44;0&#37; y 59&#44;1&#37;&#44; respectivamente&#44; para la amon&#237;aco 13N&#59; y 60&#44;7&#37;&#44; 93&#44;8&#37; y 72&#44;7&#37;&#44; respectivamente&#44; para la puntuaci&#243;n de desacoplamiento&#46;</p></span> <span id="abst0018" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0021">Conclusiones</span><p id="spar0041" class="elsevierStyleSimplePara elsevierViewall">La puntuaci&#243;n de desacoplamiento de la captaci&#243;n de amon&#237;aco 18FFDG&#47; 13N se puede utilizar para discriminar entre LGG y BIL&#46; El uso de un mapa de desacoplamiento de estos dos trazadores puede mejorar el an&#225;lisis visual y la precisi&#243;n del diagn&#243;stico&#46;</p></span>"
        "secciones" => array:4 [
          0 => array:2 [
            "identificador" => "abst0006"
            "titulo" => "Prop&#243;sito"
          ]
          1 => array:2 [
            "identificador" => "abst0013"
            "titulo" => "Materiales y m&#233;todos"
          ]
          2 => array:2 [
            "identificador" => "abst0014"
            "titulo" => "Resultados"
          ]
          3 => array:2 [
            "identificador" => "abst0018"
            "titulo" => "Conclusiones"
          ]
        ]
      ]
    ]
    "NotaPie" => array:2 [
      0 => array:2 [
        "etiqueta" => "&#9734;"
        "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as&#58; Yi C&#44; Quirce R&#44; Yu D&#44; Shi X&#44; Luo G&#44; Zhang B&#44; Lu Y&#44; Zeng R&#44; He Q&#44; Zhang X&#46; Protocolo de un d&#237;a para la TEP&#47;TC con amon&#237;aco 18F-FDG y 13N con puntuaci&#243;n de desacoplamiento de la captaci&#243;n para diferenciar el glioma de bajo grado no tratado de la inflamaci&#243;n&#46; Rev Esp Med Nucl Imagen Mol&#46; 2020&#59;39&#58;68&#8211;74&#46;</p>"
      ]
      1 => array:3 [
        "etiqueta" => "1"
        "nota" => "<p class="elsevierStyleNotepara" id="npar9005">Chang Yi and Donglan Yu contributed equally to this work&#46;</p>"
        "identificador" => "fn0005"
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    ]
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        "etiqueta" => "Fig&#46; 1"
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        "figura" => array:1 [
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          "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Patient examples&#58; region of interest &#40;ROI&#41; near the midline of the brain shows the lesion&#44; ROI in the cerebral cortex shows normal tissue&#46; a&#46; A 30-year-old woman with grade II astrocytoma in the thalamus&#46; <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG tumor-to-normal tissue &#40;T&#47;N&#41; ratio map shows decreased uptake of <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG in the lesion&#44; while <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia T&#47;N ratio map shows increased uptake of <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia in the same lesion&#46; Decoupling score map shows high decoupling scores in this lesion&#46; Decoupling scores in each voxel were calculated using the expected linear regression line of <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia within normal brain&#46; b&#46; A 45-year-old woman with grade II oligodendrogliomas in the right frontal lobe next to the longitudinal fissure&#46; Decreased uptake of both <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia was observed for this lesion in T&#47;N ratio maps&#44; which were not helpful for the diagnosis of the lesions&#46; The decoupling score map showed high decoupling scores in the lesion&#46;</p>"
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        "etiqueta" => "Fig&#46; 2"
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          "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Representative case of a 54-year-old man with a brain inflammation lesion&#46; a&#46; The region of interest shows the lesion in computed tomography images&#46; b and c&#46; Markedly increased uptake of <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG &#40;b&#41; and decreased uptake of <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia &#40;c&#41; were present in tumor-to-normal tissue &#40;T&#47;N&#41; ratio maps&#46; d&#46; Correlation was determined between <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia uptake within normal brain&#46; e&#46; The lesion in the decoupling map appears lower than surrounding normal brain tissue&#46;</p>"
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        "etiqueta" => "Fig&#46; 3"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "figura" => array:1 [
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          "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">Receiver operating characteristic analysis for detecting lesions with <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG tumor-to-normal tissue &#40;T&#47;N&#41; ratio&#44; <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia T&#47;N ratio&#44; and decoupling score&#46; The decoupling score showed the best performance&#44; with a cutoff value of 2&#46;31 &#40;area under the curve&#44; AUC&#58; 0&#46;77&#41;&#44; whereas the cutoff values for T&#47;N ratio of <a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a>F-FDG and <a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a>N-ammonia uptake were 0&#46;73 &#40;AUC&#58; 0&#46;48&#41; and 0&#46;97 &#40;AUC&#58; 0&#46;68&#41;&#44; respectively&#46;</p>"
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                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Diagnosis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#46; of patients&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Age &#40;Years&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#46; of Sex &#40;M&#47;F&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">No&#46; of diagnoses&#40;histologic&#47;follow-up&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">44&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">40&#46;11&#8239;&#177;&#8239;15&#46;86&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">23&#47;21&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">34&#47;10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Inflammation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">46&#46;38&#8239;&#177;&#8239;16&#46;49&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&#47;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#47;10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Encephalitis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">38&#46;00&#8239;&#177;&#8239;13&#46;74&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#47;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8722;&#47;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brain abscess&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&#46;67&#8239;&#177;&#8239;12&#46;34&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#47;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Demyelination&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">41&#46;25&#8239;&#177;&#8239;13&#46;44&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#47;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#47;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Fungal infection&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">72&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#47;-&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">LGGs&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">28&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">36&#46;53&#8239;&#177;&#8239;14&#46;59&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">15&#47;13&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">28&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Grade I&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">20&#46;00&#8239;&#177;&#8239;3&#46;16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#47;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Grade II&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">24&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">39&#46;30&#8239;&#177;&#8239;13&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#47;12&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">24&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Astrocytoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">39&#46;30&#8239;&#177;&#8239;15&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11&#47;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">19&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Oligodendrogliomas&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">37&#46;50&#8239;&#177;&#8239;9&#46;68&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#47;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Oligoastrocytomas&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">46&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">-&#47;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#47;&#8722;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab2248631.png"
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
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        ]
      ]
      4 => array:8 [
        "identificador" => "tbl0010"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at0025"
            "detalle" => "Table "
            "rol" => "short"
          ]
        ]
        "tabla" => array:1 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Diagnosis</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">FDG T&#47;N ratio &#40;average&#41;</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NH3 T&#47;N ratio &#40;average&#41;</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Decoupling score &#40;average&#41;</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mean&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Range&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;80&#8239;&#177;&#8239;0&#46;36&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;02&#732;3&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;94&#8239;&#177;&#8239;0&#46;20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;07&#732;3&#46;20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;20&#8239;&#177;&#8239;0&#46;71&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8722;8&#46;82&#732;9&#46;38&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Inflammation&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;88&#8239;&#177;&#8239;0&#46;52&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;02&#732;3&#46;94&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;84&#8239;&#177;&#8239;0&#46;22&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;07&#732;3&#46;20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;72&#8239;&#177;&#8239;0&#46;61&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8722;8&#46;82&#732;5&#46;44&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Encephalitis&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;64&#8239;&#177;&#8239;0&#46;09&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;24&#732;1&#46;10&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;75&#8239;&#177;&#8239;0&#46;23&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;20&#732;1&#46;38&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;58&#8239;&#177;&#8239;0&#46;76&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8722;4&#46;51&#732;4&#46;25&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Brain abscess&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;95&#8239;&#177;&#8239;0&#46;32&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;02&#732;2&#46;16&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;83&#8239;&#177;&#8239;0&#46;26&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;07&#732;1&#46;50&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">1&#46;37&#8239;&#177;&#8239;0&#46;76&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#8722;1&#46;39&#732;4&#46;05&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Demyelination&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">1&#46;05&#8239;&#177;&#8239;0&#46;75&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#46;04&#732;3&#46;94&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#8722;8&#46;82&#732;5&#46;44&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Fungal infection&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">0&#46;73&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">LGGs&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Astrocytoma&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Oligodendrogliomas&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">Oligoastrocytomas&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">0&#46;72&#732;5&#46;17&nbsp;\t\t\t\t\t\t\n
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                            0 => "D&#46;A&#46; Forst"
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                        "fecha" => "2014"
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