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Review
Whole body FDG-PET/CT for the assessment of bone marrow infiltration in patients with newly diagnosed lymphoma
FDG-PET/TC de cuerpo entero para evaluar la infiltración de la médula ósea en pacientes con linfoma de nuevo diagnóstico
Wang Xiao-Xue1, Huang Xinyue1, Zhang Lijun
Corresponding author
lzhang202003@163.com

Corresponding author.
Department of Hematology, the First Hospital, China Medical University, Shenyang 110001, China
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Lymphoma is a common malignant tumor origin from the lymphatic hematopoietic system&#46; It is usually accompanied by bone marrow infiltration thus affecting the Ann Arbor staging&#46; Therefore&#44; the evaluation of lymphoma bone marrow infiltration is particularly important&#46; Bone marrow biopsy is the most direct method of detecting lymphoma infiltration&#44; but it is an invasive procedure which is accompanied by several complications such as pain and hemorrhage&#46;<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">1</span></a> On the other hand&#44; PET&#8211;CT is a non-invasive examination that can comprehensively evaluate the state of bone marrow with extremely high sensitivity in detecting bone marrow infiltration of lymphoma&#46;<a class="elsevierStyleCrossRefs" href="#bib0230"><span class="elsevierStyleSup">2&#8211;4</span></a> Therefore&#44; many clinical institutions put forward the idea of replacing bone marrow biopsy with PET&#8211;CT as the first choice in the diagnosing of lymphoma bone marrow infiltration&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">Meanwhile&#44; many other researchers share different opinions&#46; Relevant research indicates that PET&#8211;CT cannot replace bone biopsy in the diagnosing of bone marrow infiltration in DLBCL and FL&#44;<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">5</span></a> and the accuracy of PET&#8211;CT in detecting bone marrow infiltration is dissatisfactory&#46;<a class="elsevierStyleCrossRefs" href="#bib0250"><span class="elsevierStyleSup">6&#44;7</span></a> Some researchers came to the conclusion that the clinical significance of diffuse infiltration of bone marrow in PET&#8211;CT remains uncertain because the high uptake focus of FDG in PET&#8211;CT cannot represent the bone marrow infiltration very well&#46;<a class="elsevierStyleCrossRefs" href="#bib0260"><span class="elsevierStyleSup">8&#44;9</span></a> It is not objective to do a comparison between whole body PET&#8211;CT and one sample point bone marrow biopsy&#46;<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">10</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">At this moment&#44; there is no clear international guideline between the indications of PET&#8211;CT and bone marrow biopsy&#46; The aim of this research is to discuss the significance of PET&#8211;CT in detecting lymphoma bone marrow infiltration and clinical staging&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Data and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Inclusion criteria and exclusion criteria of patients</span><p id="par0020" class="elsevierStylePara elsevierViewall">Inclusion criteria includes&#58; specific histological type&#59; accepted PET&#8211;CT and bone marrow biopsy before treatment&#59; the interval between PET&#8211;CT and bone marrow biopsy is less than 2 weeks&#59; detailed and believable clinical information&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">Exclusion criteria includes&#58; undefined histological type&#59; accepted PET&#8211;CT and bone marrow biopsy after treatment&#59; the interval between PET&#8211;CT and bone marrow biopsy is more than 2 weeks&#59; missing or suspicious clinical information&#46;</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Data collection</span><p id="par0030" class="elsevierStylePara elsevierViewall">Collected clinical information includes name&#44; age&#44; sex&#44; pathological type&#44; specific PET&#8211;CT description&#44; bone marrow biopsy report&#44; serum LDH level&#44; etc&#46; Patients were categorized based on the Ann Arbor Staging Criteria&#46; Patients are then scored based on the IPI index&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Methods</span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">PET&#8211;CT image collection and analysis</span><p id="par0035" class="elsevierStylePara elsevierViewall">Patients were imaged with equipment MCT31067&#46; After a 4-h fasting period&#44; patients were intravenous injected with imaging agent and rested for 1<span class="elsevierStyleHsp" style=""></span>h before CT was performed&#46; After attenuation correction and iterative reconstruction&#44; multifaceted and multi-piece PET imaging was performed and fused with CT images&#46; Grayscale was used to compare the imaging agent uptake level of liver and bone marrow&#46; If a high-uptake focus in bone marrow was observed and the uptake level of the focus was higher than liver &#40;or the mean SUV of bone marrow was higher than 2&#46;7&#41;&#44; the patient was defined abnormal bone marrow glucose metabolism&#46; If no high-uptake focus in bone marrow was observed and the mean uptake level of bone marrow was lower than liver &#40;or lower than 1&#46;7&#41;&#44; the patient was defined normal bone marrow glucose metabolism&#46; We acquired the SUVmax of the bone marrow focuses in patients with abnormal bone glucose metabolism&#46;</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Bone marrow biopsy and pathological analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">Unilateral iliac crest biopsies were performed before treatment&#46; BMB specimens were evaluated morphologically by hematopathologists&#46; Immunohistochemistry of the bone marrow were carried out to determine the immunophenotype of the lymphoma and to quantify marrow involvement&#46;</p></span></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Statistical analysis</span><p id="par0045" class="elsevierStylePara elsevierViewall">We used SPSS 19&#46;0 to analyze continuous variables with non-parametric tests and grouping variables with Chi-square test or Fisher&#39;s exact test&#46;</p></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Results</span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">General data</span><p id="par0050" class="elsevierStylePara elsevierViewall">Our research included 153 patients who were diagnosed with lymphoma in the First Affiliated Hospital of China Medical University between September 2016 and October 2017&#46; The basic information of the patients can be found in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Consistency analysis of bone marrow biopsy and PET&#8211;CT</span><p id="par0055" class="elsevierStylePara elsevierViewall">Among the 153 patients&#44; 42 patients were reported bone marrow infiltration by PET&#8211;CT &#40;27&#46;5&#37;&#41;&#44; 35 patients were reported bone marrow infiltration by bone marrow biopsy &#40;22&#46;9&#37;&#41;&#46; Setting bone marrow biopsy as golden standard&#44; the sensitivity&#44; specificity and accuracy of PET&#8211;CT in detecting bone marrow infiltration are 54&#46;3&#37;&#44; 80&#46;5&#37; and 74&#46;5&#37; respectively &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Correlation analysis of bone marrow biopsy and PET&#8211;CT in various pathological types of lymphoma</span><p id="par0060" class="elsevierStylePara elsevierViewall">Setting bone marrow biopsy as golden standard&#44; we analyzed the sensitivity&#44; specificity and accuracy of PET&#8211;CT in detecting bone marrow infiltration of different pathological types of lymphoma&#46; The sensitivity of PET&#8211;CT is 0&#37;&#44; specificity and accuracy are both 46&#46;7&#37; in HL patients due to no bone marrow infiltration detection by bone marrow biopsy&#46; In aggressive B-cell lymphoma &#40;DLBCL&#44; HG-BL&#41; and MZL&#44; PET&#8211;CT results of bone marrow infiltration showed high accuracy of 88&#46;1&#37; and 83&#46;3&#37; respectively&#46; In other pathological types&#44; PET&#8211;CT showed lower consistency with bone marrow biopsy&#46; The median value of SUVmax in the patients detected bone marrow infiltration by BMB was significant higher than patients with BMB negative results among subgroups of aggressive B-cell lymphoma&#44; MZL and T-NHL &#40;<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>&#41;&#46; Detailed information for each histological subgroups can be found in supplementary Table 1&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Discussion</span><p id="par0065" class="elsevierStylePara elsevierViewall">Bone marrow biopsy and PET&#8211;CT are two kinds of common examinations in detecting bone marrow infiltration of lymphoma&#46; The former is an invasive examination which has high true positive rate &#40;sensitivity&#41; and false negative rate &#40;rate of missed diagnosis&#41;&#46; The latter is a noninvasive examination which has high true negative rate &#40;specificity&#41; and false positive rate &#40;misdiagnosis rate&#41;&#46; Consequently&#44; the clinical value of bone marrow biopsy and PET&#8211;CT needed to be reevaluated&#46;</p><p id="par0070" class="elsevierStylePara elsevierViewall">Lymphoma is a common malignant proliferative disease in which bone marrow infiltration may alters Ann Arbor staging of patients&#44; and thus affects the prognosis of the disease&#46; Therefore&#44; the evaluation of lymphoma bone marrow infiltration is particularly important&#46;<a class="elsevierStyleCrossRefs" href="#bib0235"><span class="elsevierStyleSup">3&#44;4&#44;11</span></a> In our research&#44; twenty patients from the Ann Arbor stage directed by PET&#8211;CT differ from the Ann Arbor stage directed by bone marrow biopsy&#46; Among them&#44; 13 patients were upgraded by PET&#8211;CT and 7 patients were downgraded&#46; Except for the 8 patients with HL&#44; the change of stage did not affect the clinical treatment of other types of lymphoma which is similar to related literature reports&#46; Also&#44; as expected&#44; The SUVmax value of bone marrow in PET&#8211;CT showed significant correlation with bone marrow infiltration among patients with aggressive B-cell lymphoma and T-NHL &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#46;05&#41;&#44; which may be associated with a highly aggressive nature of the disease&#46;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">12&#44;13</span></a></p><p id="par0075" class="elsevierStylePara elsevierViewall">There are several recent research that have discussed the clinical status of PET&#8211;CT in detecting bone marrow infiltration of lymphoma with different pathological types&#44; however&#44; no unified conclusion has been drawn to guide the clinic so far&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">For patients with HL&#44; most investigators put forward that PET&#8211;CT is very precise in detecting bone marrow infiltration thus may replace bone marrow biopsy as the preferred examination&#46;<a class="elsevierStyleCrossRefs" href="#bib0290"><span class="elsevierStyleSup">14&#44;15</span></a> As for HL&#44; Ujjani et al&#46; reported that PET&#8211;CT detected over 90&#37; bone marrow infiltration including the ones escaped from bone marrow biopsy&#46;<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16&#8211;18</span></a> Subocz et al&#46; believed that PET&#8211;CT is the most valuable imagological examination in lymphoma&#44; and may even replace bone marrow biopsy now and then&#46;<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">19</span></a> Chen-Liang et al&#46; recommended PET&#8211;CT as the first choice examination in detecting bone marrow infiltration of HL as well&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">11</span></a> However&#44; our research does not include HL which has positive bone marrow biopsy result due to rare bone marrow infiltration in early HL&#46; Among all the 15 patients with HL&#44; 8 had positive PET&#8211;CT results about bone marrow infiltration&#44; thus the sensitivity of PET&#8211;CT bone marrow infiltration detection of HL is 0&#37; and the specificity and accuracy are both 46&#46;7&#37;&#46; Based on our data&#44; it is not appropriate to take PET positivity as an unequivocal sign of BM involvement in HL&#44; since treatment options may be changed in some of the patients in this event&#46; Sometimes&#44; PET&#8211;CT may be too sensitive and detect small degrees of BMI that are clinically irrelevant&#46; It is questionable to pursue high sensitivity blindly&#46;</p><p id="par0085" class="elsevierStylePara elsevierViewall">Some guidelines indicated that PET&#8211;CT is now recommended as the gold standard for staging DLBCL patients&#46; Thus&#44; biopsy is no longer required when a PET&#47;CT scan demonstrates bone or marrow involvement indicating advanced-stage disease but is appropriate in case of negative PET&#8211;CT results&#46;<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">20</span></a> Teagle and El Karak et al&#46; revealed that as for DLBCL&#44; the sensitivity and specificity of PET&#8211;CT are higher than bone marrow biopsy&#46;<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16&#44;21&#44;22</span></a> However&#44; low-volume involvement &#40;&#60;10&#8211;20&#37;&#41; and discordant lymphoma may be missed by PET&#47;CT imaging&#46;<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">23</span></a> Our study showed that the sensitivity&#44; specificity and accuracy of PET&#8211;CT in detecting bone marrow infiltration of DLBCL were 80&#37;&#44; 90&#46;0&#37; and 88&#46;1&#37; respectively&#46; As for HG-BL&#44; Chen-Liang et al&#46; recommended to check PET&#8211;CT first&#46; Bone marrow biopsy is necessary only in cases where PET&#8211;CT showed no bone marrow infiltration&#46;<a class="elsevierStyleCrossRef" href="#bib0275"><span class="elsevierStyleSup">11</span></a> The consistency of bone marrow biopsy and PET&#8211;CT is relatively convincing thus it was concluded that PET&#8211;CT can be used as a first line examination in detecting bone marrow infiltration of DLBCL and HG-BL&#46;</p><p id="par0090" class="elsevierStylePara elsevierViewall">As for FL&#44; PET&#8211;CT seems to be less precise in detecting bone marrow infiltration thus cannot replace bone marrow biopsy as the golden standard in clinic&#46; According to study conducted by Gallamini et al&#46;&#44; PET&#8211;CT can stage and evaluate the prognosis of FL precisely&#46;<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">24</span></a> However&#44; Ujjani and Teagle reported that the sensitivity and specificity of PET&#8211;CT in detecting bone marrow infiltration of FL are unsatisfactory&#46;<a class="elsevierStyleCrossRefs" href="#bib0300"><span class="elsevierStyleSup">16&#44;21</span></a> The sensitivity&#44; specificity and accuracy of PET&#8211;CT in detecting bone marrow infiltration of FL in our research were 37&#46;5&#37;&#44; 87&#46;5&#37; and 70&#46;8&#37;&#46; The consistency of bone marrow biopsy and PET&#8211;CT is not ideal&#44; so we believe PET&#8211;CT have less value in detecting bone marrow infiltration of FL&#46;</p><p id="par0095" class="elsevierStylePara elsevierViewall">A recent study conducted by Koh et al&#46;<a class="elsevierStyleCrossRef" href="#bib0345"><span class="elsevierStyleSup">25</span></a> analyzed 109 &#40;63 PTCL and 46 NKTCL&#41; patients&#46; Biopsy revealed BM involvement in 35&#46;8&#37; of cases&#46; Sensitivity and specificity of PET for diagnosing positive BM biopsy were 61&#46;5&#37; and 75&#46;7&#37; respectively&#46; Despite fair correlation with BM biopsy result&#44; PET may not replace BM biopsy in PTCL and NKTCL&#46; However&#44; the BM finding on PET is an independent prognostic factor&#44; suggesting additional biological implication of PET findings&#46; Abe et al&#46;<a class="elsevierStyleCrossRef" href="#bib0350"><span class="elsevierStyleSup">26</span></a> revealed that PET&#47;CT exhibited a higher sensitivity for BM involvement than BMB&#46; Furthermore&#44; BM assessment using PET&#47;CT identified patients at high risk of disease progression and mortality&#46; Shao puts forward that PET&#8211;CT is of vital importance in AITL&#46;<a class="elsevierStyleCrossRef" href="#bib0355"><span class="elsevierStyleSup">27</span></a> The sensitivity&#44; specificity and accuracy of PET&#8211;CT in detecting bone marrow infiltration of AITL and ALCL in our research were relatively high&#46; Due to the fact that there was only 1 patient with bone marrow infiltration for each pathological type&#44; we cannot draw any convincing conclusion for ALCL and AITL from our research&#46;</p><p id="par0100" class="elsevierStylePara elsevierViewall">There is no report discussing the correlation between bone marrow biopsy and PET&#8211;CT in MCL&#44; MALT&#44; and MZL for the time being&#46;</p><p id="par0105" class="elsevierStylePara elsevierViewall">Still&#44; our research had certain limitations&#46; First of all&#44; our sample was not large enough so that our conclusion may not represent the total population&#46; Secondly&#44; the pathological types included in our research were not comprehensive enough&#59; the distribution among each type was not well-proportioned&#46; As a consequence&#44; we cannot draw conclusions for each type of lymphoma&#46; Thirdly&#44; our sample was collected only from our own hospital&#44; thus our conclusion has regional limitation&#46; Lastly&#44; this retrospective study omitted the blind method in clinical information such as PET&#8211;CT and B symptom&#46; As a result&#44; the information bias may affect the results of our research&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">PET&#8211;CT has many other functions besides diagnosing and staging of lymphoma&#46; PET&#8211;CT can distinguish invasive lymphoma from noninvasive lymphoma&#46;<a class="elsevierStyleCrossRefs" href="#bib0280"><span class="elsevierStyleSup">12&#44;13&#44;28</span></a> PET&#8211;CT is also an important evidence for differential diagnosis in many diseases&#46;<a class="elsevierStyleCrossRefs" href="#bib0365"><span class="elsevierStyleSup">29&#8211;33</span></a> Furthermore&#44; PET&#8211;CT can detect lymphoma infiltration in different locations&#46;<a class="elsevierStyleCrossRefs" href="#bib0390"><span class="elsevierStyleSup">34&#8211;41</span></a></p><p id="par0115" class="elsevierStylePara elsevierViewall">In addition&#44; a delayed PET&#8211;CT may have high clinical value&#46;<a class="elsevierStyleCrossRefs" href="#bib0430"><span class="elsevierStyleSup">42&#44;43</span></a> Recent studies on PET-MRI stated that the combination of PET&#8211;CT with MRI resulted in a reduction of radiation from CT&#44; thus giving it a promising future development&#46;<a class="elsevierStyleCrossRef" href="#bib0440"><span class="elsevierStyleSup">44</span></a> More future researches with larger sample size are needed to determine if delayed PET&#8211;CT is better than the standard PET&#8211;CT and whether PET-MRI can replace PET&#8211;CT in the evaluation of bone marrow condition without radiation&#46;</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Conclusion</span><p id="par0120" class="elsevierStylePara elsevierViewall">PET&#8211;CT may be sometime useful in the diagnosis of bone marrow infiltration in lymphoma&#46; At some point it may show influence on Ann Arbor staging of lymphoma even lead to changes of clinical treatment&#46; However&#44; the clinical significance of PET in the diagnosis of bone marrow infiltration remains uncertain in certain pathological types&#46; So&#44; PET&#8211;CT cannot replace bone marrow biopsy completely&#46;</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflict of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors declare no conflicts of interest&#46;</p></span></span>"
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                  "titulo" => "PET&#8211;CT image collection and analysis"
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              "titulo" => "General data"
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            1 => array:2 [
              "identificador" => "sec0055"
              "titulo" => "Consistency analysis of bone marrow biopsy and PET&#8211;CT"
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              "titulo" => "Correlation analysis of bone marrow biopsy and PET&#8211;CT in various pathological types of lymphoma"
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    "fechaRecibido" => "2018-12-16"
    "fechaAceptado" => "2019-07-18"
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          "clase" => "keyword"
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          "palabras" => array:5 [
            0 => "Lymphoma"
            1 => "PET&#8211;CT"
            2 => "SUVmax"
            3 => "Bone marrow infiltration"
            4 => "Ann Arbor stage"
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          "palabras" => array:5 [
            0 => "Linfoma"
            1 => "PET&#47;TC"
            2 => "SUVm&#225;x"
            3 => "Infiltraci&#243;n de la m&#233;dula &#243;sea"
            4 => "Estadificaci&#243;n de Ann Arbor"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Background</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Positron emission tomography&#8211;computed tomography &#40;PET&#8211;CT&#41; and bone marrow biopsy are currently the common clinical examination of lymphoma infiltration&#46; The aim of this research is to evaluate the value of PET&#8211;CT in diagnosis of bone marrow infiltration&#44; clinical staging and pathological typing of lymphoma&#46;</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">153 cases were analyzed retrospectively to compare the consistency of PET&#8211;CT and bone marrow biopsy&#46; We analyzed the sensitivity&#44; accuracy and specificity of PET&#8211;CT in different clinical pathology of lymphoma&#46;</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The PET&#8211;CT sensitivity in detecting bone marrow infiltration is 54&#46;3&#37; with a specificity of 80&#46;5&#37; and accuracy of 74&#46;5&#37;&#46; In aggressive B-cell lymphoma &#40;DLBCL&#44; HG-BL&#41; and MZL&#44; PET&#8211;CT results of bone marrow infiltration showed high accuracy of 88&#46;1&#37; and 83&#46;3&#37; respectively&#46; The median value of SUVmax in the patients detected to have bone marrow infiltration by BMB was significantly higher than patients with BMB negative results among subgroups of aggressive B-cell lymphoma&#44; MZL and T-NHL &#40;<span class="elsevierStyleItalic">p</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;05&#41;&#46;</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusion</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">PET&#8211;CT is significant in detecting bone marrow infiltration in certain pathological types of lymphoma&#46; However pathological inconsistencies still exist between bone marrow biopsy and PET&#8211;CT&#44; thus PET&#8211;CT cannot completely replace biopsy&#46;</p></span>"
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            "titulo" => "Background"
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            "titulo" => "Methods"
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        "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Antecedentes</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">La tomograf&#237;a computarizada por emisi&#243;n de positrones &#40;PET&#47;TC&#41; y la biopsia de m&#233;dula &#243;sea &#40;BMB&#41; son actualmente los ex&#225;menes cl&#237;nicos comunes para valorar la infiltraci&#243;n linfomatosa&#46; El objetivo de este estudio es evaluar el valor de la PET&#47;TC en el diagn&#243;stico de la infiltraci&#243;n de la m&#233;dula &#243;sea&#44; la estadificaci&#243;n cl&#237;nica y la tipificaci&#243;n patol&#243;gica del linfoma&#46;</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">M&#233;todos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Se analizaron retrospectivamente 153 casos para comparar la consistencia de la PET&#47;TC y la BMB&#46; Analizamos la sensibilidad&#44; la fiabilidad y la especificidad de la PET&#47;TC en las diferentes enfermedades cl&#237;nicas del linfoma&#46;</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">La sensibilidad de la PET&#47;TC para detectar infiltraci&#243;n de la m&#233;dula &#243;sea es del 54&#44;3&#37;&#44; con una especificidad del 80&#44;5&#37; y una precisi&#243;n del 74&#44;5&#37;&#46; En los casos de linfoma agresivo de c&#233;lulas B &#40;DLBCL&#44; HG-BL&#41; y MZL&#44; los resultados de la PET&#47;TC para la infiltraci&#243;n de la m&#233;dula &#243;sea reflejaron una alta precisi&#243;n del 88&#44;1 y 83&#44;3&#37;&#44; respectivamente&#46; El valor medio SUVm&#225;x en los pacientes en los que se detect&#243; infiltraci&#243;n de la m&#233;dula &#243;sea mediante BMB fue significativamente superior al de los pacientes con resultados negativos de BMB entre los subgrupos de linfoma agresivo de c&#233;lulas B&#44; MZL y T-NHL &#40;p<span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>0&#44;05&#41;&#46;</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusi&#243;n</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">La PET&#47;TC es significativa a la hora de detectar infiltraci&#243;n de la m&#233;dula &#243;sea en ciertos tipos patol&#243;gicos de linfoma&#46; Sin embargo&#44; siguen existiendo inconsistencias patol&#243;gicas entre la biopsia de m&#233;dula &#243;sea y la PET&#47;TC&#44; aunque esta t&#233;cnica no puede sustituir por completo a la biopsia&#46;</p></span>"
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            "titulo" => "Supplementary data"
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                  \t\t\t\t">73 &#40;47&#46;7&#37;&#41;&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
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Female&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">80 &#40;52&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Hodgkin&#39;s lymphoma&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">15 &#40;9&#46;8&#37;&#41;&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
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Diffuse large B cell lymphoma&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>High grade B-cell lymphoma&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">4 &#40;2&#46;6&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>Follicular lymphoma&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 &#40;15&#46;7&#37;&#41;&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>Mantle cell lymphoma&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">9 &#40;5&#46;9&#37;&#41;&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>Mucosa associated lymphoid tissue lymphoma&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">7 &#40;4&#46;6&#37;&#41;&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>Marginal zone lymphoma&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">5 &#40;3&#46;3&#37;&#41;&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>Peripheral T cell lymphoma&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 &#40;9&#46;8&#37;&#41;&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>NK&#47;T cell lymphoma&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 &#40;3&#46;9&#37;&#41;&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>Anaplastic large cell lymphoma&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">7 &#40;4&#46;6&#37;&#41;&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>Angioimmunoblastic T cell lymphoma&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 &#40;3&#46;9&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Performance score</span></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>0&#8211;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">102 &#40;66&#46;7&#37;&#41;&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>2&#8211;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">51 &#40;33&#46;3&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Ann Arbor staging</span></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>I&#8211;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">68 &#40;44&#46;4&#37;&#41;&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>III&#8211;IV&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">85 &#40;55&#46;6&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">International Prognostic Index</span></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>0&#8211;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">87 &#40;56&#46;9&#37;&#41;&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>3&#8211;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">66 &#40;43&#46;1&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab2209545.png"
              ]
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        ]
        "descripcion" => array:1 [
          "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Patient characteristics&#46;</p>"
        ]
      ]
      1 => array:8 [
        "identificador" => "tbl0010"
        "etiqueta" => "Table 2"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at2"
            "detalle" => "Table "
            "rol" => "short"
          ]
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">BMB<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>bone marrow biopsy&#44; PET&#8211;CT<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>positron emission tomography&#47;computed tomography&#46;</p>"
          "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-with-role" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col">PET&#8211;CT&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  " colspan="2" align="center" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">BMB</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">Total&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&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">Positive&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">Negative&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="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">&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">Positive&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">42&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">Negative&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">95&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">111&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></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">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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">35&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">118&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">153&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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          "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Consistency analysis of bone marrow biopsy and PET&#8211;CT&#46;</p>"
        ]
      ]
      2 => array:8 [
        "identificador" => "tbl0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "detalles" => array:1 [
          0 => array:3 [
            "identificador" => "at3"
            "detalle" => "Table "
            "rol" => "short"
          ]
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        "tabla" => array:2 [
          "leyenda" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">BMB<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>bone marrow biopsy&#44; HL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>Hodgkin&#39;s lymphoma&#44; FL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>follicular lymphoma&#44; MCL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>mantle cell lymphoma&#44; MZL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>marginal zone lymphoma&#44; T-NHL<span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>T cell non-Hodgkin&#39;s lymphoma&#46;</p>"
          "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">Pathological subtype&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">PET&#8211;CT positive&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">PET&#8211;CT negative&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">Sensitivity&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">Specificity&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">Accuracy&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">Median and range of SUVmax&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"><span class="elsevierStyleItalic">p</span>&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" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">HL &#40;N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">&#61;</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">15&#41;</span></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>BMB positive&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">46&#46;7&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">46&#46;7&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8211;</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>BMB negative&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;9 &#40;0&#8211;4&#46;7&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Aggressive B-cell lymphoma &#40;N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">&#61;</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">59&#41;</span></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>BMB positive&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">80&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">90&#46;0&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">88&#46;1&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10&#46;4 &#40;1&#46;2&#8211;18&#46;9&#41;&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;05</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>BMB negative&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;9 &#40;0&#8211;5&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">FL &#40;N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">&#61;</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">24&#41;</span></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>BMB positive&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">37&#46;5&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">87&#46;5&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">70&#46;8&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;52 &#40;0&#8211;3&#46;7&#41;&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;62</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>BMB negative&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;44 &#40;0&#8211;2&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">MCL &#40;N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">&#61;</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">9&#41;</span></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>BMB positive&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" 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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">40&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">50&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">44&#46;4&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;49 &#40;0&#8211;9&#46;3&#41;&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;47</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>BMB negative&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;98 &#40;0&#8211;5&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleVsp" style="height:0.5px"></span></td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="8" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">MZL &#40;N</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">&#61;</span><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleItalic">12&#41;</span></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>BMB positive&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="char" 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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">60&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">100&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">83&#46;3&#37;</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;5 &#40;0&#8211;7&#46;4&#41;&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  " rowspan="2" align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;0&#46;05</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>BMB negative&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="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&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
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