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Association between white matter lesions and cerebral glucose metabolism in patients with cognitive impairment
Asociación entre daños en la sustancia blanca y metabolismo de la glucosa cerebral en pacientes con disfunción cognitiva
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"descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Radiochemical purity of <span class="elsevierStyleSup">99m</span>Tc-LAP over time in saline, at room temperature, and in the presence of plasma, at 37<span class="elsevierStyleHsp" style=""></span>°C (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>6).</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "Sued E.M. Miranda, Janaína A. Lemos, Renata S. Fernandes, Flaviano Melo Ottoni, Ricardo J. Alves, Alice Ferretti, Domenico Rubello, Valbert N. Cardoso, André L.B. de Barros" "autores" => array:9 [ 0 => array:2 [ "nombre" => "Sued E.M." "apellidos" => "Miranda" ] 1 => array:2 [ "nombre" => "Janaína A." "apellidos" => "Lemos" ] 2 => array:2 [ "nombre" => "Renata S." "apellidos" => "Fernandes" ] 3 => array:2 [ "nombre" => "Flaviano Melo" "apellidos" => "Ottoni" ] 4 => array:2 [ "nombre" => "Ricardo J." "apellidos" => "Alves" ] 5 => array:2 [ "nombre" => "Alice" "apellidos" => "Ferretti" ] 6 => array:2 [ "nombre" => "Domenico" "apellidos" => "Rubello" ] 7 => array:2 [ "nombre" => "Valbert N." "apellidos" => "Cardoso" ] 8 => array:2 [ "nombre" => "André L.B." 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WMLs are frequently observed in brain MRI of elderly subjects, particularly those with hypertension and stroke.<a class="elsevierStyleCrossRef" href="#bib0215"><span class="elsevierStyleSup">1</span></a> A recent autopsy study revealed that WMLs are associated with cerebrovascular neuropathology (amyloid angiopathy, microinfarcts, infarcts, lacunes), as well as tau pathology.<a class="elsevierStyleCrossRef" href="#bib0220"><span class="elsevierStyleSup">2</span></a> Although the pathophysiology of WMLs is not yet completely understood, several studies have revealed the role of WMLs in the development of AD.<a class="elsevierStyleCrossRefs" href="#bib0225"><span class="elsevierStyleSup">3–5</span></a> In particular, WMLs were found to be associated with gray matter atrophy in AD-related regions such as medial temporal lobe.<a class="elsevierStyleCrossRef" href="#bib0240"><span class="elsevierStyleSup">6</span></a> Furthermore, it was reported that the appearance of WMLs doubles the risk of AD dementia.<a class="elsevierStyleCrossRef" href="#bib0245"><span class="elsevierStyleSup">7</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">AD is a progressive neurodegenerative disorder characterized by neuronal dysfunction and loss of synapses along with the extracellular accumulation of cerebral β-amyloid (Aβ) plaques and intracellular neurofibrillary tangles.<a class="elsevierStyleCrossRef" href="#bib0250"><span class="elsevierStyleSup">8</span></a> An understanding of the association between the cerebral Aβ burden and neuronal dysfunction is of great importance for the characterization of the natural behaviour of the disease and the evaluation of new treatment approaches for AD. Positron emission tomography (PET) is a suitable tool for the in vivo follow-up of the natural progression of AD. <span class="elsevierStyleSup">18</span>F-fluorodeoxyglucose (FDG) and C-11 Pittsburgh compound B, <span class="elsevierStyleSup">18</span>F-florbetaben (FBB), <span class="elsevierStyleSup">18</span>F-florbetapir, or <span class="elsevierStyleSup">18</span>F-flutemetamol are the most commonly used PET biomarkers for AD; these allow noninvasive examinations of neuronal dysfunction and cerebral Aβ burden, respectively.<a class="elsevierStyleCrossRefs" href="#bib0255"><span class="elsevierStyleSup">9,10</span></a> A recent longitudinal study revealed that an increased cerebral Aβ burden in the gray matter of the brain precedes specific anatomical patterns of decreased cerebral glucose metabolism in patients with AD.<a class="elsevierStyleCrossRef" href="#bib0265"><span class="elsevierStyleSup">11</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Similar to cerebral Aβ plaques, WMLs have also been shown to contribute to a decrease in the cerebral glucose metabolism and cognitive decline.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">12</span></a> Previous studies using <span class="elsevierStyleSup">18</span>F-FDG PET revealed that a generalized decrease in the cerebral glucose metabolism was associated with an increased WML burden.<a class="elsevierStyleCrossRefs" href="#bib0275"><span class="elsevierStyleSup">13,14</span></a> Since the additional decrease in the glucose metabolism induced by WMLs in regions typically affected by cerebral Aβ plaques is likely to impose an additive effect on symptoms caused by the AD pathology itself, the overlap between the decreased cerebral glucose metabolism caused by WMLs and that caused by cerebral Aβ plaques should be clarified. However, it has not been sufficiently evidened that cognitive impairment in patients with AD is caused by WMLs as well as amyloid pathology. Thus, the aim of this study was to evaluate the relationship between WMLs and the cerebral glucose metabolism in patients with cognitive impairment after the adjustment of cerebral Aβ burden.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Materials and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study population</span><p id="par0020" class="elsevierStylePara elsevierViewall">A consecutive series of patients aged 50–90 years who were attended at our memory clinic for the evaluation of cognitive function between June 2015 and January 2017 were included in this cross-sectional study. All subjects were divided into three syndromal cognitive categories based on the 2018 National Institute on Aging-Alzheimer's Association Research Framework: cognitively unimpaired (CU), mild cognitive impairment (MCI), and AD dementia.<a class="elsevierStyleCrossRef" href="#bib0285"><span class="elsevierStyleSup">15</span></a> The Mini-Mental State Examination (MMSE), Digit Span Memory Test, Korean-Boston Naming Test (K-BNT), and Rey–Osterrieth Complex Figure Test and Recognition Trial (RCFT) were used for the assessment of cognitive function.<a class="elsevierStyleCrossRef" href="#bib0290"><span class="elsevierStyleSup">16</span></a> All subjects were examined using brain MRI, <span class="elsevierStyleSup">18</span>F-FDG PET, and <span class="elsevierStyleSup">18</span>F-FBB PET within 4 weeks of their visit to the clinic. Patients with an MMSE score of <10 and those with conditions that could affect cognition, such as vascular dementia, a history of psychiatric episodes or substance abuse, or a previous diagnosis of dementia, were excluded. The institutional review board of Dongsan Medical Center approved this study, and written informed consent was obtained from all participants or caregivers.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Brain MRI</span><p id="par0025" class="elsevierStylePara elsevierViewall">Brain MRI was performed for each patient using a 3-T Signa Excite scanner (GE Healthcare, Milwaukee, WI, USA) with an eight-channel high-resolution brain coil. We obtained an anatomic image series using a three-dimensional spoiled gradient-echo sequence. Fast spin echo T2-weighted images were acquired under the following conditions: repetition time, 4000<span class="elsevierStyleHsp" style=""></span>ms; echo time, 110<span class="elsevierStyleHsp" style=""></span>ms; field of view, 210<span class="elsevierStyleHsp" style=""></span>mm; matrix, 512<span class="elsevierStyleHsp" style=""></span>×<span class="elsevierStyleHsp" style=""></span>320; slice thickness, 5<span class="elsevierStyleHsp" style=""></span>mm; and space thickness, 2<span class="elsevierStyleHsp" style=""></span>mm. Two researchers blinded to the clinical information of patients independently rated periventricular white matter hyperintensities and deep white matter hyperintensities using a modified Fazekas scale to assess the degree of severity of WMLs on T2 MRI images.<a class="elsevierStyleCrossRef" href="#bib0295"><span class="elsevierStyleSup">17</span></a> The periventricular white matter hyperintensity score ranged from 0 to 3 as follows: 0, absent; 1, caps or pencil-thin lining; 2, smooth halo; and 3, irregular periventricular white matter hyperintensity extending into the deep white matter. The deep white matter hyperintensity score ranged from 0 to 3 as follows: 0, absence; 1, punctuated foci; 2, initial confluence of foci; and 3, large confluent areas. The Fazekas scale adopts the highest periventricular white matter hyperintensity score or deep white matter hyperintensity score. In the event of any disagreement between the two raters, a consensus was reached with the help of a neuroradiologist (H.W.C.). Patients with a Fazekas scale score of 0 or 1 were classified into the low-WML group and patients with a Fazekas scale score of 2 or 3 were classified into the high-WML group. Differences in the regional cerebral glucose metabolism were evaluated between the low- and high-WML groups.</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085"><span class="elsevierStyleSup">18</span>F-FBB and <span class="elsevierStyleSup">18</span>F-FDG PET</span><p id="par0030" class="elsevierStylePara elsevierViewall">A PET/computed tomography (CT) system (Biograph mCT-64, Siemens Healthcare, Knoxville, TN) was used to acquire <span class="elsevierStyleSup">18</span>F-FBB PET and <span class="elsevierStyleSup">18</span>F-FDG PET images. All subjects had fasted for at least 6<span class="elsevierStyleHsp" style=""></span>h before <span class="elsevierStyleSup">18</span>F-FDG PET images were obtained. A light, foam-rubber holder was used for fixation of the head. <span class="elsevierStyleSup">18</span>F-FBB PET images were acquired from 90 to 100<span class="elsevierStyleHsp" style=""></span>min after the intravenous injection of 300<span class="elsevierStyleHsp" style=""></span>MBq of <span class="elsevierStyleSup">18</span>F-FBB. <span class="elsevierStyleSup">18</span>F-FDG PET images were acquired from 30 to 40<span class="elsevierStyleHsp" style=""></span>min after the intravenous injection of 4.0<span class="elsevierStyleHsp" style=""></span>MBq/kg of <span class="elsevierStyleSup">18</span>F-FDG in a three-dimensional mode. Nonenhanced low-dose CT was performed for attenuation correction and localization in the spiral mode at 120<span class="elsevierStyleHsp" style=""></span>kVp and 150<span class="elsevierStyleHsp" style=""></span>mAs with the True X algorithm. The PET images were subjected to iterative reconstruction using ordered subset expectation maximization. Attenuation correction of the PET images was performed using attenuation data from the CT images.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Quantitative analyses were conducted for volumes of interest (VOI) using the software program PMOD (PMOD Technologies Ltd, Zurich, Switzerland), as previously described.<a class="elsevierStyleCrossRef" href="#bib0300"><span class="elsevierStyleSup">18</span></a> Image processing was performed using SPM12 (Wellcome Department of Imaging Neuroscience, Institute of Neurology, University College London) within MATLAB 2013a (MathWorks Inc., MA, USA) and MRIcro version 1.37 (Chris Rorden, Columbia, SC, USA, <a id="intr0010" class="elsevierStyleInterRef" href="http://www.mricro.com/">www.mricro.com</a>). Each MRI and PET image was coregistered with a standard mutual information algorithm and spatially normalized. An automated anatomical labeling template was subsequently applied for standardized, regional brain VOI sampling of count densities.<a class="elsevierStyleCrossRef" href="#bib0305"><span class="elsevierStyleSup">19</span></a></p><p id="par0040" class="elsevierStylePara elsevierViewall">For quantification of the cerebral Aβ burden, VOIs were individually defined in the frontal, temporal, parietal, and occipital cortices; anterior and posterior cingulate; and cerebellar cortex on <span class="elsevierStyleSup">18</span>F-FBB PET images. Standardized <span class="elsevierStyleSup">18</span>F-FBB uptake values were obtained from the defined regional VOIs. A composite standardized <span class="elsevierStyleSup">18</span>F-FBB uptake value ratio (SUVR<span class="elsevierStyleInf">FBB</span>) was calculated by dividing the mean of the standardized <span class="elsevierStyleSup">18</span>F-FBB uptake values for the frontal, temporal, and parietal cortices, and the cingulate by that for the cerebellar cortex as a reference region, as previously described.<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">20</span></a> The composite SUVR<span class="elsevierStyleInf">FBB</span> was used for evaluating the relationship between the cerebral Aβ burden and the cerebral glucose metabolism. Patients with a composite SUVR of ≥1.39, which is a previously reported cut-off value considered to reflect an abnormally high cerebral Aβ burden, were considered positive for Aβ, while those with a composite SUVR of <1.39 were considered negative for Aβ.<a class="elsevierStyleCrossRef" href="#bib0310"><span class="elsevierStyleSup">20</span></a></p><p id="par0045" class="elsevierStylePara elsevierViewall">For the quantification of the cerebral glucose metabolism, VOIs were individually defined in the central region; lateral, medial, and orbital frontal cortices; lateral temporal cortex; lateral and medial parietal cortices; lateral and medial occipital cortices; and limbic lobe on <span class="elsevierStyleSup">18</span>F-FDG PET images. Standardized <span class="elsevierStyleSup">18</span>F-FDG uptake values were obtained from the defined regional VOIs, and a regional standardized <span class="elsevierStyleSup">18</span>F-FDG uptake value ratio (SUVR<span class="elsevierStyleInf">FDG</span>) was calculated by dividing the standardized <span class="elsevierStyleSup">18</span>F-FDG uptake value for the individual target region by that for the whole brain.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Statistical analyses</span><p id="par0050" class="elsevierStylePara elsevierViewall">Composite SUVR<span class="elsevierStyleInf">FBB</span> (cerebral Aβ burden) and regional SUVR<span class="elsevierStyleInf">FDG</span> (cerebral glucose metabolism) were compared among three groups using the one-way ANOVA analysis. The Bonferroni correction was applied to a post hoc analysis of between-group comparisons. Differences of the regional SUVR<span class="elsevierStyleInf">FDG</span> between low- and high-WML groups were evaluated using two-sample <span class="elsevierStyleItalic">t</span>-test. The <span class="elsevierStyleItalic">P</span>-values were corrected for multiple comparisons using a false discovery rate correction. We also assessed the relationship between composite SUVR<span class="elsevierStyleInf">FBB</span> and regional SUVR<span class="elsevierStyleInf">FDG</span> and between composite SUVR<span class="elsevierStyleInf">FBB</span> and the MMSE score using Pearson's correlation analysis. Spearman's correlation analyses were performed to evaluate the relationship of the Fazekas scale score with SUVR<span class="elsevierStyleInf">FDG</span> and the MMSE score. Multiple linear regression analyses, which were adjusted for age, sex, and composite SUVR<span class="elsevierStyleInf">FBB</span>, or adjusted for age, sex, and cognitive staging, were performed to evaluate the effects of the Fazekas scale score on the regional SUVR<span class="elsevierStyleInf">FDG</span> and MMSE score. A <span class="elsevierStyleItalic">P</span>-value of <0.05 was considered statistically significant.</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Patient characteristics</span><p id="par0055" class="elsevierStylePara elsevierViewall">A total of 83 subjects were enrolled in this study. Of these 83 subjects, 19 were categorized into CU, 30 into MCI, and 34 into AD dementia. A flowchart of the study population is presented in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>. The time interval between brain MRI and <span class="elsevierStyleSup">18</span>F-FDG PET was 6.8<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>6.4 days (range, 0–23 days), while that between <span class="elsevierStyleSup">18</span>F-FBB PET and <span class="elsevierStyleSup">18</span>F-FDG PET was 3.2<span class="elsevierStyleHsp" style=""></span>±<span class="elsevierStyleHsp" style=""></span>3.7 days (range, 0–27 days). Descriptive information for the characteristics of the included patients is provided in <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>.</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0060" class="elsevierStylePara elsevierViewall">With regard to the cerebral Aβ burden, regional and composite SUVR<span class="elsevierStyleInf">FBB</span> were significantly higher for the AD dementia group than for the CU and MCI groups (<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001) (Supplemental Table 1). With regard to the cerebral glucose metabolism, SUVR<span class="elsevierStyleInf">FDG</span> in the bilateral lateral frontal, lateral temporal, and lateral parietal cortices and limbic lobes was significantly lower for the AD dementia group than for the CU and MCI groups (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0105">Relationship between WMLs and the cerebral glucose metabolism</span><p id="par0065" class="elsevierStylePara elsevierViewall">The regional SUVR<span class="elsevierStyleInf">FDG</span> for the bilateral lateral frontal, bilateral lateral temporal, and left lateral parietal cortices, and bilateral limbic lobes in the high-WML group were significantly lower than those in the low-WML group (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">There was a significant negative correlation between the Fazekas scale score and regional SUVR<span class="elsevierStyleInf">FDG</span> in the bilateral lateral frontal (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.389, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.345, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001), bilateral lateral temporal (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.326, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.003 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.343, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002) and left lateral parietal cortices (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.267, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.015), and bilateral limbic lobes (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.355, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.001 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>-0.333, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002). Composite SUVR<span class="elsevierStyleInf">FBB</span> and regional SUVR<span class="elsevierStyleInf">FDG</span> in the bilateral lateral temporal cortices (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.255, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.020 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.335, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.002), lateral parietal cortices (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.268, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.014 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.224, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.042) and bilateral limbic lobes (left; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.276, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.012 and right; <span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.239, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.029) also exhibited a significant negative correlation. Multiple linear regression analysis adjusted for age, sex and composite SUVR<span class="elsevierStyleInf">FBB</span> revealed that the Fazekas scale score was an independent determinant of the regional SUVR<span class="elsevierStyleInf">FDG</span> in the bilateral lateral frontal, lateral temporal, lateral parietal and limbic lobes (<a class="elsevierStyleCrossRef" href="#tbl0020">Table 4</a>). Multiple linear regression analysis, adjusted for age, sex, and cognitive staging, revealed that the Fazekas scale score was an independent determinant of the regional SUVR<span class="elsevierStyleInf">FDG</span> in the left lateral frontal, bilateral lateral temporal, and left lateral parietal cortices, as well as the bilateral limbic lobes (Supplemental Table 2). Representative T2 FLAIR MRI and <span class="elsevierStyleSup">18</span>F-FDG PET images are presented in <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>.</p><elsevierMultimedia ident="tbl0020"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">There were significant negative correlations between the Fazekas scale score and the MMSE score (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.387, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>0.001) and between composite SUVR<span class="elsevierStyleInf">FBB</span> and the MMSE score (<span class="elsevierStyleItalic">r</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.327, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.003). Multiple linear regression analysis adjusted for age, sex and composite SUVR<span class="elsevierStyleInf">FBB</span> revealed that the Fazekas scale score were independent factors affecting the MMSE score (adjusted <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.097, standardized <span class="elsevierStyleItalic">β</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>−0.318, <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>0.003).</p></span></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0110">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">In the present study, we found a negative correlation between WMLs and the cerebral glucose metabolism in patients with cognitive impairment. This finding suggests that not only the cerebral Aβ burden, but also WMLs, which are a consequence of small vessel disease, contribute to cognitive impairment in the elderly. In concordance with our findings, previous studies reported a considerable overlap between small vessel disease and AD, with an increased prevalence of WMLs. Moreover, it was reported that WMLs lower the threshold for the clinical expression of dementia at a certain burden of AD pathology.<a class="elsevierStyleCrossRef" href="#bib0315"><span class="elsevierStyleSup">21</span></a> WMLs are considered potential risk factors for memory and cognitive impairment<a class="elsevierStyleCrossRef" href="#bib0320"><span class="elsevierStyleSup">22</span></a> and are reportedly associated with an increased incidence of dementia<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">3</span></a> as well as the development of white matter microstructural changes in the presymptomatic stage of AD.<a class="elsevierStyleCrossRef" href="#bib0325"><span class="elsevierStyleSup">23</span></a></p><p id="par0085" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleSup">18</span>F-FDG PET has been used to measure the resting-state cerebral glucose metabolism, which is a proxy for neuronal activity. In patients with AD, <span class="elsevierStyleSup">18</span>F-FDG PET shows a characteristic pattern of decreased glucose metabolism in the hippocampi or medial temporal cortices, posterior cingulate, precuneus, and lateral temporoparietal cortex.<a class="elsevierStyleCrossRef" href="#bib0330"><span class="elsevierStyleSup">24</span></a> Milder but similar regional changes are observed in patients with MCI who are likely to progress to clinical AD, whereas patients with more advanced AD typically show frontal cortex involvement.<a class="elsevierStyleCrossRef" href="#bib0335"><span class="elsevierStyleSup">25</span></a> In accordance with previous studies, the present study revealed decreased glucose metabolism in the bilateral frontal, lateral temporal, and lateral parietal cortices and limbic lobes in patients with AD dementia. Recent studies reported that the longitudinal pattern of decreased cerebral metabolism anatomically follows the pattern of amyloid deposition with temporal delay, which indicates that neuronal dysfunction spreads within the anatomical pattern of cerebral Aβ pathology.<a class="elsevierStyleCrossRef" href="#bib0340"><span class="elsevierStyleSup">26</span></a> In accordance with these studies, the present study also revealed that the cerebral glucose metabolism in the bilateral frontal, temporal, and parietal cortices and limbic lobes was significantly lower for the AD dementia group than for the CU and MCI groups.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Many factors that increase the risk of cerebrovascular disease are associated with a higher risk of AD. These factors include smoking, obesity in midlife and diabetes.<a class="elsevierStyleCrossRef" href="#bib0225"><span class="elsevierStyleSup">3</span></a> In addition, several studies have shown associations between WMLs and AD pathology.<a class="elsevierStyleCrossRefs" href="#bib0345"><span class="elsevierStyleSup">27–29</span></a> A large population-based study reported that WMLs contribute to brain atrophy patterns in regions related to AD,<a class="elsevierStyleCrossRef" href="#bib0235"><span class="elsevierStyleSup">5</span></a> and another study proposed that the appearance of WMLs doubles risk of AD.<a class="elsevierStyleCrossRef" href="#bib0360"><span class="elsevierStyleSup">30</span></a> WMLs are frequently observed as white matter hyperintensities on brain T2-weighted images in the elderly, particularly in hypertension and stroke patients.<a class="elsevierStyleCrossRef" href="#bib0365"><span class="elsevierStyleSup">31</span></a> These lesions have been known to occur as a consequence of ischemia and may be caused by small vessel disease.<a class="elsevierStyleCrossRef" href="#bib0370"><span class="elsevierStyleSup">32</span></a> The present study revealed weak to moderate correlations between WML burden and decreased glucose metabolism in the bilateral lateral frontal, lateral temporal, and lateral parietal cortices, as well as the limbic lobe. This finding implies that there are factors other than WML, such as age, sex, or Aβ, which affect the decreased cerebral glucose metabolism. Nevertheless, the present study revealed that, even after adjustment for age, sex and cerebral Aβ burden, the WML burden remained a significant determinant of cerebral glucose metabolism. This finding corresponds with the results of previous studies regarding other diseases, in which WMLs were associated with diffusely decreased glucose metabolism in the cerebral cortex. An <span class="elsevierStyleSup">18</span>F-FDG PET study showed that patients with vascular dementia had a more diffuse pattern of decreased glucose metabolism in the cortex and greater difficulty maintaining sustained attention than those with probable AD.<a class="elsevierStyleCrossRef" href="#bib0270"><span class="elsevierStyleSup">12</span></a> Another cohort study involving patients with cognitive impairment revealed a significant relationship between the disruption of limbic white matter pathways and decreased glucose metabolism in the parietal and temporal cortices and posterior cingulated.<a class="elsevierStyleCrossRef" href="#bib0375"><span class="elsevierStyleSup">33</span></a> Furthermore, in cognitively unimpaired subjects, a MRI study using the connectivity change score also revealed that the gray matter with more impaired connectivity due to WMLs also had lower glucose metabolism.<a class="elsevierStyleCrossRef" href="#bib0380"><span class="elsevierStyleSup">34</span></a> These findings can be attributed to the fact that WMLs represent demyelination and axonal destruction in the periventricular white matter and deep white matter. Pathological studies revealed that extensive WMLs were associated with a decreased density of glia and vacuolation, while subtle WMLs were associated with microglial and endothelial activation.<a class="elsevierStyleCrossRef" href="#bib0385"><span class="elsevierStyleSup">35</span></a></p><p id="par0095" class="elsevierStylePara elsevierViewall">WMLs occur more commonly in patients with AD than in normal elderly controls, possibly as a consequence of small vessel disease.<a class="elsevierStyleCrossRefs" href="#bib0215"><span class="elsevierStyleSup">1,3</span></a> Moreover, WMLs can be etiologically related to the dementia or a coincident finding.<a class="elsevierStyleCrossRef" href="#bib0390"><span class="elsevierStyleSup">36</span></a> Patients with AD combined with vascular dementia constitute an important subset of patients with dementia.<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">37</span></a> A recent study using diffusion tensor imaging revealed substantial overlap of areas of regional decrease in fractional anisotropy, which is an index of the WML burden, in patients with MCI and AD.<a class="elsevierStyleCrossRef" href="#bib0400"><span class="elsevierStyleSup">38</span></a> This indicated that WMLs occur in patients with MCI prior to the development of dementia. Pure vascular dementia without Aβ pathology is uncommon, and many patients who do not meet the pathological criteria for either AD or vascular dementia have cognitive deficits as a result of AD combined with vascular disease.<a class="elsevierStyleCrossRef" href="#bib0395"><span class="elsevierStyleSup">37</span></a> A meta-analysis revealed that WMLs are associated with attenuated performance in tasks involving processing speed, immediate and delayed memory, executive functions, and indices of global cognitive functioning.<a class="elsevierStyleCrossRef" href="#bib0405"><span class="elsevierStyleSup">39</span></a> In accordance with previous studies, the present study showed a negative correlation between the WML burden and the MMSE score. Even after adjustment for the cerebral Aβ burden, the WML burden was an independent determinant of the MMSE score. This finding suggests that WMLs contribute to cognitive impairment with cerebral Aβ accumulation and may facilitate the emergence of clinical signs of dementia in individuals with proven AD or make AD-related impairment evident at a younger age.<a class="elsevierStyleCrossRef" href="#bib0410"><span class="elsevierStyleSup">40</span></a> Thus, strategies to prevent cerebral small vessel disease, including medication, rehabilitation, and surgery, may help to decrease prevalence of AD dementia, or prevent its progression. Modification of traditional risk factors and a healthy lifestyle are currently the most important prophylactic and therapeutic approaches for cerebral small vessel disease.<a class="elsevierStyleCrossRef" href="#bib0415"><span class="elsevierStyleSup">41</span></a></p><p id="par0100" class="elsevierStylePara elsevierViewall">The present study has some limitations. First, the WML burden was visually assessed using the Fazekas scale. This could have influenced our results. However, even with current semi-automatic or automatic quantitative methods for assessing WML burden, lesion measurements and brain tissue parameters can be affected during image processing, differentiation from artifacts, and coregistration.<a class="elsevierStyleCrossRef" href="#bib0405"><span class="elsevierStyleSup">39</span></a> Since the consistency of the Fazekas scale scoring system has been proven,<a class="elsevierStyleCrossRef" href="#bib0420"><span class="elsevierStyleSup">42</span></a> our results would be minimally affected. Second, the present study did not reveal changes in the glucose metabolism with the progression of WMLs because of the cross-sectional design. Despite these limitations, the present study revealed that small vessel disease can affect cognitive impairment in addition to the cerebral Aβ accumulation. Further longitudinal studies with large sample sizes are necessary for evaluating the contribution of small vessel disease to cognitive impairment.</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0115">Conclusion</span><p id="par0105" class="elsevierStylePara elsevierViewall">WMLs are associated with decreased cerebral glucose metabolism. Our findings suggest that small vessel disease, as well as Aβ pathology, may contribute to cognitive impairment in patients with AD.</p></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0120">Ethical approval</span><p id="par0110" class="elsevierStylePara elsevierViewall">All procedures involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration.</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0125">Informed consent</span><p id="par0115" class="elsevierStylePara elsevierViewall">The institutional review board approved this study, and written informed consent was obtained from all participants or caregivers.</p></span><span id="sec0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0130">Funding</span><p id="par0120" class="elsevierStylePara elsevierViewall">This study was supported by Bumsuk Academic Research Fund in 2016. The authors have no conflict of interest to report.</p></span><span id="sec0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0135">Conflicts of interest</span><p id="par0125" class="elsevierStylePara elsevierViewall">The authors have no conflicts of interest to declare.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:14 [ 0 => array:3 [ "identificador" => "xres1185597" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Aim" ] 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" => "xpalclavsec1105403" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1185596" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1105402" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Materials and methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Study population" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Brain MRI" ] 2 => array:2 [ "identificador" => "sec0025" "titulo" => "F-FBB and F-FDG PET" ] 3 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical analyses" ] ] ] 6 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Patient characteristics" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Relationship between WMLs and the cerebral glucose metabolism" ] ] ] 7 => array:2 [ "identificador" => "sec0050" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0055" "titulo" => "Conclusion" ] 9 => array:2 [ "identificador" => "sec0060" "titulo" => "Ethical approval" ] 10 => array:2 [ "identificador" => "sec0065" "titulo" => "Informed consent" ] 11 => array:2 [ "identificador" => "sec0070" "titulo" => "Funding" ] 12 => array:2 [ "identificador" => "sec0075" "titulo" => "Conflicts of interest" ] 13 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2018-10-11" "fechaAceptado" => "2018-12-08" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1105403" "palabras" => array:6 [ 0 => "White matter lesion" 1 => "Small vessel disease" 2 => "Alzheimer's disease" 3 => "β-Amyloid" 4 => "<span class="elsevierStyleSup">18</span>F-FDG" 5 => "Positron emission tomography" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1105402" "palabras" => array:5 [ 0 => "Daños en la sustancia blanca" 1 => "Enfermedad de pequeños vasos" 2 => "Enfermedad de Alzheimer" 3 => "β-Amiloide" 4 => "PET con 18<span class="elsevierStyleInf">F</span>-FDG" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Aim</span><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">White matter lesions (WMLs), detected as hyperintensities in T2-weighted MRI, represent small vessel disease in the brain and are considered a potential risk factor for memory and cognitive impairment. It has not been sufficiently evidenced that cognitive impairment in patients with Alzheimer's disease is caused by WMLs as well as β-amyloid (Aβ) pathology. The aim of this study was to evaluate the relationship between WMLs and cerebral glucose metabolism in patients with cognitive impairment after adjustment of cerebral Aβ burden.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials and methods</span><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Eighty-three subjects with cognitive performance ranging from normal to dementia, who underwent brain MRI and <span class="elsevierStyleSup">18</span>F-florbetaben positron emission tomography (PET) and <span class="elsevierStyleSup">18</span>F-fluorodeoxyglucose PET, were included in this cross-sectional study. The Fazekas scale was used to quantify WMLs on brain T2-weighted MRI. The cerebral Aβ burden and cerebral glucose metabolism were quantitatively estimated using volume-of-interest analysis. Differences in the regional cerebral glucose metabolism were evaluated between low-WML (Fazekas scale<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>2) and high-WML (Fazekas scale<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>2) groups. Multiple linear regression analysis adjusted for age, sex and cerebral Aβ burden was performed to evaluate the relationship between the Fazekas scale score and cerebral glucose metabolism.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">The regional cerebral glucose metabolism for the bilateral frontal, temporal, and parietal cortices, and limbic lobes in the high-WML group were significantly lower than those in the low-WML group. There were significant negative correlations between the Fazekas scale score and regional cerebral glucose metabolism in the bilateral frontal, bilateral temporal and left parietal cortices, and bilateral limbic lobes. Multiple linear regression analysis revealed that the Fazekas scale score was an independent determinant of the glucose metabolism in the bilateral frontal and temporal cortices and limbic lobes.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">WMLs are associated with decreased cerebral glucose metabolism. Our findings suggest that small vessel disease, as well as Aβ pathology, may contribute to cognitive impairment in patients with Alzheimer's disease.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Aim" ] 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" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Objetivo</span><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Los daños en la sustancia blanca (DSB), detectados como hiperintensidades en las imágenes de RM ponderadas en T2, representan la enfermedad de pequeños vasos cerebrales, y están considerados como un factor de riesgo potencial de trastornos de la memoria y disfunción cognitiva. No se ha evidenciado suficientemente que la disfunción cognitiva en pacientes con enfermedad de Alzheimer esté causada por DSB y la patología β-amiloide (Aβ). El objetivo de estudio fue evaluar la relación entre los DSB y el metabolismo de la glucosa cerebral en pacientes con disfunción cognitiva, tras el ajuste de la carga cerebral de Aβ.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materiales y métodos</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Incluimos en este estudio transversal a ochenta y tres sujetos con desempeño cognitivo que oscilaba entre normal y demencia, a quienes se realizó RM cerebral y PET con Florbetaben (18<span class="elsevierStyleInf">F</span>) y PET con 18<span class="elsevierStyleInf">F</span>-FDG. Utilizamos la escala Fazekas para cuantificar los DSB en la RM cerebral ponderada en T2. Estimamos cuantitativamente la carga cerebral de Aβ y el metabolismo de la glucosa cerebral utilizando el análisis del volumen de interés. Evaluamos las diferencias del metabolismo de la glucosa cerebral regional entre los grupos de bajo DSB (escala Fazekas<span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>2) y alto DSB (escala Fazekas<span class="elsevierStyleHsp" style=""></span>≥<span class="elsevierStyleHsp" style=""></span>2). Realizamos un análisis de regresión lineal múltiple ajustado por edad, sexo y carga cerebral de Aβ, para evaluar la relación entre la puntuación de la escala Fazekas y el metabolismo de la glucosa cerebral.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">El metabolismo de la glucosa cerebral regional para los lóbulos bilateral frontal, temporal, córtices parietales, y lóbulos límbicos en el grupo de alto DSB fueron significativamente menores que los del grupo de bajo DSB. Existieron correlaciones negativas significativas entre la puntuación de la escala Fazekas y el metabolismo de la glucosa cerebral regional en los córtices bilateral frontal, bilateral temporal y córtices parietales izquierdos, y lóbulos límbicos bilaterales. Los análisis de regresión lineal múltiple revelaron que la puntuación de la escala Fazekas era un determinante independiente del metabolismo de la glucosa en los córtices bilateral frontal y temporal y los lóbulos límbicos.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Los DSB están asociados a un descenso del metabolismo de la glucosa cerebral. Nuestros hallazgos sugieren que la enfermedad de pequeños vasos, así como lo patología de Aβ, pueden contribuir a la disfunción cognitiva en pacientes con enfermedad de Alzheimer.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Objetivo" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0025">Please cite this article as: No H-J, Yi H-A, Won KS, Chang HW, Kim HW. Asociación entre daños en la sustancia blanca y metabolismo de la glucosa cerebral en pacientes con disfunción cognitiva. Rev Esp Med Nucl Imagen Mol. 2019;38:160–166.</p>" ] ] "multimedia" => array:6 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1109 "Ancho" => 2022 "Tamanyo" => 149170 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">Flow diagram of the study population.</p>" ] ] 1 => array:7 [ "identificador" => "fig0010" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 2550 "Ancho" => 2167 "Tamanyo" => 395128 ] ] "descripcion" => array:1 [ "en" => "<p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Representative T2 FLAIR MRI and <span class="elsevierStyleSup">18</span>F-FDG PET images in patients with cognitive impairment. As the fazekas scale score is higher, glucose metabolism is lower in the parietal and temporal cortices. (A) A cognitively unimpaired 56-year-old man with negative Aβ burden (SUVR<span class="elsevierStyleInf">FBB</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.34) and grade 0 of Fazekas scale had no abnormal glucose metabolism in the bilateral parietal and temporal cortices. (B) A mild cognitively impaired 66-year-old woman with positive Aβ burden (SUVR<span class="elsevierStyleInf">FBB</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.55) and grade 1 of Fazekas scale had mildly decreased glucose metabolism in the right parietal and temporal cortices. (C) A mild cognitively impaired 68-year-old woman with positive Aβ burden (SUVR<span class="elsevierStyleInf">FBB</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.47) and grade 2 of Fazekas scale had moderately decreased glucose metabolism in the bilateral parietal and temporal cortices. (D) A demented 72-year-old man with positive Aβ burden (SUVR<span class="elsevierStyleInf">FBB</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>1.71) and grade 3 of Fazekas scale had severely decreased glucose metabolism in the bilateral parietal and temporal cortices.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">CU<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>cognitively unimpaired, MCI<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>mild cognitive impairment, AD<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>Alzheimer's disease, K-BNT<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>Korean–Boston Naming Test, RCFT<span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>Rey–Osterrieth Complex Figure Test and Recognition Trial.</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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Characteristic \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Overall (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>83) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CU (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>19) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">MCI (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>30) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AD dementia (<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>=<span class="elsevierStyleHsp" style=""></span>34) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span> value \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Post hoc results \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Age, y \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">65.7 (9.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">62.5 (5.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">64.9 (9.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">68.2 (9.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.083 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Female, % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">61.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">63.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">56.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">64.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.792 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Education, y \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.5 (5.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">14.2 (3.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">12.8 (5.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">8.8 (8.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.061 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">APOE4+, % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">18.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">22.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">40.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.122 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">MMSE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">24.2 (5.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">28.7 (1.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">25.7 (2.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">20.1 (5.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN><span class="elsevierStyleHsp" style=""></span>MCI><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Digit span \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9.3 (2.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">11.7 (2.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">10.0 (2.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">7.5 (2.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN<span class="elsevierStyleHsp" style=""></span>>MCI<span class="elsevierStyleHsp" style=""></span>>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">K-BNT \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">42.7 (12.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">51.8 (3.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">46.3 (9.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">34.4 (13.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">RCFT \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">27.9 (8.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">33 (2.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">30.6 (5.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21.9 (10.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Fazekas scale \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.0 (1.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.5 (0.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">0.8 (0.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.4 (1.0) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<<span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Grade 0–1, <span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">51 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">21 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Grade 2–3, <span class="elsevierStyleItalic">n</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">32 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">19 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Composite SUVR<span class="elsevierStyleInf">FBB</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.50 (0.25) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.32 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.45 (0.22) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">1.55 (0.31) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.006 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<<span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Aβ positivity, % \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">33.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">15.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">26.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">50.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.016 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2021875.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">All values are means (SD).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Characteristics of patients<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a></p>" ] ] 3 => 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" ] ] "tabla" => array:2 [ "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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Region \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Side \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CU \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">MCI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">AD dementia \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Corrected<br><span class="elsevierStyleItalic">P</span>-value \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Post hoc results \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Central</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.02) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.02) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.851 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.02) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.079 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.97 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.008 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial Frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.884 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.325 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Orbital frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.983 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.91 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.371 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral temporal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.07 (0.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.06 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.017 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.05 (0.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.05 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral parietal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.13) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.89 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.029 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial parietal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.08 (0.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.09 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.05 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.269 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.06 (0.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.07 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.13) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.373 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral occipital</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.97 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.620 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.15) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.98 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.96 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.594 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial occipital</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.02 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.03 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.03 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.785 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.03 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.729 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">– \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Limbic</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.89 (0.05) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.83 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.82 (0.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.84 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.77 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">CN, MCI<span class="elsevierStyleHsp" style=""></span>><span class="elsevierStyleHsp" style=""></span>AD \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2021878.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">All values are means (SD).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Comparisons of SUVR<span class="elsevierStyleInf">FDG</span> among cognitively unimpaired (CU), mild cognitive impairment (MCI), and Alzheimer's disease (AD) dementia groups<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">a</span></a></p>" ] ] 4 => 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" ] ] "tabla" => array:2 [ "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="table-head ; entry_with_role_rowhead " align="left" valign="top" scope="col">Region \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col">Side \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="2" align="center" valign="top" scope="col" style="border-bottom: 2px solid black">WML burden</th><th class="td" title="table-head " align="left" valign="top" scope="col">Corrected<br><span class="elsevierStyleItalic">P</span>-value \t\t\t\t\t\t\n \t\t\t\t</th></tr><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Low \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">High \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Central</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.02) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.02 (0.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.503 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.03) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.04) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.035 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.97 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.042 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial Frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.141 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.92 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.047 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Orbital frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.009) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.91 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.439 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.095 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral temporal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.06 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.01 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.006 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.05 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.99 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral parietal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.00 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.94 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.020 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.93 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.90 (0.09) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.170 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial parietal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.07 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.08 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.793 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.10) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.08 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.592 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral occipital</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.95 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.96 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.663 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.96 (0.13) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.96 (0.12) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.890 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Medial occipital</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.03 (0.08) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.02 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.606 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1.04 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.764 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Limbic</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.89 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.84 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.82 (0.06) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.78 (0.07) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.004 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2021876.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">All values are means (SD).</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Comparisons of SUVR<span class="elsevierStyleInf">FDG</span> between the low- and high-white matter lesion (WML) groups<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">a</span></a></p>" ] ] 5 => array:8 [ "identificador" => "tbl0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at4" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "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="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Region \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Side \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Adjusted <span class="elsevierStyleItalic">R</span><span class="elsevierStyleSup">2</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Standardized <span class="elsevierStyleItalic">β</span><a class="elsevierStyleCrossRef" href="#tblfn0020"><span class="elsevierStyleSup">a</span></a> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleItalic">P</span>-value \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral frontal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.145 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.394 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top"><0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.084 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.308 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.005 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral temporal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.127 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.371 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.161 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.276 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.011 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Lateral parietal</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.060 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.268 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.014 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.038 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.224 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.042 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " rowspan="2" align="left" valign="top">Limbic</td><td class="td" title="table-entry " align="left" valign="top">Left \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.126 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.369 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="table-entry ; entry_with_role_rowhead " align="left" valign="top">Right \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.097 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">−0.329 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2021877.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Values presented are standardized linear regression coefficients (<span class="elsevierStyleItalic">β</span>) representing the correlation of the Fazekas scale with SUVR<span class="elsevierStyleInf">FDG</span> after adjustment for age, sex and cerebral Aβ burden.</p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">The relationships of the Fazekas scale score with SUVR<span class="elsevierStyleInf">FDG</span>.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:42 [ 0 => array:3 [ "identificador" => "bib0215" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Age, hypertension, and lacunar stroke are the major determinants of the severity of age-related white matter changes. The LADIS (Leukoaraiosis and Disability in the Elderly) Study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A.M. Basile" 1 => "L. Pantoni" 2 => "G. Pracucci" 3 => "K. Asplund" 4 => "H. Chabriat" 5 => "T. Erkinjuntti" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "Revista" => array:5 [ "tituloSerie" => "Cerebrovasc Dis" "fecha" => "2006" "volumen" => "21" "paginaInicial" => "315" "paginaFinal" => "322" ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0220" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A clinicopathological investigation of white matter hyperintensities and Alzheimer's disease neuropathology" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "M.L. Alosco" 1 => "M.A. Sugarman" 2 => "L.M. Besser" 3 => "Y. Tripodis" 4 => "B. Martin" 5 => "J.N. 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