Gray matter atrophy in progressive supranuclear palsy: meta-analysis of voxel-based morphometry studies

Abstract

Voxel-based morphometry (VBM) studies have provided cumulative evidence of gray matter (GM) atrophy in patients with progressive supranuclear palsy (PSP) relative to healthy controls (HC). However, not all findings have been entirely concordant. Herein, we performed a quantitative meta-analysis study in order to consistently quantify GM anomalies in PSP. We conducted a systematic search for VBM studies of PSP patients and HC using PubMed and Embase databases from January 2000 to May 2012. Meta-analysis of these VBM studies was performed using a newly improved voxel-based meta-analytic technique, effect-size signed differential mapping. A total of 9 cross-sectional VBM studies that involved 143 PSP patients and 216 HC subjects met the inclusion criteria. Considerable regional GM volume decrease was detected in the thalamus, basal ganglia, midbrain, insular cortex, and frontal cortex. These findings remained largely unchanged following jackknife sensitivity analyses. The present meta-analysis provided evidence of PSP-specific GM atrophy. This finding might help contribute to our understanding of the neurobiological basis underlying PSP.

Disrupted Resting-State Functional Connectivity in Progressive Supranuclear Palsy

“…38,39 In this study, patients with PSP displayed a gray matter volume decrease in subcortical structures and DTI abnormalities in white matter compared with healthy subjects, which is in keeping with the results of previous studies. [5][6][7] These structural abnormalities did not correlate with FC. Although it is commonly assumed that FC reflects structural connectivity, the relationship between the 2 is rather complex 40 : FC can be observed, for example, between regions with no or few anatomic connections, owing to the dynamic reorganization capabilities of functional connections in the brain.…”

Disease-Specific Regions Outperform Whole-Brain Approaches in Identifying Progressive Supranuclear Palsy: A Multicentric MRI Study

“…Many studies found a diminished gray matter density (GMD) in the left and right insulae (Brenneis et al, 2004; Padovani et al, 2006; Ghosh et al, 2012). Several papers reported a reduced GMD in the thalamus (Cordato et al, 2005; Boxer et al, 2006; Padovani et al, 2006; Shi et al, 2013), but other papers did not find GMD changes here (Brenneis et al, 2004; Ghosh et al, 2012). Volumetric analysis of structural MRI showed a significantly smaller putamen in PSP patients in comparison to healthy controls (Messina et al, 2011).…”

“…Recently, quantitative and systematic meta-analyses have been introduced to imaging data to identify the prototypical neural correlates of neurodegenerative diseases (Schroeter et al, 2007, 2008, 2009). Meanwhile three comprehensive meta-analyses have applied methods like anatomical likelihood estimates or effect-size signed differential mapping to PSP studies (Shi et al, 2013; Shao et al, 2014; Yu et al, 2015). By investigating gray matter changes, these meta-analyses consistently identified the thalamus, basal ganglia, insula, and midbrain as the disease-specific core network of PSP.…”

“…Similar to their approach (Dukart et al, 2013) and in contrast to other recent work (Focke et al, 2011; Salvatore et al, 2014), we used disease-specific ROIs based on meta-analytically extracted prototypical neural networks for PSP (Shi et al, 2013; Shao et al, 2014; Yu et al, 2015) and performed SVM classification using the voxels within these ROIs for feature selection in addition to whole-brain analyses. Note that the ROIs are defined here (Shi et al, 2013; Shao et al, 2014; Yu et al, 2015) in an independent cohort in a data-driven manner. We compared the resulting accuracy rates with the results from a whole-brain approach, expecting higher accuracy rates within the ROI-based technique.…”

Quantitative T1 and T2 MRI signal characteristics in the human brain: different patterns of MR contrasts in normal ageing

“…MRI has been widely employed for volumetric and morphometric analysis of changes in the brain [10–20]. However, brain tissue microstructure and chemistry also change with age and alter magnetic resonance parameters, subsequently influencing the contrast in various MRI modalities.…”