Quantification of global cerebral atrophy in multiple sclerosis from 3T MRI using SPM: the role of misclassification errors

Abstract

Purpose: We tested the validity of a freely available segmentation pipeline to measure compartmental brain volumes from 3T MRI in patients with multiple sclerosis (MS). Our primary focus was methodological to explore the effect of segmentation corrections on the clinical relevance of the output metrics.

Methods: Three-dimensional T1-weighted images were acquired to compare 61 MS patients to 30 age- and gender-matched normal controls (NC). We also tested the within patient MRI relationship to disability (eg, expanded disability status scale [EDSS] score) and cognition. Statistical parametric mapping v. 8 (SPM8)-derived gray matter (GMF), white matter (WMF), and total brain parenchyma fractions (BPF) were derived before and after correcting errors from T1 hypointense MS lesions and/or ineffective deep GM contouring.

Results: MS patients had lower GMF and BPF as compared to NC (P<.05). Cognitively impaired patients had lower BPF than cognitively preserved patients (P<.05). BPF was related to EDSS; BPF and GMF were related to disease duration (all P<.05). Errors caused bias in GMFs and WMFs but had no discernable influence on BPFs or any MRI-clinical associations.

Conclusions: We report the validity of a segmentation pipeline for the detection of MS-related brain atrophy with 3T MRI. Longitudinal studies are warranted to extend these results.

Keywords: Brain atrophy; MRI; gray matter; lesions; multiple sclerosis; segmentation.

Figure 1

This flow chart represents the image processing steps that were followed to obtain final segmentation for masks gray matter (GM), white matter (WM), and CSF. Raw MDEFT images were manually deskulled, intensity normalized, and automatically segmented into GM, WM, and CSF. The obtained segmentation masks were corrected for misclassifications of deep GM and T1 hypointensities. The generated GM correction mask and T1 hypointensities mask were used to correct the original tissue masks, thus obtaining final corrected segmentations for GM, WM, and CSF.

Figure 2

Panels A and B show a representative slice of a raw axial MDEFT image before and after manual skull stripping in a patient with MS. Panel C shows the corresponding uncorrected SPM8-derived segmented images obtained for white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) tissue compartments; note the images from left to right show: underestimation of the volume of the putamen and thalamus (anterior arrows) and misclassification of T1 hypointensities in WM as GM (posterior arrows). Panel D shows the corresponding segmentations obtained for the same tissue dually corrected compartments (ie, after manually correcting both types of errors).