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

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.

The impact of lesion in-painting and registration methods on voxel-based morphometry in detecting regional cerebral gray matter atrophy in multiple sclerosis

BACKGROUND AND PURPOSE

VBM has been widely used to study GM atrophy in MS. MS lesions lead to segmentation and registration errors that may affect the reliability of VBM results. Improved segmentation and registration have been demonstrated by WM LI before segmentation. DARTEL appears to improve registration versus the USM. Our aim was to compare the performance of VBM-DARTEL versus VBM-USM and the effect of LI in the regional analysis of GM atrophy in MS.

MATERIALS AND METHODS

3T T1 MR imaging scans were acquired from 26 patients with RRMS and 28 age-matched NC. LI replaced WM lesions with normal-appearing WM intensities before image segmentation. VBM analysis was performed in SPM8 by using DARTEL and USM with and without LI, allowing the comparison of 4 VBM methods (DARTEL + LI, DARTEL - LI, USM + LI, and USM - LI). Accuracy of VBM was assessed by using NMI, CC, and a simulation analysis.

RESULTS

Overall, DARTEL + LI yielded the most accurate GM maps among the 4 methods (highest NMI and CC, P < .001). DARTEL + LI showed significant GM loss in the bilateral thalami and caudate nuclei in patients with RRMS versus NC. The other 3 methods overestimated the number of regions of GM loss in RRMS versus NC. LI improved the accuracy of both VBM methods. Simulated data suggested the accuracy of the results provided from patient MR imaging analysis.

CONCLUSIONS

We introduce a pipeline that shows promise in limiting segmentation and registration errors in VBM analysis in MS.

Neurovascular coupling is impaired in slow walkers: the MOBILIZE Boston Study

OBJECTIVE

Neurovascular coupling may be involved in compensatory mechanisms responsible for preservation of gait speed in elderly people with cerebrovascular disease. Our study examines the association between neurovascular coupling in the middle cerebral artery and gait speed in elderly individuals with impaired cerebral vasoreactivity.

METHODS

Twenty-two fast and 20 slow walkers in the lowest quartile of cerebral vasoreactivity were recruited from the MOBILIZE Boston Study. Neurovascular coupling was assessed in bilateral middle cerebral arteries by measuring cerebral blood flow during the N-Back task. Cerebral white matter hyperintensities were measured for each group using magnetic resonance imaging.

RESULTS

Neurovascular coupling was attenuated in slow compared to fast walkers (2.8%; 95% confidence interval [CI], -0.9 to 6.6 vs 8.2%; 95% CI, 4.7-11.8; p = 0.02). The odds ratio of being a slow walker was 6.4 (95% CI, 1.7-24.9; p = 0.007) if there was a high burden of white matter hyperintensity; however, this risk increased to 14.5 (95% CI, 2.3-91.1; p = 0.004) if neurovascular coupling was also attenuated.

INTERPRETATION

Our results suggest that intact neurovascular coupling may help preserve mobility in elderly people with cerebral microvascular disease.

A 3T MR imaging investigation of the topography of whole spinal cord atrophy in multiple sclerosis

BACKGROUND AND PURPOSE

Spinal cord atrophy is a common feature of MS. However, it is unknown which cord levels are most susceptible to atrophy. We performed whole cord imaging to identify the levels most susceptible to atrophy in patients with MS versus controls and also tested for differences among MS clinical phenotypes.

MATERIALS AND METHODS

Thirty-five patients with MS (2 with CIS, 27 with RRMS, 2 with SPMS, and 4 with PPMS phenotypes) and 27 healthy controls underwent whole cord 3T MR imaging. The spinal cord contour was segmented and assigned to bins representing each C1 to T12 vertebral level. Volumes were normalized, and group comparisons were age-adjusted.

RESULTS

There was a trend toward decreased spinal cord volume at the upper cervical levels in PPMS/SPMS versus controls. A trend toward increased spinal cord volume throughout the cervical and thoracic cord in RRMS/CIS versus controls reached statistical significance at the T10 vertebral level. A statistically significant decrease was found in spinal cord volume at the upper cervical levels in PPMS/SPMS versus RRMS/CIS.

CONCLUSIONS

Opposing pathologic factors impact spinal cord volume measures in MS. Patients with PPMS demonstrated a trend toward upper cervical cord atrophy. However patients with RRMS showed a trend toward increased volume at the cervical and thoracic levels, which most likely reflects inflammation or edema-related cord expansion. With the disease causing both expansion and contraction of the cord, the specificity of spinal cord volume measures for neuroprotective therapeutic effect may be limited.

Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging

BACKGROUND AND PURPOSE

Histopathologic studies have reported widespread cortical lesions in MS; however, in vivo detection by using routinely available pulse sequences is challenging. We investigated the relative frequency and subtypes of cortical lesions and their relationships to white matter lesions and cognitive and physical disability.

MATERIALS AND METHODS

Cortical lesions were identified and classified on the basis of concurrent review of 3D FLAIR and 3D T1-weighted IR-SPGR 3T MR images in 26 patients with MS. Twenty-five patients completed the MACFIMS battery. White matter lesion volume, cortical lesion number, and cortical lesion volume were assessed.

RESULTS

Overall, 249 cortical lesions were detected. Cortical lesions were present in 24/26 patients (92.3%) (range per patient, 0-30; mean, 9.6 ± 8.8). Most (94.4%, n = 235) cortical lesions were classified as mixed cortical-subcortical (type I); the remaining 5.6% (n = 14) were classified as purely intracortical (type II). Subpial cortical lesions (type III) were not detected. White matter lesion volume correlated with cortical lesion number and cortical lesion volume (r(S) = 0.652, r(S) = 0.705, respectively; both P < .001). After controlling for age, depression, and premorbid intelligence, we found that all MR imaging variables (cortical lesion number, cortical lesion volume, white matter lesion volume) correlated with the SDMT score (R(2) = 0.513, R(2) = 0.449, R(2) = 0.418, respectively; P < .014); cortical lesion number also correlated with the CVLT-II scores (R(2) = 0.542-0.461, P < .043). The EDSS scores correlated with cortical lesion number and cortical lesion volume (r(S) = 0.472, r(S) = 0.404, respectively; P < .05), but not with white matter lesion volume.

CONCLUSIONS

Our routinely available imaging method detected many cortical lesions in patients with MS and was useful in their precise topographic characterization in the context of the gray matter-white matter junction. Routinely detectable cortical lesions were related to physical disability and cognitive impairment.

Disease modeling in multiple sclerosis: assessment and quantification of sources of variability in brain parenchymal fraction measurements

The measurement of brain atrophy from magnetic resonance imaging (MRI) has become an established method of estimating disease severity and progression in multiple sclerosis (MS). Most commonly reported in the form of brain parenchymal fraction (BPF), it is more sensitive to the degenerative component of the disease and shows progression more reliably than lesion burden. Typically, the reliability of BPF and other morphometric measurements is assessed by evaluating scan-rescan experiments. While these experiments provide good estimates of real-life error related to imperfect patient repositioning in the MRI scanner, measurement variance due to physiological and reversible pathological fluctuations in brain volume are not taken into account. In this work, we propose a new model for estimating variability in serial morphometry, particularly the BPF measurement. Specifically, we attempt to detect and explicitly model the remaining sources of error to more accurately describe the overall variability in BPF measurements. Our results show that sources of variability beyond subject repositioning error are important and cannot be ignored. We demonstrate that scan-rescan experiments only provide a lower bound on the true error in repeated measurements of patients' BPF. We have estimated the variance due to patient repositioning during scan-rescan (sigma(sr)(2) = 3.0e-06), variance assigned to physiological fluctuations (sigma(p)(2) = 5.74e-06) and the variance associated with lesion activity (sigma(les)(2) = 1.09e-05). These variance components can be used to determine the relative impact of their sources on sample size estimates for studies investigating change over time in MS patients. Our results demonstrate that sample size calculations based exclusively on scan-rescan variability (sigma(sr)) are likely to underestimate the number of patients required. If the physiological variability (sigma(p)) is incorporated in sample size calculations, the required sample size would increase by a factor of 5.69 based on standard t-test sample size calculation.