William A. Stern

Spinal Cord Gray Matter Atrophy Correlates with Multiple Sclerosis Disability

In multiple sclerosis (MS), cerebral gray matter (GM) atrophy correlates more strongly than white matter (WM) atrophy with disability. The corresponding relationships in the spinal cord (SC) are unknown due to technical limitations in assessing SC GM atrophy. Using phase‐sensitive inversion recovery (PSIR) magnetic resonance imaging, we determined the association of the SC GM and SC WM areas with MS disability and disease type.

Spinal cord gray matter atrophy correlates with multiple sclerosis disability - eScholarship

In multiple sclerosis (MS), cerebral gray matter (GM) atrophy correlates more strongly than white matter (WM) atrophy with disability. The corresponding relationships in the spinal cord (SC) are unknown due to technical limitations in assessing SC GM atrophy. Using phase‐sensitive inversion recovery (PSIR) magnetic resonance imaging, we determined the association of the SC GM and SC WM areas with MS disability and disease type.

Long-term evolution of multiple sclerosis disability in the treatment era.

To characterize the accrual of long‐term disability in a cohort of actively treated multiple sclerosis (MS) patients and to assess whether clinical and magnetic resonance imaging (MRI) data used in clinical trials have long‐term prognostic value.

Association between thoracic spinal cord gray matter atrophy and disability in multiple sclerosis

IMPORTANCE In multiple sclerosis (MS), upper cervical cord gray matter (GM) atrophy correlates more strongly with disability than does brain or cord white matter (WM) atrophy. The corresponding relationships in the thoracic cord are unknown owing to technical difficulties in assessing GM and WM compartments by conventional magnetic resonance imaging techniques. OBJECTIVES To investigate the associations between MS disability and disease type with lower thoracic cord GM and WM areas using phase-sensitive inversion recovery magnetic resonance imaging at 3 T, as well as to compare these relationships with those obtained at upper cervical levels. DESIGN, SETTING, AND PARTICIPANTS Between July 2013 and March 2014, a total of 142 patients with MS (aged 25-75 years; 86 women) and 20 healthy control individuals were included in this cross-sectional observational study conducted at an academic university hospital. MAIN OUTCOMES AND MEASURES Total cord areas (TCAs), GM areas, and WM areas at the disc levels C2/C3, C3/C4, T8/9, and T9/10. Area differences between groups were assessed, with age and sex as covariates. RESULTS Patients with relapsing MS (RMS) had smaller thoracic cord GM areas than did age- and sex-matched control individuals (mean differences [coefficient of variation (COV)]: 0.98 mm2 [9.2%]; P = .003 at T8/T9 and 0.93 mm2 [8.0%]; P = .01 at T9/T10); however, there were no significant differences in either the WM area or TCA. Patients with progressive MS showed smaller GM areas (mean differences [COV]: 1.02 mm2 [10.6%]; P < .001 at T8/T9 and 1.37 mm2 [13.2%]; P < .001 at T9/T10) and TCAs (mean differences [COV]: 3.66 mm2 [9.0%]; P < .001 at T8/T9 and 3.04 mm2 [7.2%]; P = .004 at T9/T10) compared with patients with RMS. All measurements (GM, WM, and TCA) were inversely correlated with Expanded Disability Status Scale score. Thoracic cord GM areas were correlated with lower limb function. In multivariable models (which also included cord WM areas and T2 lesion number, brain WM volumes, brain T1 and fluid-attenuated inversion recovery lesion loads, age, sex, and disease duration), cervical cord GM areas had the strongest correlation with Expanded Disability Status Scale score followed by thoracic cord GM area and brain GM volume. CONCLUSIONS AND RELEVANCE Thoracic cord GM atrophy can be detected in vivo in the absence of WM atrophy in RMS. This atrophy is more pronounced in progressive MS than RMS and correlates with disability and lower limb function. Our results indicate that remarkable cord GM atrophy is present at multiple cervical and lower thoracic levels and, therefore, may reflect widespread cord GM degeneration.

Age, gender and normalization covariates for spinal cord gray matter and total cross-sectional areas at cervical and thoracic levels: A 2D phase sensitive inversion recovery imaging study

The source of inter-subject variability and the influence of age and gender on morphometric characteristics of the spinal cord, such as the total cross-sectional area (TCA), the gray matter (GM) and white matter (WM) areas, currently remain under investigation. Understanding the effect of covariates such as age, gender, brain volumes, and skull- and vertebra-derived metrics on cervical and thoracic spinal cord TCA and GM areas in healthy subjects would be fundamental for exploring compartment specific changes in neurological diseases affecting the spinal cord. Using Magnetic Resonance Imaging at 3T we investigated 32 healthy subjects using a 2D phase sensitive inversion recovery sequence and we measured TCA, GM and WM areas at 4 cervical and thoracic levels of the spinal cord. We assessed age and gender relationships of cord measures and explored associations between cord measures and a) brain volumes and b) skull- and vertebra-derived metrics. Age and gender had a significant effect on TCA, WM and GM areas (with women and elderly having smaller values than men and younger people respectively), but not on the GM area/TCA ratio. The total intracranial volume and C3 vertebra dimensions showed the highest correlations with cord measures. When used in multi-regression models, they reduced cord areas group variability by approximately a third. Age and gender influences on cord measures and normalization strategies here presented might be of use in the study of compartment specific changes in various neurological diseases affecting the spinal cord.

Power estimation for non-standardized multisite studies

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfers segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

2D phase‐sensitive inversion recovery imaging to measure in vivo spinal cord gray and white matter areas in clinically feasible acquisition times

To present and assess a procedure for measurement of spinal cord total cross‐sectional areas (TCA) and gray matter (GM) areas based on phase‐sensitive inversion recovery imaging (PSIR). In vivo assessment of spinal cord GM and white matter (WM) could become pivotal to study various neurological diseases, but it is challenging because of insufficient GM/WM contrast provided by conventional magnetic resonance imaging (MRI).

Volumetric Analysis from a Harmonized Multisite Brain MRI Study of a Single Subject with Multiple Sclerosis

The North American Imaging in Multiple Sclerosis Cooperative steering committee developed a uniform high-resolution 3T MR imaging protocol relevant to the quantification of cerebral lesions and atrophy and implemented it at 7 sites across the United States. They assessed intersite variability in scan data, by imaging a volunteer with relapsing-remitting MS with a scan-rescan at each site. In multicenter studies with consistent scanner field strength and manufacturer after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses. BACKGROUND AND PURPOSE: MR imaging can be used to measure structural changes in the brains of individuals with multiple sclerosis and is essential for diagnosis, longitudinal monitoring, and therapy evaluation. The North American Imaging in Multiple Sclerosis Cooperative steering committee developed a uniform high-resolution 3T MR imaging protocol relevant to the quantification of cerebral lesions and atrophy and implemented it at 7 sites across the United States. To assess intersite variability in scan data, we imaged a volunteer with relapsing-remitting MS with a scan-rescan at each site. MATERIALS AND METHODS: All imaging was acquired on Siemens scanners (4 Skyra, 2 Tim Trio, and 1 Verio). Expert segmentations were manually obtained for T1-hypointense and T2 (FLAIR) hyperintense lesions. Several automated lesion-detection and whole-brain, cortical, and deep gray matter volumetric pipelines were applied. Statistical analyses were conducted to assess variability across sites, as well as systematic biases in the volumetric measurements that were site-related. RESULTS: Systematic biases due to site differences in expert-traced lesion measurements were significant (P < .01 for both T1 and T2 lesion volumes), with site explaining >90% of the variation (range, 13.0–16.4 mL in T1 and 15.9–20.1 mL in T2) in lesion volumes. Site also explained >80% of the variation in most automated volumetric measurements. Output measures clustered according to scanner models, with similar results from the Skyra versus the other 2 units. CONCLUSIONS: Even in multicenter studies with consistent scanner field strength and manufacturer after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses.

Gradient nonlinearity effects on upper cervical spinal cord area measurement from 3D T1‐weighted brain MRI acquisitions

To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T1‐weighted scans related to gradient nonlinearity (GNL) and subject positioning; (ii) the effect of vendor‐implemented GNL corrections; and (iii) easily applicable methods that can be used to retrospectively correct data.

An Automated Statistical Technique for Counting Distinct Multiple Sclerosis Lesions

BACKGROUND AND PURPOSE: Lesion load is a common biomarker in multiple sclerosis, yet it has historically shown modest association with clinical outcome. Lesion count, which encapsulates the natural history of lesion formation and is thought to provide complementary information, is difficult to assess in patients with confluent (ie, spatially overlapping) lesions. We introduce a statistical technique for cross-sectionally counting pathologically distinct lesions. MATERIALS AND METHODS: MR imaging was used to assess the probability of a lesion at each location. The texture of this map was quantified using a novel technique, and clusters resembling the center of a lesion were counted. Validity compared with a criterion standard count was demonstrated in 60 subjects observed longitudinally, and reliability was determined using 14 scans of a clinically stable subject acquired at 7 sites. RESULTS: The proposed count and the criterion standard count were highly correlated (r = 0.97, P < .001) and not significantly different (t59 = −.83, P = .41), and the variability of the proposed count across repeat scans was equivalent to that of lesion load. After accounting for lesion load and age, lesion count was negatively associated (t58 = −2.73, P < .01) with the Expanded Disability Status Scale. Average lesion size had a higher association with the Expanded Disability Status Scale (r = 0.35, P < .01) than lesion load (r = 0.10, P = .44) or lesion count (r = −.12, P = .36) alone. CONCLUSIONS: This study introduces a novel technique for counting pathologically distinct lesions using cross-sectional data and demonstrates its ability to recover obscured longitudinal information. The proposed count allows more accurate estimation of lesion size, which correlated more closely with disability scores than either lesion load or lesion count alone.