Evaluation of Intra- and Interscanner Reliability of MRI Protocols for Spinal Cord Gray Matter and Total Cross-Sectional Area Measurements.

BackgroundIn vivo quantification of spinal cord atrophy in neurological diseases using MRI has attracted increasing attention.PurposeTo compare across different platforms the most promising imaging techniques to assess human spinal cord atrophy.Study typeTest/retest multiscanner study.SubjectsTwelve healthy volunteers.Field strength/sequenceThree different 3T scanner platforms (Siemens, Philips, and GE) / optimized phase sensitive inversion recovery (PSIR), T1 -weighted (T1 -w), and T2 *-weighted (T2 *-w) protocols.AssessmentOn all images acquired, two operators assessed contrast-to-noise ratio (CNR) between gray matter (GM) and white matter (WM), and between WM and cerebrospinal fluid (CSF); one experienced operator measured total cross-sectional area (TCA) and GM area using JIM and the Spinal Cord Toolbox (SCT).Statistical testsCoefficient of variation (COV); intraclass correlation coefficient (ICC); mixed effect models; analysis of variance (t-tests).ResultsFor all the scanners, GM/WM CNR was higher for PSIR than T2 *-w (P < 0.0001) and WM/CSF CNR for T1 -w was the highest (P < 0.0001). For TCA, using JIM, median COVs were smaller than 1.5% and ICC >0.95, while using SCT, median COVs were in the range 2.2-2.75% and ICC 0.79-0.95. For GM, despite some failures of the automatic segmentation, median COVs using SCT on T2 *-w were smaller than using JIM manual PSIR segmentations. In the mixed effect models, the subject was always the main contributor to the variance of area measurements and scanner often contributed to TCA variance (P < 0.05). Using JIM, TCA measurements on T2 *-w were different than on PSIR (P = 0.0021) and T1 -w (P = 0.0018), while using SCT, no notable differences were found between T1 -w and T2 *-w (P = 0.18). JIM and SCT-derived TCA were not different on T1 -w (P = 0.66), while they were different for T2 *-w (P < 0.0001). GM area derived using SCT/T2 *-w versus JIM/PSIR were different (P < 0.0001).Data conclusionThe present work sets reference values for the magnitude of the contribution of different effects to cord area measurement intra- and interscanner variability.Level of evidence1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:1078-1090

Simultaneous assessment of regional distributions of atrophy across the neuraxis in MS patients

BACKGROUND: The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution. OBJECTIVE: To test a promising tool to simultaneously map the regional distribution of atrophy in multiple sclerosis (MS) patients across the brain and cord. METHODS: Voxel-based morphometry combined with a statistical parametric mapping probabilistic brain-spinal cord (SPM-BSC) template was applied to standard T1-weighted magnetic resonance imaging (MRI) scans covering the brain and cervical cord from 37 MS patients and 20 healthy controls (HC). We also measured the cord area at C2-C3 with a semi-automatic segmentation method using (i) the same T1-weighted acquisitions used for the new voxel-based analysis and (ii) dedicated spinal cord phase sensitive inversion recovery (PSIR) acquisitions. Cervical cord findings derived from the three approaches were compared to each other and the goodness to fit to clinical scores was assessed by regression analyses. RESULTS: The SPM-BSC approach revealed a severity-dependent pattern of atrophy across the cervical cord and thalamus in MS patients when compared to HCs. The magnitude of cord atrophy was confirmed by the semi-automatic extraction approach at C2-C3 using both standard brain T1-weighted and advanced cord dedicated acquisitions. Associations between atrophy of cord and thalamus with disability and cognition were demonstrated. CONCLUSION: Atrophy in the brain and cervical cord of MS patients can be identified simultaneously and rapidly at the voxel-level. The SPM-BSC approach yields similar results as available standard processing tools with the added advantage of performing the analysis simultaneously and faster

Silent progression in disease activity-free relapsing multiple sclerosis.

ObjectiveRates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow-up. Notably, "no evidence of disease activity" at 2 years did not predict long-term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long-term disability accumulation.MethodsDisability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0-5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA-DRB1*15:01 as covariates.ResultsRelapses were associated with a transient increase in disability over 1-year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p < 0.05).InterpretationLong-term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing-remitting MS. Ann Neurol 2019;85:653-666

Spinal Cord Atrophy Predicts Progressive Disease in Relapsing Multiple Sclerosis

Objective A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS). Methods From a single-center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12-year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion. Results Patients who developed SPMS showed faster cord atrophy rates (-2.19%/yr) at least 4 years before conversion compared to their RRMS matches (-0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (-1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (-1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively. Interpretation Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 202

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Power estimation for non-standardized multisite studies

AbstractA 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 Freesurfer's 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