MWF of the corpus callosum is a robust measure of remyelination: Results from the ReBUILD trial.

Myelin repair is an unrealized therapeutic goal in the treatment of multiple sclerosis (MS). Uncertainty remains about the optimal techniques for assessing therapeutic efficacy and imaging biomarkers are required to measure and corroborate myelin restoration. We analyzed myelin water fraction imaging from ReBUILD, a double-blind, randomized placebo-controlled (delayed treatment) remyelination trial, that showed a significant reduction in VEP latency in patients with MS. We focused on brain regions rich in myelin. Fifty MS subjects in two arms underwent 3T MRI at baseline and months 3 and 5. Half of the cohort was randomly assigned to receive treatment from baseline through 3 mo, whereas the other half received treatment from 3 mo to 5 mo post-baseline. We computed myelin water fraction changes occurring in normal-appearing white matter of corpus callosum, optic radiations, and corticospinal tracts. An increase in myelin water fraction was documented in the normal-appearing white matter of the corpus callosum, in correspondence with the administration of the remyelinating treatment clemastine. This study provides direct, biologically validated imaging-based evidence of medically induced myelin repair. Moreover, our work strongly suggests that significant myelin repair occurs outside of lesions. We therefore propose myelin water fraction within the normal-appearing white matter of the corpus callosum as a biomarker for clinical trials looking at remyelination.

A multicenter pilot study evaluating simplified central vein assessment for the diagnosis of multiple sclerosis.

BACKGROUND: The central vein sign (CVS) is a proposed magnetic resonance imaging (MRI) biomarker for multiple sclerosis (MS); the optimal method for abbreviated CVS scoring is not yet established. OBJECTIVE: The aim of this study was to evaluate the performance of a simplified approach to CVS assessment in a multicenter study of patients being evaluated for suspected MS. METHODS: Adults referred for possible MS to 10 sites were recruited. A post-Gd 3D T2*-weighted MRI sequence (FLAIR*) was obtained in each subject. Trained raters at each site identified up to six CVS-positive lesions per FLAIR* scan. Diagnostic performance of CVS was evaluated for a diagnosis of MS which had been confirmed using the 2017 McDonald criteria at thresholds including three positive lesions (Select-3*) and six positive lesions (Select-6*). Inter-rater reliability assessments were performed. RESULTS: Overall, 78 participants were analyzed; 37 (47%) were diagnosed with MS, and 41 (53%) were not. The mean age of participants was 45 (range: 19-64) years, and most were female (n = 55, 71%). The area under the receiver operating characteristic curve (AUROC) for the simplified counting method was 0.83 (95% CI: 0.73-0.93). Select-3* and Select-6* had sensitivity of 81% and 65% and specificity of 68% and 98%, respectively. Inter-rater agreement was 78% for Select-3* and 83% for Select-6*. CONCLUSION: A simplified method for CVS assessment in patients referred for suspected MS demonstrated good diagnostic performance and inter-rater agreement.

Diagnostic performance of central vein sign versus oligoclonal bands for multiple sclerosis.

BACKGROUND: Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy. OBJECTIVES: The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS. METHODS: Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months. RESULTS: Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status. DISCUSSION: Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB.

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 2022;91:268-281.

Susceptibility-based imaging aids accurate distinction of pediatric-onset MS from myelin oligodendrocyte glycoprotein antibody-associated disease.

BACKGROUND: Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) and pediatric-onset multiple sclerosis (POMS) share clinical and magnetic resonance imaging (MRI) features but differ in prognosis and management. Early POMS diagnosis is essential to avoid disability accumulation. Central vein sign (CVS), paramagnetic rim lesions (PRLs), and central core lesions (CCLs) are susceptibility-based imaging (SbI)-related signs understudied in pediatric populations that may help discerning POMS from MOGAD. METHODS: T2-FLAIR and SbI (three-dimensional echoplanar imaging (3D-EPI)/susceptibility-weighted imaging (SWI) or similar) were acquired on 1.5T/3T scanners. Two readers assessed CVS-positive rate (%CVS+), and their average score was used to build a receiver operator curve (ROC) assessing the ability to discriminate disease type. PRLs and CCLs were identified using a consensual approach. RESULTS: The %CVS+ distinguished 26 POMS cases (mean age 13.7 years, 63% females, median EDSS 1.5) from 14 MOGAD cases (10.8 years, 35% females, EDSS 1.0) with ROC = 1, p < 0.0001, (cutoff 41%). PRLs were only detectable in POMS participants (mean 2.1±2.3, range 1-10), discriminating the two conditions with a sensitivity of 69% and a specificity of 100%. CCLs were more sensitive (81%) but less specific (71.43%). CONCLUSION: The %CVS+ and PRLs are highly specific markers of POMS. After proper validation on larger multicenter cohorts, consideration should be given to including such imaging markers for diagnosing POMS at disease onset.

Association of daily physical activity with brain volumes and cervical spinal cord areas in multiple sclerosis.

BACKGROUND: Remote activity monitoring has the potential to evaluate real-world, motor function, and disability at home. The relationships of daily physical activity with spinal cord white matter and gray matter (GM) areas, multiple sclerosis (MS) disability and leg function, are unknown. OBJECTIVE: Evaluate the association of structural central nervous system pathology with ambulatory disability. METHODS: Fifty adults with progressive or relapsing MS with motor disability who could walk >2 minutes were assessed using clinician-evaluated, patient-reported outcomes, and quantitative brain and spinal cord magnetic resonance imaging (MRI) measures. Fitbit Flex2, worn on the non-dominant wrist, remotely assessed activity over 30 days. Univariate and multivariate analyses were performed to assess correlations between physical activity and other disability metrics. RESULTS: Mean age was 53.3 years and median Expanded Disability Status Scale (EDSS) was 4.0. Average daily step counts (STEPS) were highly correlated with EDSS and walking measures. Greater STEPS were significantly correlated with greater C2-C3 spinal cord GM areas (ρ = 0.39, p = 0.04), total cord area (TCA; ρ = 0.35, p = 0.04), and cortical GM volume (ρ = 0.32, p = 0.04). CONCLUSION: These results provide preliminary evidence that spinal cord GM area is a neuroanatomical substrate associated with STEPS. STEPS could serve as a proxy to alert clinicians and researchers to possible changes in structural nervous system pathology.

Effect of GBCA Use on Detection and Diagnostic Performance of the Central Vein Sign: Evaluation Using a 3-T FLAIR* Sequence in Patients With Suspected Multiple Sclerosis.

BACKGROUND. The central vein sign (CVS) is a proposed MRI biomarker of multiple sclerosis (MS). The impact of gadolinium-based contrast agent (GBCA) administration on CVS evaluation remains poorly investigated. OBJECTIVE. The purpose of this study was to assess the effect of GBCA use on CVS detection and on the diagnostic performance of the CVS for MS using a 3-T FLAIR* sequence. METHODS. This study was a secondary analysis of data from the pilot study for the prospective multicenter Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS), which recruited adults with suspected MS from April 2018 to February 2020. Participants underwent 3-T brain MRI including FLAIR and precontrast and post-contrast echo-planar imaging T2*-weighted acquisitions. Postprocessing was used to generate combined FLAIR and T2*-weighted images (hereafter, FLAIR*). MS diagnoses were established using the 2017 McDonald criteria. Thirty participants (23 women, seven men; mean age, 45 years) were randomly selected from the CAVS-MS pilot study cohort. White matter lesions (WMLs) were marked using FLAIR* images. A single observer, blinded to clinical data and GBCA use, reviewed marked WMLs on FLAIR* images for the presence of the CVS. RESULTS. Thirteen of 30 participants had MS. Across participants, on precontrast FLAIR* imaging, 218 CVS-positive and 517 CVS-negative WMLs were identified; on post-contrast FLAIR* imaging, 269 CVS-positive and 459 CVS-negative WMLs were identified. The fraction of WMLs that were CVS-positive on precontrast and postcontrast images was 48% and 58% in participants with MS and 7% and 10% in participants without MS, respectively. The median patient-level CVS-positivity rate on precontrast and postcontrast images was 43% and 67% for participants with MS and 4% and 8% for participants without MS, respectively. In a binomial model adjusting for MS diagnoses, GBCA use was associated with an increased likelihood of at least one CVS-positive WML (odds ratio, 1.6; p < .001). At a 40% CVS-positivity threshold, the sensitivity of the CVS for MS increased from 62% on precontrast images to 92% on postcontrast images (p = .046). Specificity was not significantly different between precontrast (88%) and postcontrast (82%) images (p = .32). CONCLUSION. GBCA use increased CVS detection on FLAIR* images, thereby increasing the sensitivity of the CVS for MS diagnoses. CLINICAL IMPACT. The postcontrast FLAIR* sequence should be considered for CVS evaluation in future investigational trials and clinical practice.

Silent progression in disease activity-free relapsing multiple sclerosis.

OBJECTIVE: Rates 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. METHODS: Disability 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. RESULTS: Relapses 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). INTERPRETATION: Long-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.

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

BACKGROUND: In vivo quantification of spinal cord atrophy in neurological diseases using MRI has attracted increasing attention. PURPOSE: To compare across different platforms the most promising imaging techniques to assess human spinal cord atrophy. STUDY TYPE: Test/retest multiscanner study. SUBJECTS: Twelve healthy volunteers. FIELD STRENGTH/SEQUENCE: Three different 3T scanner platforms (Siemens, Philips, and GE) / optimized phase sensitive inversion recovery (PSIR), T1 -weighted (T1 -w), and T2 *-weighted (T2 *-w) protocols. ASSESSMENT: On 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 TESTS: Coefficient of variation (COV); intraclass correlation coefficient (ICC); mixed effect models; analysis of variance (t-tests). RESULTS: For 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 CONCLUSION: The present work sets reference values for the magnitude of the contribution of different effects to cord area measurement intra- and interscanner variability. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:1078-1090.

Multisite reliability and repeatability of an advanced brain MRI protocol.

BACKGROUND: MRI is the imaging modality of choice for diagnosis and intervention assessment in neurological disease. Its full potential has not been realized due in part to challenges in harmonizing advanced techniques across multiple sites. PURPOSE: To develop a method for the assessment of reliability and repeatability of advanced multisite-multisession neuroimaging studies and specifically to assess the reliability of an advanced MRI protocol, including multiband fMRI and diffusion tensor MRI, in a multisite setting. STUDY TYPE: Prospective. POPULATION: Twice repeated measurement of a single subject with stable relapsing-remitting multiple sclerosis (MS) at seven institutions. FIELD STRENGTH/SEQUENCE: A 3 T MRI protocol included higher spatial resolution anatomical scans, a variable flip-angle longitudinal relaxation rate constant (R1 ≡ 1/T1 ) measurement, quantitative magnetization transfer imaging, diffusion tensor imaging, and a resting-state fMRI (rsFMRI) series. ASSESSMENT: Multiple methods of assessing intrasite repeatability and intersite reliability were evaluated for imaging metrics derived from each sequence. STATISTICAL TESTS: Student's t-test, Pearson's r, and intraclass correlation coefficient (ICC) (2,1) were employed to assess repeatability and reliability. Two new statistical metrics are introduced that frame reliability and repeatability in the respective units of the measurements themselves. RESULTS: Intrasite repeatability was excellent for quantitative R1 , magnetization transfer ratio (MTR), and diffusion-weighted imaging (DWI) based metrics (r > 0.95). rsFMRI metrics were less repeatable (r = 0.8). Intersite reliability was excellent for R1 , MTR, and DWI (ICC >0.9), and moderate for rsFMRI metrics (ICC∼0.4). DATA CONCLUSION: From most reliable to least, using a new reliability metric introduced here, MTR > R1 > DWI > rsFMRI; for repeatability, MTR > DWI > R1 > rsFMRI. A graphical method for at-a-glance assessment of reliability and repeatability, effect sizes, and outlier identification in multisite-multisession neuroimaging studies is introduced. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:878-888.

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

PURPOSE: 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. METHODS: A multiple sclerosis patient was scanned at seven sites using 3T MRI scanners with the same 3D T1 -weighted protocol without GNL-distortion correction. Two healthy subjects and a phantom were additionally scanned at a single site with varying table positions. The 2D and 3D vendor-implemented GNL-correction algorithms and retrospective methods based on (i) phantom data fit, (ii) normalization with C2 vertebral body diameters, and (iii) the Jacobian determinant of nonlinear registrations to a template were tested. RESULTS: Depending on the positioning of the subject, GNL introduced up to 15% variability in UCCA measurements from volumetric brain T1 -weighted scans when no distortion corrections were used. The 3D vendor-implemented correction methods and the three proposed methods reduced this variability to less than 3%. CONCLUSIONS: Our results raise awareness of the significant impact that GNL can have on quantitative UCCA studies, and point the way to prospectively and retrospectively managing GNL distortions in a variety of settings, including clinical environments. Magn Reson Med 79:1595-1601, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

The NAIMS cooperative pilot project: Design, implementation and future directions.

The North American Imaging in Multiple Sclerosis (NAIMS) Cooperative represents a network of 27 academic centers focused on accelerating the pace of magnetic resonance imaging (MRI) research in multiple sclerosis (MS) through idea exchange and collaboration. Recently, NAIMS completed its first project evaluating the feasibility of implementation and reproducibility of quantitative MRI measures derived from scanning a single MS patient using a high-resolution 3T protocol at seven sites. The results showed the feasibility of utilizing advanced quantitative MRI measures in multicenter studies and demonstrated the importance of careful standardization of scanning protocols, central image processing, and strategies to account for inter-site variability.

Gray matter segmentation of the spinal cord with active contours in MR images.

OBJECTIVE: Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. METHODS: The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. RESULTS: Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. CONCLUSION: We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols.

Spinal cord grey matter segmentation challenge.

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication.

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

OBJECTIVE: 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. METHODS: This is a prospective study of 517 actively managed MS patients enrolled at a single center. RESULTS: More than 91% of patients were retained, with data ascertained up to 10 years after the baseline visit. At this last assessment, neurologic disability as measured by the Expanded Disability Status Scale (EDSS) was stable or improved compared to baseline in 41% of patients. Subjects with no evidence of disease activity (NEDA) by clinical and MRI criteria during the first 2 years had long-term outcomes that were no different from those of the cohort as a whole. 25-OH vitamin D serum levels were inversely associated with short-term MS disease activity; however, these levels had no association with long-term disability. At a median time of 16.8 years after disease onset, 10.7% (95% confidence interval [CI] = 7.2-14%) of patients reached an EDSS ≥ 6, and 18.1% (95% CI = 13.5-22.5%) evolved from relapsing MS to secondary progressive MS (SPMS). INTERPRETATION: Rates of worsening and evolution to SPMS were substantially lower when compared to earlier natural history studies. Notably, the NEDA 2-year endpoint was not a predictor of long-term stability. Finally, the data call into question the utility of annual MRI assessments as a treat-to-target approach for MS care. Ann Neurol 2016;80:499-510.

Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes.

Adrenomyeloneuropathy is the late-onset form of X-linked adrenoleukodystrophy, and is considered the most frequent metabolic hereditary spastic paraplegia. In adrenomyeloneuropathy the spinal cord is the main site of pathology. Differently from quantitative magnetic resonance imaging of the brain, little is known about the feasibility and utility of advanced neuroimaging in quantifying the spinal cord abnormalities in hereditary diseases. Moreover, little is known about the subtle pathological changes that can characterize the brain of adrenomyeloneuropathy subjects in the early stages of the disease. We performed a cross-sectional study on 13 patients with adrenomyeloneuropathy and 12 age-matched healthy control subjects who underwent quantitative magnetic resonance imaging to assess the structural changes of the upper spinal cord and brain. Total cord areas from C2-3 to T2-3 level were measured, and diffusion tensor imaging metrics, i.e. fractional anisotropy, mean, axial and radial diffusivity values were calculated in both grey and white matter of spinal cord. In the brain, grey matter regions were parcellated with Freesurfer and average volume and thickness, and mean diffusivity and fractional anisotropy from co-registered diffusion maps were calculated in each region. Brain white matter diffusion tensor imaging metrics were assessed using whole-brain tract-based spatial statistics, and tractography-based analysis on corticospinal tracts. Correlations among clinical, structural and diffusion tensor imaging measures were calculated. In patients total cord area was reduced by 26.3% to 40.2% at all tested levels (P < 0.0001). A mean 16% reduction of spinal cord white matter fractional anisotropy (P ≤ 0.0003) with a concomitant 9.7% axial diffusivity reduction (P < 0.009) and 34.5% radial diffusivity increase (P < 0.009) was observed, suggesting co-presence of axonal degeneration and demyelination. Brain tract-based spatial statistics showed a marked reduction of fractional anisotropy, increase of radial diffusivity (P < 0.001) and no axial diffusivity changes in several white matter tracts, including corticospinal tracts and optic radiations, indicating predominant demyelination. Tractography-based analysis confirmed the results within corticospinal tracts. No significant cortical volume and thickness reduction or grey matter diffusion tensor imaging values alterations were observed in patients. A correlation between radial diffusivity and disease duration along the corticospinal tracts (r = 0.806, P < 0.01) was found. In conclusion, in adrenomyeloneuropathy patients quantitative magnetic resonance imaging-derived measures identify and quantify structural changes in the upper spinal cord and brain which agree with the expected histopathology, and suggest that the disease could be primarily caused by a demyelination rather than a primitive axonal damage. The results of this study may also encourage the employment of quantitative magnetic resonance imaging in other hereditary diseases with spinal cord involvement.

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 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.

Structural connectivity of the human anterior temporal lobe: A diffusion magnetic resonance imaging study.

The anterior temporal lobes (ATL) have been implicated in a range of cognitive functions including auditory and visual perception, language, semantic knowledge, and social-emotional processing. However, the anatomical relationships between the ATLs and the broader cortical networks that subserve these functions have not been fully elucidated. Using diffusion tensor imaging (DTI) and probabilistic tractography, we tested the hypothesis that functional segregation of information in the ATLs is reflected by distinct patterns of structural connectivity to regions outside the ATLs. We performed a parcellation of the ATLs bilaterally based on the degree of connectivity of each voxel with eight ipsilateral target regions known to be involved in various cognitive networks. Six discrete segments within each ATL showed preferential connectivity to one of the ipsilateral target regions, via four major fiber tracts (uncinate, inferior longitudinal, middle longitudinal, and arcuate fasciculi). Two noteworthy interhemispheric differences were observed: connections between the ATL and orbito-frontal areas were stronger in the right hemisphere, while the consistency of the connection between the ATL and the inferior frontal gyrus through the arcuate fasciculus was greater in the left hemisphere. Our findings support the hypothesis that distinct regions within the ATLs have anatomical connections to different cognitive networks. Hum Brain Mapp 37:2210-2222, 2016. © 2016 Wiley Periodicals, Inc.

Retrospective head motion correction approaches for diffusion tensor imaging: Effects of preprocessing choices on biases and reproducibility of scalar diffusion metrics.

PURPOSE: To evaluate how retrospective head motion correction strategies affect the estimation of scalar metrics commonly used in clinical diffusion tensor imaging (DTI) studies along with their across-session reproducibility errors. MATERIALS AND METHODS: Fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and their respective across-session reproducibility errors were measured on a 4T test-retest dataset of healthy participants using five processing pipelines. These differed in: 1) the number of b0 volumes used for motion correction reference (one or five); 2) the estimations of the gradient matrix rotation (based on 6 or 12 degrees of freedom derived from coregistration); and 3) the software packages used (FSL or DTIPrep). Biases and reproducibility were evaluated in three regions of interest (ROIs) (bilateral arcuate fasciculi, cingula, and the corpus callosum) and also at the full brain level with tract based skeleton images. RESULTS: Preprocessing choices affected DTI measures and their reproducibility. The DTIPrep pipeline exhibited higher DTI metrics: FA/MD and AD (P < 0.05) relative to FSL pipelines both at the ROI and full brain level, and lower RD estimates (P < 0.05) at the ROI level. Within FSL pipelines no such effects were found (P-values ranging between 0.25 and 0.97). The DTIPrep pipeline showed the highest number of white matter skeleton voxels, with significantly higher reproducibility (P < 0.001) relative to the other pipelines (tested on P < 0.01 uncorrected maps). CONCLUSION: The use of an iteratively averaged b0 image as motion correction reference (as performed by DTIPrep) affects both scalar values and improves test-retest reliability relative to the other tested pipelines. These considerations are potentially relevant for data analysis in longitudinal DTI studies.