Intensity warping for multisite MRI harmonization.

In multisite neuroimaging studies there is often unwanted technical variation across scanners and sites. These "scanner effects" can hinder detection of biological features of interest, produce inconsistent results, and lead to spurious associations. We propose mica (multisite image harmonization by cumulative distribution function alignment), a tool to harmonize images taken on different scanners by identifying and removing within-subject scanner effects. Our goals in the present study were to (1) establish a method that removes scanner effects by leveraging multiple scans collected on the same subject, and, building on this, (2) develop a technique to quantify scanner effects in large multisite studies so these can be reduced as a preprocessing step. We illustrate scanner effects in a brain MRI study in which the same subject was measured twice on seven scanners, and assess our method's performance in a second study in which ten subjects were scanned on two machines. We found that unharmonized images were highly variable across site and scanner type, and our method effectively removed this variability by aligning intensity distributions. We further studied the ability to predict image harmonization results for a scan taken on an existing subject at a new site using cross-validation.

Central vein sign: A diagnostic biomarker in multiple sclerosis (CAVS-MS) study protocol for a prospective multicenter trial.

The specificity and implementation of current MRI-based diagnostic criteria for multiple sclerosis (MS) are imperfect. Approximately 1 in 5 of individuals diagnosed with MS are eventually determined not to have the disease, with overreliance on MRI findings a major cause of MS misdiagnosis. The central vein sign (CVS), a proposed MRI biomarker for MS lesions, has been extensively studied in numerous cross sectional studies and may increase diagnostic specificity for MS. CVS has desirable analytical, measurement, and scalability properties. "Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS)" is an NIH-supported, 2-year, prospective, international, multicenter study conducted by the North American Imaging in MS Cooperative (NAIMS) to evaluate CVS as a diagnostic biomarker for immediate translation into clinical care. Study objectives include determining the concordance of CVS and McDonald Criteria to diagnose MS, the sensitivity of CVS to detect MS in those with typical presentations, and the specificity of CVS among those with atypical presentations. The study will recruit a total of 400 participants (200 with typical and 200 with atypical presentations) across 11 sites. T2*-weighted, high-isotropic-resolution, segmented echo-planar MRI will be acquired at baseline and 24 months on 3-tesla scanners, and FLAIR* images (combination of FLAIR and T2*) will be generated for evaluating CVS. Data will be processed on a cloud-based platform that contains clinical and CVS rating modules. Imaging quality control will be conducted by automated methods and neuroradiologist review. CVS will be determined by Select6* and Select3* lesion methods following published criteria at each site and by central readers, including neurologists and neuroradiologists. Automated CVS detection and algorithms for incorporation of CVS into McDonald Criteria will be tested. Diagnosis will be adjudicated by three neurologists who served on the 2017 International Panel on the Diagnosis of MS. The CAVS-MS study aims to definitively establish CVS as a diagnostic biomarker that can be applied broadly to individuals presenting for evaluation of the diagnosis of MS.

Regional hippocampal atrophy in multiple sclerosis.

Gray matter brain structures, including deep nuclei and the cerebral cortex, are affected significantly and early in the course of multiple sclerosis and these changes may not be directly related to demyelinating white matter lesions. The hippocampus is an archicortical structure that is critical for memory functions and is especially sensitive to multiple insults including inflammation. We used high-resolution MR imaging at 3.0 T to measure hippocampal volumes in relapsing remitting MS (RRMS) and secondary progressive MS (SPMS) patients and controls. We found that both groups of MS patients had hippocampal atrophy and that this volume loss was in excess of global brain atrophy. Subregional analysis revealed selective volume loss in the cornu ammonis (CA) 1 region of the hippocampus in RRMS with further worsening of CA1 loss and extension into other CA regions in SPMS. Hippocampal atrophy was not correlated with T2-lesion volumes, and right and left hippocampi were affected equally. Volume loss in the hippocampus and subregions was correlated with worsening performance on word-list learning, a task requiring memory encoding, but not with performance on the Paced Auditory Serial Addition Task (PASAT), a test of information processing speed. Our findings provide evidence for selective and progressive hippocampal atrophy in MS localized initially to the CA1 subregion that is associated with deficits in memory encoding and retrieval. The underlying histopathological substrate for this selective, symmetric and disproportionate regional hippocampal vulnerability remains speculative at this time. Further understanding of this process could provide targets for therapeutic interventions including neuroprotective treatments.

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.

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

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.

Onset of multiple sclerosis associated with anti-TNF therapy.

Therapies aimed at inhibiting tumor necrosis factor (TNF), a proinflammatory cytokine implicated in autoimmune disease are effective, especially for rheumatoid arthritis. We report a patient with new onset MS closely associated with the initiation of anti-TNF therapy for juvenile rheumatoid arthritis. It is possible that the inhibition of TNF triggered MS in this individual.

Optical imaging of bilingual cortical representations. Case report.

The organization of language in the brains of multilingual persons remains controversial. The authors investigated language representations in a proficient bilingual patient by using a novel neuroimaging technique, intraoperative optical imaging of intrinsic signals (iOIS), and a visual object naming task. The results indicate that there are cortical areas that are activated by the use of both English and Spanish languages (superior temporal sulcus, superior and middle temporal gyri, and parts of the supramarginal gyrus). In addition, language-specific areas were identified in the supramarginal (Spanish) and precentral (English) gyri. These results suggest that cortical language representations in bilingual persons may consist of both overlapping and distinct components. Furthermore, this study demonstrates the utility of iOIS in detecting topographical segregation of cognitively distinct cortices.

A longitudinal fMRI study of the paced auditory serial addition task.

The paced auditory serial addition task (PASAT) is a test of working memory and attention that is frequently abnormal in MS and is used serially to assess cognitive dysfunction as part of the MS Functional Composite in clinical trials. Previous studies using functional MRI (fMRI) during PASAT performance have shown significant differences in activation patterns between healthy controls and MS patients matched for performance, but serial fMRI measures have not been reported. A confound is that learning effects are common with repeated PASAT testing, diminishing over successive trials. After measuring PASAT performance weekly for four weeks in 10 healthy controls to eliminate practice effects, we assessed brain activity using fMRI at baseline and after six months to determine the reproducibility of activation patterns in healthy controls during PASAT performance. Results showed that scores improved during the first three testing trials and stabilized subsequently. Brain activation during PASAT performance was seen in left frontal and parietal regions consistent with previous reports. After a six-month interval, PASAT performance and fMRI activity were stable, suggesting that serial fMRI during PASAT performance could be used as an outcome measure in trials assessing cognitive decline in clinical populations once practice effects are eliminated.

Diffusion tensor MRI shows abnormal brainstem crossing fibers associated with ROBO3 mutations.

Horizontal gaze palsy with progressive scoliosis (HGPPS) is caused by mutations in the ROBO3 gene, critical for the crossing of long ascending medial lemniscal and descending corticospinal tracts in the medulla. Diffusion tensor imaging in a patient with HGGPS revealed the absence of major pontine crossing fiber tracts and no decussation of the superior cerebellar peduncles. Mutations in the ROBO3 gene lead to a widespread lack of crossing fibers throughout the brainstem.

Handedness in twins: a meta-analysis.

In the largest meta-analysis of twins and singletons conducted to date we have found a higher incidence of left-handedness in twins compared to singletons. Our analysis revealed no difference in the frequency of left-handedness among monozygotic versus dizygotic twins. However, identical twins were more likely to be concordant for hand preference than non-identical twins, which is consistent with a genetic model of handedness. Prior analyses have not revealed these findings consistently, and this has led to a number of conflicting models of handedness.

Creation and use of a Talairach-compatible atlas for accurate, automated, nonlinear intersubject registration, and analysis of functional imaging data.

Spatial normalization in functional imaging can encompass various processes, including nonlinear warping to correct for intersubject differences, linear transformations to correct for identifiable head movements, and data detrending to remove residual motion correlated artifacts. We describe the use of AIR to create a custom, site-specific, normal averaged brain atlas that can be used to map T2 weighted echo-planar images and coplanar functional images directly into a Talairach-compatible space. We also discuss extraction of characteristic descriptors from sets of linear transformation matrices describing head movements in a functional imaging series. Scores for these descriptors, derived using principal components analysis with singular value decomposition, can be treated as confounds associated with each individual image in the series and systematically removed prior to voxel-by-voxel statistical analysis.

Automated image registration: II. Intersubject validation of linear and nonlinear models.

PURPOSE: Our goal was to validate linear and nonlinear intersubject image registration using an automated method (AIR 3.0) based on voxel intensity. METHOD: PET and MRI data from 22 normal subjects were registered to corresponding averaged PET or MRI brain atlases using several specific linear and nonlinear spatial transformation models with an automated algorithm. Validation was based on anatomically defined landmarks. RESULTS: Automated registration produced results that were superior to a manual nine parameter variant of the Talairach registration method. Increasing the degrees of freedom in the spatial transformation model improved the accuracy of automated intersubject registration. CONCLUSION: Linear or nonlinear automated intersubject registration based on voxel intensities is computationally practical and produces more accurate alignment of homologous landmarks than manual nine parameter Talairach registration. Nonlinear models provide better registration than linear models but are slower.