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Background: Leptomeningeal contrast enhancement (LME) on T2-weighted Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRI is a reported marker of leptomeningeal inflammation, which is known to be associated with progression of multiple sclerosis (MS). However, this MRI approach, as typically implemented on clinical 3-tesla (T) systems, detects only a few enhancing foci in ~25% of patients and has thus been criticized as poorly sensitive., Purpose: To compare an optimized 3D real-reconstruction inversion recovery (Real-IR) MRI sequence on a clinical 3 T scanner to T2-FLAIR for prevalence, characteristics, and clinical/radiological correlations of LME., Materials and Methods: We obtained 3D T2-FLAIR and Real-IR scans before and after administration of standard-dose gadobutrol in 177 scans of 154 participants (98 women, 64%; mean ± SD age: 49 ± 12 years), including 124 with an MS-spectrum diagnosis, 21 with other neurological and/or inflammatory disorders, and 9 without neurological history. We calculated contrast-to-noise ratios (CNR) in 20 representative LME foci and determined association of LME with cortical lesions identified at 7 T (n = 19), paramagnetic rim lesions (PRL) at 3 T (n = 105), and clinical/demographic data., Results: We observed focal LME in 73% of participants on Real-IR (70% in established MS, 33% in healthy volunteers, P < 0.0001), compared to 33% on T2-FLAIR (34% vs. 11%, P = 0.0002). Real-IR showed 3.7-fold more LME foci than T2-FLAIR ( P = 0.001), including all T2-FLAIR foci. LME CNR was 2.5-fold higher by Real-IR ( P < 0.0001). The major determinant of LME status was age. Although LME was not associated with cortical lesions, the number of PRL was associated with the number of LME foci on both T2-FLAIR ( P = 0.003) and Real-IR ( P = 0.0003) after adjusting for age, sex, and white matter lesion volume., Conclusions: Real-IR a promising tool to detect, characterize, and understand the significance of LME in MS. The association between PRL and LME highlights a possible role of the leptomeninges in sustaining chronic inflammation., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Remyelination is crucial to recover from inflammatory demyelination in multiple sclerosis (MS). Investigating remyelination in vivo using magnetic resonance imaging (MRI) is difficult in MS, where collecting serial short-interval scans is challenging. Using experimental autoimmune encephalomyelitis (EAE) in common marmosets, a model of MS that recapitulates focal cerebral inflammatory demyelinating lesions, we investigated whether MRI is sensitive to, and can characterize, remyelination. In six animals followed with multisequence 7 T MRI, 31 focal lesions, predicted to be demyelinated or remyelinated based on signal intensity on proton density-weighted images, were subsequently assessed with histopathology. Remyelination occurred in four of six marmosets and 45% of lesions. Radiological-pathological comparison showed that MRI had high statistical sensitivity (100%) and specificity (90%) for detecting remyelination. This study demonstrates the prevalence of spontaneous remyelination in marmoset EAE and the ability of in vivo MRI to detect it, with implications for preclinical testing of pro-remyelinating agents., Competing Interests: MD, NL, MG, SH, NL, SR, BI, EL, CY, DP, AS, SJ, PS, DR No competing interests declared, MJ is a shareholder and employee of Vertex Pharmaceuticals, Inc

Background: The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied., Objective: Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis., Methods: Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated., Results: CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm 3 , p  = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives)., Conclusion: Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.

Background and Objectives: The central vein sign (CVS), a central linear hypointensity within lesions on T2*-weighted imaging, has been established as a sensitive and specific biomarker for the diagnosis of multiple sclerosis (MS). However, the CVS has not yet been comprehensively studied in newly developing MS lesions. We aimed to identify the CVS profiles of new white matter lesions in patients with MS followed over time and investigate demographic and clinical risk factors associated with new CVS+ or CVS- lesion development., Methods: In this retrospective longitudinal cohort study, adults from the NIH MS Natural History Study were considered for inclusion. Participants with new T2 or enhancing lesions were identified through review of the radiology report and/or longitudinal subtraction imaging. Each new lesion was evaluated for the CVS. Clinical characteristics were identified through chart review., Results: A total of 153 adults (95 relapsing-remitting MS, 27 secondary progressive MS, 16 primary progressive MS, 5 clinically isolated syndrome, and 10 healthy; 67% female) were included. Of this cohort, 96 had at least 1 new T2 or contrast-enhancing lesion during median 3.1 years (Q1-Q3: 0.7-6.3) of follow-up; lesions eligible for CVS evaluation were found in 62 (65%). Of 233 new CVS-eligible lesions, 159 (68%) were CVS+, with 30 (48%) individuals having only CVS+, 12 (19%) only CVS-, and 20 (32%) both CVS+ and CVS- lesions. In gadolinium-enhancing (Gd+) lesions, the CVS+ percentage increased from 102/152 (67%) at the first time point where the lesion was observed, to 92/114 (82%) after a median follow-up of 2.8 years. Younger age (OR = 0.5 per 10-year increase, 95% CI = 0.3-0.8) and higher CVS+ percentage at baseline (OR = 1.4 per 10% increase, 95% CI = 1.1-1.9) were associated with increased likelihood of new CVS+ lesion development., Discussion: In a cohort of adults with MS followed over a median duration of 3 years, most newly developing T2 or enhancing lesions were CVS+ (68%), and nearly half (48%) developed new CVS+ lesions only. Importantly, the effects of edema and T2 signal changes can obscure small veins in Gd+ lesions; therefore, caution and follow-up is necessary when determining their CVS status., Trial Registration Information: Clinical trial registration number NCT00001248., Classification of Evidence: This study provides Class III evidence that younger age and higher CVS+ percentage at baseline are associated with new CVS+ lesion development., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

Patients with multiple sclerosis (MS) have heterogeneous clinical presentations, symptoms, and progression over time, making MS difficult to assess and comprehend in vivo. The combination of large-scale data sharing and artificial intelligence creates new opportunities for monitoring and understanding MS using MRI. First, development of validated MS-specific image analysis methods can be boosted by verified reference, test, and benchmark imaging data. Using detailed expert annotations, artificial intelligence algorithms can be trained on such MS-specific data. Second, understanding disease processes could be greatly advanced through shared data of large MS cohorts with clinical, demographic, and treatment information. Relevant patterns in such data that may be imperceptible to a human observer could be detected through artificial intelligence techniques. This applies from image analysis (lesions, atrophy, or functional network changes) to large multidomain datasets (imaging, cognition, clinical disability, genetics). After reviewing data sharing and artificial intelligence, we highlight 3 areas that offer strong opportunities for making advances in the next few years: crowdsourcing, personal data protection, and organized analysis challenges. Difficulties as well as specific recommendations to overcome them are discussed, in order to best leverage data sharing and artificial intelligence to improve image analysis, imaging, and the understanding of MS., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image segmentation algorithms. It offers a standardized measure of segmentation accuracy which has proven useful. However, it offers diminishing insight when the number of objects is unknown, such as in white matter lesion segmentation of multiple sclerosis (MS) patients. We present a refinement for finer grained parsing of SDI results in situations where the number of objects is unknown. We explore these ideas with two case studies showing what can be learned from our two presented studies. Our first study explores an inter-rater comparison, showing that smaller lesions cannot be reliably identified. In our second case study, we demonstrate fusing multiple MS lesion segmentation algorithms based on the insights into the algorithms provided by our analysis to generate a segmentation that exhibits improved performance. This work demonstrates the wealth of information that can be learned from refined analysis of medical image segmentations.

Background: The effects of disease-modifying therapies (DMTs) on region-specific brain atrophy in multiple sclerosis (MS) are unclear., Objective: To determine the effects of higher versus lower efficacy DMTs on rates of brain substructure atrophy in MS., Methods: A non-randomized, observational cohort of people with MS followed with annual brain magnetic resonance imaging (MRI) was evaluated retrospectively. Whole brain, subcortical gray matter (GM), cortical GM, and cerebral white matter (WM) volume fractions were obtained. DMTs were categorized as higher (DMT-H: natalizumab and rituximab) or lower (DMT-L: interferon-beta and glatiramer acetate) efficacy. Follow-up epochs were analyzed if participants had been on a DMT for ⩾6 months prior to baseline and had at least one follow-up MRI while on DMTs in the same category., Results: A total of 86 DMT epochs (DMT-H: n  = 32; DMT-L: n  = 54) from 78 participants fulfilled the study inclusion criteria. Mean follow-up was 2.4 years. Annualized rates of thalamic (-0.15% vs -0.81%; p  = 0.001) and putaminal (-0.27% vs -0.73%; p  = 0.001) atrophy were slower during DMT-H compared to DMT-L epochs. These results remained significant in multivariate analyses including demographics, clinical characteristics, and T2 lesion volume., Conclusion: DMT-H treatment may be associated with slower rates of subcortical GM atrophy, especially of the thalamus and putamen. Thalamic and putaminal volumes are promising imaging biomarkers in MS.

Total brain white matter lesion (WML) volume is the most widely established magnetic resonance imaging (MRI) outcome measure in studies of multiple sclerosis (MS). To estimate WML volume, there are a number of automatic segmentation methods available, yet manual delineation remains the gold standard approach. Automatic approaches often yield a probability map to which a threshold is applied to create lesion segmentation masks. Unfortunately, few approaches systematically determine the threshold employed; many methods use a manually selected threshold, thus introducing human error and bias into the automated procedure. In this study, we propose and validate an automatic thresholding algorithm, Thresholding Approach for Probability Map Automatic Segmentation in Multiple Sclerosis (TAPAS), to obtain subject-specific threshold estimates for probability map automatic segmentation of T2-weighted (T2) hyperintense WMLs. Using multimodal MRI, the proposed method applies an automatic segmentation algorithm to obtain probability maps. We obtain the true subject-specific threshold that maximizes the Sørensen-Dice similarity coefficient (DSC). Then the subject-specific thresholds are modeled on a naive estimate of volume using a generalized additive model. Applying this model, we predict a subject-specific threshold in data not used for training. We ran a Monte Carlo-resampled split-sample cross-validation (100 validation sets) using two data sets: the first obtained from the Johns Hopkins Hospital (JHH) on a Philips 3 Tesla (3T) scanner (n = 94) and a second collected at the Brigham and Women's Hospital (BWH) using a Siemens 3T scanner (n = 40). By means of the proposed automated technique, in the JHH data we found an average reduction in subject-level absolute error of 0.1 mL per one mL increase in manual volume. Using Bland-Altman analysis, we found that volumetric bias associated with group-level thresholding was mitigated when applying TAPAS. The BWH data showed similar absolute error estimates using group-level thresholding or TAPAS likely since Bland-Altman analyses indicated no systematic biases associated with group or TAPAS volume estimates. The current study presents the first validated fully automated method for subject-specific threshold prediction to segment brain lesions., Competing Interests: Declaration of competing interest Ms. Alessandra Valcarcel has nothing to disclose. Dr. John Muschelli has nothing to disclose. Dr. Dzung Pham has nothing to disclose. Ms. Melissa Martin has nothing to disclose. Dr. Paul Yushkevich has nothing to disclose. Dr. Kristina Patterson has served on the advisory board for Alexion. Dr. Peter Calabresi has received personal consulting fees for serving on SABs for Biogen and Disarm Therapeutics. He is PI on grants to JHU from Biogen, Novartis, Sanofi, Annexon and MedImmune. Dr. Rohit Bakshi has received consulting fees from Bayer, Biogen, Celgene, EMD Serono, Genentech, Guerbet, Sanofi-Genzyme, and Shire and research support from EMD Serono and Sanofi-Genzyme. Dr. Russell (Taki) Shinohara has received consulting fees from Genentech and Roche., (Published by Elsevier Inc.)

Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibility between protocols and scanners. It has been shown that even when care is taken to standardize acquisitions, any changes in hardware, software, or protocol design can lead to differences in quantitative results. This greatly impacts the quantitative utility of MRI in multi-site or long-term studies, where consistency is often valued over image quality. We propose a method of contrast harmonization, called DeepHarmony, which uses a U-Net-based deep learning architecture to produce images with consistent contrast. To provide training data, a small overlap cohort (n = 8) was scanned using two different protocols. Images harmonized with DeepHarmony showed significant improvement in consistency of volume quantification between scanning protocols. A longitudinal MRI dataset of patients with multiple sclerosis was also used to evaluate the effect of a protocol change on atrophy calculations in a clinical research setting. The results show that atrophy calculations were substantially and significantly affected by protocol change, whereas such changes have a less significant effect and substantially reduced overall difference when using DeepHarmony. This establishes that DeepHarmony can be used with an overlap cohort to reduce inconsistencies in segmentation caused by changes in scanner protocol, allowing for modernization of hardware and protocol design in long-term studies without invalidating previously acquired data., (Copyright © 2019 Elsevier Inc. All rights reserved.)

On average, African Americans with multiple sclerosis demonstrate higher inflammatory disease activity, faster disability accumulation, greater visual dysfunction, more pronounced brain tissue damage and higher lesion volume loads compared to Caucasian Americans with multiple sclerosis. Neurodegeneration is an important component of multiple sclerosis, which in part accounts for the clinical heterogeneity of the disease. Brain atrophy appears to be widespread, although it is becoming increasingly recognized that regional substructure atrophy may be of greater clinical relevance. Patient race (within the limitations of self-identified ancestry) is regarded as an important contributing factor. However, there is a paucity of studies examining differences in neurodegeneration and brain substructure volumes over time in African Americans relative to Caucasian American patients. Optical coherence tomography is a non-invasive and reliable tool for measuring structural retinal changes. Recent studies support its utility for tracking neurodegeneration and disease progression in vivo in multiple sclerosis. Relative to Caucasian Americans, African American patients have been found to have greater retinal structural injury in the inner retinal layers. Increased thickness of the inner nuclear layer and the presence of microcystoid macular pathology at baseline predict clinical and radiological inflammatory activity, although whether race plays a role in these changes has not been investigated. Similarly, assessment of outer retinal changes according to race in multiple sclerosis remains incompletely characterized. Twenty-two African Americans and 60 matched Caucasian Americans with multiple sclerosis were evaluated with brain MRI, and 116 African Americans and 116 matched Caucasian Americans with multiple sclerosis were monitored with optical coherence tomography over a mean duration of 4.5 years. Mixed-effects linear regression models were used in statistical analyses. Grey matter (-0.9%/year versus -0.5%: P =0.02), white matter (-0.7%/year versus -0.3%: P =0.04) and nuclear thalamic (-1.5%/year versus -0.7%/year: P =0.02) atrophy rates were approximately twice as fast in African Americans. African Americans also exhibited higher proportions of microcystoid macular pathology (12.1% versus 0.9%, P =0.001). Retinal nerve fibre layer (-1.1% versus -0.8%: P =0.02) and ganglion cell+ inner plexiform layer (-0.7%/year versus -0.4%/year: P =0.01) atrophy rates were faster in African versus Caucasian Americans. African Americans on average exhibited more rapid neurodegeneration than Caucasian Americans and had significantly faster brain and retinal tissue loss. These results corroborate the more rapid clinical progression reported to occur, in general, in African Americans with multiple sclerosis and support the need for future studies involving African Americans in order to identify individual differences in treatment responses in multiple sclerosis.

Dizziness, postural instability, and ataxia are among the most debilitating symptoms of multiple sclerosis (MS), reflecting, in large part, dysfunctional integration of visual, somatosensory, and vestibular sensory cues. However, the role of MS-related supratentorial lesions in producing such symptoms is poorly understood. In this study, motor control test (MCT) and dynamic sensory organization test (SOT) scores of 58 MS patients were compared to those of 72 healthy controls; correlations were determined between the MS scores of 49 patients and lesion volumes within 26 brain regions. Depending upon platform excursion direction and magnitude, MCT latencies, which were longer in MS patients than controls (p < 0.0001), were correlated with lesion volumes in the cortex, medial frontal lobes, temporal lobes, and parietal opercula (r's ranging from 0.20 to 0.39). SOT test scores were also impacted by MS and correlated with lesions in these same brain regions as well as within the superior frontal lobe (r's ranging from - 0.28 to - 0.40). The strongest and most consistent correlations occurred for the most challenging tasks in which incongruent visual and proprioceptive feedback were given. This study demonstrates that supratentorial lesion volumes are associated with quantitative balance measures in MS, in accord with the concept that balance relies upon highly convergent and multimodal neural pathways involving the skin, muscles, joints, eyes, and vestibular system.

Background and Purpose: The central vein sign is a promising MR imaging diagnostic biomarker for multiple sclerosis. Recent studies have demonstrated that patients with MS have higher proportions of white matter lesions with the central vein sign compared with those with diseases that mimic MS on MR imaging. However, the clinical application of the central vein sign as a biomarker is limited by interrater differences in the adjudication of the central vein sign as well as the time burden required for the determination of the central vein sign for each lesion in a patient's full MR imaging scan. In this study, we present an automated technique for the detection of the central vein sign in white matter lesions., Materials and Methods: Using multimodal MR imaging, the proposed method derives a central vein sign probability, π ij , for each lesion, as well as a patient-level central vein sign biomarker, ψ i . The method is probabilistic in nature, allows site-specific lesion segmentation methods, and is potentially robust to intersite variability. The proposed algorithm was tested on imaging acquired at the University of Vermont in 16 participants who have MS and 15 participants who do not., Results: By means of the proposed automated technique, participants with MS were found to have significantly higher values of ψ than those without MS (ψ MS = 0.55 ± 0.18; ψ non-MS = 0.31 ± 0.12; P < .001). The algorithm was also found to show strong discriminative ability between patients with and without MS, with an area under the curve of 0.88., Conclusions: The current study presents the first fully automated method for detecting the central vein sign in white matter lesions and demonstrates promising performance in a sample of patients with and without MS., (© 2018 by American Journal of Neuroradiology.)

Background and Purpose: Magnetic resonance imaging (MRI) is crucial for in vivo detection and characterization of white matter lesions (WMLs) in multiple sclerosis. While WMLs have been studied for over two decades using MRI, automated segmentation remains challenging. Although the majority of statistical techniques for the automated segmentation of WMLs are based on single imaging modalities, recent advances have used multimodal techniques for identifying WMLs. Complementary modalities emphasize different tissue properties, which help identify interrelated features of lesions., Methods: Method for Inter-Modal Segmentation Analysis (MIMoSA), a fully automatic lesion segmentation algorithm that utilizes novel covariance features from intermodal coupling regression in addition to mean structure to model the probability lesion is contained in each voxel, is proposed. MIMoSA was validated by comparison with both expert manual and other automated segmentation methods in two datasets. The first included 98 subjects imaged at Johns Hopkins Hospital in which bootstrap cross-validation was used to compare the performance of MIMoSA against OASIS and LesionTOADS, two popular automatic segmentation approaches. For a secondary validation, a publicly available data from a segmentation challenge were used for performance benchmarking., Results: In the Johns Hopkins study, MIMoSA yielded average Sørensen-Dice coefficient (DSC) of .57 and partial AUC of .68 calculated with false positive rates up to 1%. This was superior to performance using OASIS and LesionTOADS. The proposed method also performed competitively in the segmentation challenge dataset., Conclusion: MIMoSA resulted in statistically significant improvements in lesion segmentation performance compared with LesionTOADS and OASIS, and performed competitively in an additional validation study., (Copyright © 2018 by the American Society of Neuroimaging.)

Purpose: To explore (i) the variability of upper cervical cord area (UCCA) measurements from volumetric brain 3D T 1 -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 T 1 -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 T 1 -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., (© 2017 International Society for Magnetic Resonance in Medicine.)

In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: (1) the sharing of a rich data set; (2) collaboration and comparison of the various avenues of research being pursued in the community; and (3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website 2 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters., (Copyright © 2017 Elsevier Inc. All rights reserved.)

It is not known whether lateralized olfactory sensitivity deficits are present in MS. Since projections from the olfactory bulb to the olfactory cortex are largely ipsilateral, and since both functional imaging and psychophysical studies suggest that the right side of the brain may be more involved in olfactory processing than the left, we addressed this issue by administering well-validated tests of odor detection, along with tests of odor identification, to each side of the nose of 73 MS patients and 73 age-, gender-, and race-matched normal controls. We also determined, in 63 of the MS patients, whether correlations were present between the olfactory test measures and MRI-determined lesions in brain regions ipsilateral and contralateral to the nose side that was tested. No significant left:right differences in either olfactory sensitivity or identification were present, although in both cases mean performance was lower in the MS than in the control subjects (ps<0.0001). Scores on the two sides of the nose were positively correlated with one another (threshold r=0.56, p<0.0001; Identification r=0.71, p<0.0001). The percent of MS patients whose bilateral test scores fell below the 10th percentile of controls did not differ between the odor identification and detection threshold tests. Both left and right odor identification and detection test scores were weakly correlated with lesion volumes in temporal and frontal lobe brain regions (r's<0.40). Our findings demonstrate that MS does not differentially influence odor perception on left and right sides of the nose, regardless of whether sensitivity or identification is being measured. They also indicate that tests of odor identification and detection are similarly influenced by MS and that such influences are associated with central brain lesions., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Empirical studies of taste function in multiple sclerosis (MS) are rare. Moreover, a detailed assessment of whether quantitative measures of taste function correlate with the punctate and patchy myelin-related lesions found throughout the CNS of MS patients has not been made. We administered a 96-trial test of sweet (sucrose), sour (citric acid), bitter (caffeine) and salty (NaCl) taste perception to the left and right anterior (CN VII) and posterior (CN IX) tongue regions of 73 MS patients and 73 matched controls. The number and volume of lesions were assessed using quantitative MRI in 52 brain regions of 63 of the MS patients. Taste identification scores were significantly lower in the MS patients for sucrose (p = 0.0002), citric acid (p = 0.0001), caffeine (p = 0.0372) and NaCl (p = 0.0004) and were present in both anterior and posterior tongue regions. The percent of MS patients with identification scores falling below the 5th percentile of controls was 15.07 % for caffeine, 21.9 % for citric acid, 24.66 % for sucrose, and 31.50 % for NaCl. Such scores were inversely correlated with lesion volumes in the temporal, medial frontal, and superior frontal lobes, and with the number of lesions in the left and right superior frontal lobes, right anterior cingulate gyrus, and left parietal operculum. Regardless of the subject group, women outperformed men on the taste measures. These findings indicate that a sizable number of MS patients exhibit taste deficits that are associated with MS-related lesions throughout the brain.

Background: Susceptibility-based MRI offers a unique opportunity to study neurological diseases such as multiple sclerosis (MS). In this work, we assessed a three-dimensional segmented echo-planar-imaging (3D-EPI) sequence to rapidly acquire high-resolution T2 -weighted and phase contrast images of the whole brain. We also assessed if these images could depict important features of MS at clinical field strength, and we tested the effect of a gadolinium-based contrast agent (GBCA) on these images., Materials and Methods: The 3D-EPI acquisition was performed on four healthy volunteers and 15 MS cases on a 3T scanner. The 3D sagittal images of the whole brain were acquired with a voxel size of 0.55 × 0.55 × 0.55 mm(3) in less than 4 minutes. For the MS cases, the 3D-EPI acquisition was performed before, during, and after intravenous GBCA injection., Results: Both T2-weighted and phase-contrast images from the 3D-EPI acquisition were sensitive to the presence of lesions, parenchymal veins, and tissue iron. Conspicuity of the veins was enhanced when images were obtained during injection of GBCA., Conclusions: We propose this rapid imaging sequence for investigating, in a clinical setting, the spatiotemporal relationship between small parenchymal veins, iron deposition, and lesions in MS patient brains., (© The Author(s) 2014.)

While computed tomography and other imaging techniques are measured in absolute units with physical meaning, magnetic resonance images are expressed in arbitrary units that are difficult to interpret and differ between study visits and subjects. Much work in the image processing literature on intensity normalization has focused on histogram matching and other histogram mapping techniques, with little emphasis on normalizing images to have biologically interpretable units. Furthermore, there are no formalized principles or goals for the crucial comparability of image intensities within and across subjects. To address this, we propose a set of criteria necessary for the normalization of images. We further propose simple and robust biologically motivated normalization techniques for multisequence brain imaging that have the same interpretation across acquisitions and satisfy the proposed criteria. We compare the performance of different normalization methods in thousands of images of patients with Alzheimer's disease, hundreds of patients with multiple sclerosis, and hundreds of healthy subjects obtained in several different studies at dozens of imaging centers.

Objective: To determine the relationships between conventional and segmentation-derived optical coherence tomography (OCT) retinal layer thickness measures with intracranial volume (a surrogate of head size) and brain substructure volumes in multiple sclerosis (MS)., Design: Cross-sectional study., Setting: Johns Hopkins University, Baltimore, Maryland., Participants: A total of 84 patients with MS and 24 healthy control subjects., Main Outcome Measures: High-definition spectral-domain OCT conventional and automated segmentation-derived discrete retinal layer thicknesses and 3-T magnetic resonance imaging brain substructure volumes., Results: Peripapillary retinal nerve fiber layer as well as composite ganglion cell layer+inner plexiform layer thicknesses in the eyes of patients with MS without a history of optic neuritis were associated with cortical gray matter (P=.01 and P=.04, respectively) and caudate (P=.04 and P=.03, respectively) volumes. Inner nuclear layer thickness, also in eyes without a history of optic neuritis, was associated with fluid-attenuated inversion recovery lesion volume (P=.007) and inversely associated with normal-appearing white matter volume (P=.005) in relapsing-remitting MS. As intracranial volume was found to be related with several of the OCT measures in patients with MS and healthy control subjects and is already known to be associated with brain substructure volumes, all OCT-brain substructure relationships were adjusted for intracranial volume. CONCLUSIONS Retinal measures reflect global central nervous system pathology in multiple sclerosis, with thicknesses of discrete retinal layers each appearing to be associated with distinct central nervous system processes. Moreover, OCT measures appear to correlate with intracranial volume in patients with MS and healthy control subjects, an important unexpected factor unaccounted for in prior studies examining the relationships between peripapillary retinal nerve fiber layer thickness and brain substructure volumes.

Despite the fact that acute cases of multiple sclerosis (MS)-related pure-tone hearing loss have been reported in the literature, consensus is lacking as to the chronic influences of MS on pure-tone thresholds. Most studies examining such influences have been limited by small sample sizes, lack of statistical comparisons between patients and controls, and confounding of the hearing measure with influences from sex and age. To date, associations between pure-tone thresholds and central MS-related brain lesions have not been assessed. In this study, pure-tone thresholds ranging from 0.5 to 8 kHz were measured in 73 MS patients and 73 individually age- and gender-matched normal controls. In 63 MS patients, correlations were computed between the threshold values and MRI-determined lesion activity in 26 central brain regions. Although thresholds were strongly influenced by sex, age, and tonal frequency, no meaningful influences of MS were discerned. Moreover, no significant association between the threshold values and central MS-related lesion activity was evident in any brain region evaluated. This study, the largest on this topic to use carefully matched control subjects and the sole study to assess relationships between auditory thresholds and central MS-related lesions, strongly suggests that (a) MS is not chronically associated with pure-tone hearing loss and (b) pure-tone thresholds are unrelated to MS lesion activity in higher brain regions. These findings, along with general reports from the literature, support the concept that when MS-related hearing threshold deficits are found, they are episodic and primarily dependent on lesions within the eighth nerve or brainstem., ((c) 2012 APA, all rights reserved)

Background: Brain atrophy is a well-accepted imaging biomarker of multiple sclerosis (MS) that partially correlates with both physical disability and cognitive impairment., Methodology/principal Findings: Based on MRI scans of 60 MS cases and 37 healthy volunteers, we measured the volumes of white matter (WM) lesions, cortical gray matter (GM), cerebral WM, caudate nucleus, putamen, thalamus, ventricles, and brainstem using a validated and completely automated segmentation method. We correlated these volumes with the Expanded Disability Status Scale (EDSS), MS Severity Scale (MSSS), MS Functional Composite (MSFC), and quantitative measures of ankle strength and toe sensation. Normalized volumes of both cortical and subcortical GM structures were abnormally low in the MS group, whereas no abnormality was found in the volume of the cerebral WM. High physical disability was associated with low cerebral WM, thalamus, and brainstem volumes (partial correlation coefficients ~0.3-0.4) but not with low cortical GM volume. Thalamus volumes were inversely correlated with lesion load (r = -0.36, p<0.005)., Conclusion: The GM is atrophic in MS. Although lower WM volume is associated with greater disability, as might be expected, WM volume was on average in the normal range. This paradoxical result might be explained by the presence of coexisting pathological processes, such as tissue damage and repair, that cause both atrophy and hypertrophy and that underlie the observed disability.

Inflammatory demyelination and axon damage in the corpus callosum are prominent features of multiple sclerosis (MS) and may partially account for impaired performance on complex tasks. The objective of this article was to characterize quantitative callosal MRI abnormalities and their association with disability. In 69 participants with MS and 29 healthy volunteers, lesional and extralesional callosal MRI indices were estimated via diffusion tensor tractography. expanded disability status scale (EDSS) and MS functional composite (MSFC) scores were recorded in 53 of the participants with MS. All tested callosal MRI indices were diffusely abnormal in MS. EDSS score was correlated only with age (r = 0.51). Scores on the overall MSFC and its paced serial auditory addition test (PASAT) and 9-hole peg test components were correlated with callosal fractional anisotropy (r = 0.27, 0.35, and 0.31, respectively) and perpendicular diffusivity (r = -0.29, -0.30, and -0.31) but not with overall callosal volume or callosal lesion volume; the PASAT score was more weakly correlated with callosal magnetization-transfer ratio (r = 0.21). Anterior callosal abnormalities were associated with impaired PASAT performance and posterior abnormalities with slow performance on the 9-hole peg test. In conclusion, abnormalities in the corpus callosum can be assessed with quantitative MRI and are associated with cognitive and complex upper-extremity dysfunction in MS.

We describe a new fully automatic method for the segmentation of brain images that contain multiple sclerosis white matter lesions. Multichannel magnetic resonance images are used to delineate multiple sclerosis lesions while segmenting the brain into its major structures. The method is an atlas-based segmentation technique employing a topological atlas as well as a statistical atlas. An advantage of this approach is that all segmented structures are topologically constrained, thereby allowing subsequent processing such as cortical unfolding or diffeomorphic shape analysis techniques. Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.

Background and purposeMR 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 methodsAll 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.ResultsSystematic 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.ConclusionsEven in multicenter studies with consistent scanner field strength and manufacturer after protocol harmonization, systematic differences can lead to severe biases in volumetric analyses.

The article presents a study which assesses rapid, high-resolution, whole-brain, susceptibility-based MRI of patients with multiple sclerosis (MS). Three-dimensional segmented echo-planar-imaging (3D-EPI) sequence on four healthy volunteers and 15 MS cases were evaluated to acquire high-resolution and phase contrast images of the whole brain. The study proposed the use of rapid imaging sequence in investigating spatiotemporal relationship in MS patients brains.