Assessing clinical utility of machine learning and artificial intelligence approaches to analyze speech recordings in multiple sclerosis: A pilot study.

BACKGROUND: An early diagnosis together with an accurate disease progression monitoring of multiple sclerosis is an important component of successful disease management. Prior studies have established that multiple sclerosis is correlated with speech discrepancies. Early research using objective acoustic measurements has discovered measurable dysarthria. METHOD: The objective was to determine the potential clinical utility of machine learning and deep learning/AI approaches for the aiding of diagnosis, biomarker extraction and progression monitoring of multiple sclerosis using speech recordings. A corpus of 65 MS-positive and 66 healthy individuals reading the same text aloud was used for targeted acoustic feature extraction utilizing automatic phoneme segmentation. A series of binary classification models was trained, tuned, and evaluated regarding their Accuracy and area-under-the-curve. RESULTS: The Random Forest model performed best, achieving an Accuracy of 0.82 on the validation dataset and an area-under-the-curve of 0.76 across 5 k-fold cycles on the training dataset. 5 out of 7 acoustic features were statistically significant. CONCLUSION: Machine learning and artificial intelligence in automatic analyses of voice recordings for aiding multiple sclerosis diagnosis and progression tracking seems promising. Further clinical validation of these methods and their mapping onto multiple sclerosis progression is needed, as well as a validating utility for English-speaking populations.

Facing privacy in neuroimaging: removing facial features degrades performance of image analysis methods.

BACKGROUND: Recent studies have created awareness that facial features can be reconstructed from high-resolution MRI. Therefore, data sharing in neuroimaging requires special attention to protect participants' privacy. Facial features removal (FFR) could alleviate these concerns. We assessed the impact of three FFR methods on subsequent automated image analysis to obtain clinically relevant outcome measurements in three clinical groups. METHODS: FFR was performed using QuickShear, FaceMasking, and Defacing. In 110 subjects of Alzheimer's Disease Neuroimaging Initiative, normalized brain volumes (NBV) were measured by SIENAX. In 70 multiple sclerosis patients of the MAGNIMS Study Group, lesion volumes (WMLV) were measured by lesion prediction algorithm in lesion segmentation toolbox. In 84 glioblastoma patients of the PICTURE Study Group, tumor volumes (GBV) were measured by BraTumIA. Failed analyses on FFR-processed images were recorded. Only cases in which all image analyses completed successfully were analyzed. Differences between outcomes obtained from FFR-processed and full images were assessed, by quantifying the intra-class correlation coefficient (ICC) for absolute agreement and by testing for systematic differences using paired t tests. RESULTS: Automated analysis methods failed in 0-19% of cases in FFR-processed images versus 0-2% of cases in full images. ICC for absolute agreement ranged from 0.312 (GBV after FaceMasking) to 0.998 (WMLV after Defacing). FaceMasking yielded higher NBV (p = 0.003) and WMLV (p ≤ 0.001). GBV was lower after QuickShear and Defacing (both p < 0.001). CONCLUSIONS: All three outcome measures were affected differently by FFR, including failure of analysis methods and both "random" variation and systematic differences. Further study is warranted to ensure high-quality neuroimaging research while protecting participants' privacy. KEY POINTS: • Protecting participants' privacy when sharing MRI data is important. • Impact of three facial features removal methods on subsequent analysis was assessed in three clinical groups. • Removing facial features degrades performance of image analysis methods.

Multiple sclerosis susceptibility loci do not alter clinical and MRI outcomes in clinically isolated syndrome.

It has not yet been established whether genetic predictors of multiple sclerosis (MS) susceptibility also influence disease severity and accumulation of disability. Our aim was to evaluate associations between 16 previously validated genetic susceptibility markers and MS phenotype. Patients with clinically isolated syndrome verified by positive magnetic resonance imaging (MRI) and cerebrospinal fluid findings (n=179) were treated with interferon-ß. Disability and volumetric MRI parameters were evaluated regularly for 2 years. Sixteen single-nucleotide polymorphisms (SNPs) previously validated as predictors of MS susceptibility in our cohort and their combined weighted genetic risk score (wGRS) were tested for associations with clinical (conversion to MS, relapses and disability) and MRI disease outcomes (whole brain, grey matter and white matter volumes, corpus callosum cross-sectional area, brain parenchymal fraction, T2 and T1 lesion volumes) 2 years from disease onset using mixed-effect models. We have found no associations between the tested SNPs and the clinical or MRI outcomes. Neither the combined wGRS predicted MS activity and progression over 2-year follow-up period. Power analyses confirmed 90% power to identify clinically relevant changes in all outcome variables. We conclude that the most important MS susceptibility loci do not determine MS phenotype and disease outcomes.

Diffusion tensor-MRI evidence for extra-axonal neuronal degeneration in caudate and thalamic nuclei of patients with multiple sclerosis.

BACKGROUND AND PURPOSE: MS is an inflammatory demyelinating disease affecting both WM and GM. While WM lesions are easily visualized by conventional MR imaging, the detection of GM alterations remains challenging. This diffusion tensor MR imaging study aimed to detect and characterize diffuse microscopic alterations in 2 deep GM structures, the caudate nucleus and the thalamus, in patients with RR and SP MS. The relationship between diffusivity markers, and atrophy of the caudate and the thalamus, as well as brain lesion load and clinical status of the patients was also explored. MATERIALS AND METHODS: Twenty-three RR and 18 SP patients, along with 27 healthy controls, underwent MR imaging examination including anatomic and DTI acquisitions. Volumes, mean FA, and MD of the caudate and the thalamus, as well as WM lesion volumes, were assessed. RESULTS: FA was significantly (P < .001) increased in the caudate and the thalamus of patients with MS compared with controls, and was higher in SP compared with RR patients. Increased FA was associated with volume decreases of caudate (r = -0.712; P < .001) and thalamus (r = -0.407; P < .01) in patients with MS. WM T2 lesion load was significantly associated with caudate (r = 0.611; P < .001) and thalamic (r = 0.354; P < .05) FA. Caudate FA, and, to a lesser extent, thalamic FA, were associated with functional deficits, as measured by EDSS and MSFC. CONCLUSIONS: Increased FA in the caudate and the thalamus may constitute a sensitive marker of MS pathologic processes, such as loss of dendrites and/or swelling of neuronal cell bodies.

The impact of lesion in-painting and registration methods on voxel-based morphometry in detecting regional cerebral gray matter atrophy in multiple sclerosis.

BACKGROUND AND PURPOSE: VBM has been widely used to study GM atrophy in MS. MS lesions lead to segmentation and registration errors that may affect the reliability of VBM results. Improved segmentation and registration have been demonstrated by WM LI before segmentation. DARTEL appears to improve registration versus the USM. Our aim was to compare the performance of VBM-DARTEL versus VBM-USM and the effect of LI in the regional analysis of GM atrophy in MS. MATERIALS AND METHODS: 3T T1 MR imaging scans were acquired from 26 patients with RRMS and 28 age-matched NC. LI replaced WM lesions with normal-appearing WM intensities before image segmentation. VBM analysis was performed in SPM8 by using DARTEL and USM with and without LI, allowing the comparison of 4 VBM methods (DARTEL + LI, DARTEL - LI, USM + LI, and USM - LI). Accuracy of VBM was assessed by using NMI, CC, and a simulation analysis. RESULTS: Overall, DARTEL + LI yielded the most accurate GM maps among the 4 methods (highest NMI and CC, P < .001). DARTEL + LI showed significant GM loss in the bilateral thalami and caudate nuclei in patients with RRMS versus NC. The other 3 methods overestimated the number of regions of GM loss in RRMS versus NC. LI improved the accuracy of both VBM methods. Simulated data suggested the accuracy of the results provided from patient MR imaging analysis. CONCLUSIONS: We introduce a pipeline that shows promise in limiting segmentation and registration errors in VBM analysis in MS.

A 3T MR imaging investigation of the topography of whole spinal cord atrophy in multiple sclerosis.

BACKGROUND AND PURPOSE: Spinal cord atrophy is a common feature of MS. However, it is unknown which cord levels are most susceptible to atrophy. We performed whole cord imaging to identify the levels most susceptible to atrophy in patients with MS versus controls and also tested for differences among MS clinical phenotypes. MATERIALS AND METHODS: Thirty-five patients with MS (2 with CIS, 27 with RRMS, 2 with SPMS, and 4 with PPMS phenotypes) and 27 healthy controls underwent whole cord 3T MR imaging. The spinal cord contour was segmented and assigned to bins representing each C1 to T12 vertebral level. Volumes were normalized, and group comparisons were age-adjusted. RESULTS: There was a trend toward decreased spinal cord volume at the upper cervical levels in PPMS/SPMS versus controls. A trend toward increased spinal cord volume throughout the cervical and thoracic cord in RRMS/CIS versus controls reached statistical significance at the T10 vertebral level. A statistically significant decrease was found in spinal cord volume at the upper cervical levels in PPMS/SPMS versus RRMS/CIS. CONCLUSIONS: Opposing pathologic factors impact spinal cord volume measures in MS. Patients with PPMS demonstrated a trend toward upper cervical cord atrophy. However patients with RRMS showed a trend toward increased volume at the cervical and thoracic levels, which most likely reflects inflammation or edema-related cord expansion. With the disease causing both expansion and contraction of the cord, the specificity of spinal cord volume measures for neuroprotective therapeutic effect may be limited.

Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging.

BACKGROUND AND PURPOSE: Histopathologic studies have reported widespread cortical lesions in MS; however, in vivo detection by using routinely available pulse sequences is challenging. We investigated the relative frequency and subtypes of cortical lesions and their relationships to white matter lesions and cognitive and physical disability. MATERIALS AND METHODS: Cortical lesions were identified and classified on the basis of concurrent review of 3D FLAIR and 3D T1-weighted IR-SPGR 3T MR images in 26 patients with MS. Twenty-five patients completed the MACFIMS battery. White matter lesion volume, cortical lesion number, and cortical lesion volume were assessed. RESULTS: Overall, 249 cortical lesions were detected. Cortical lesions were present in 24/26 patients (92.3%) (range per patient, 0-30; mean, 9.6 ± 8.8). Most (94.4%, n = 235) cortical lesions were classified as mixed cortical-subcortical (type I); the remaining 5.6% (n = 14) were classified as purely intracortical (type II). Subpial cortical lesions (type III) were not detected. White matter lesion volume correlated with cortical lesion number and cortical lesion volume (r(S) = 0.652, r(S) = 0.705, respectively; both P < .001). After controlling for age, depression, and premorbid intelligence, we found that all MR imaging variables (cortical lesion number, cortical lesion volume, white matter lesion volume) correlated with the SDMT score (R(2) = 0.513, R(2) = 0.449, R(2) = 0.418, respectively; P < .014); cortical lesion number also correlated with the CVLT-II scores (R(2) = 0.542-0.461, P < .043). The EDSS scores correlated with cortical lesion number and cortical lesion volume (r(S) = 0.472, r(S) = 0.404, respectively; P < .05), but not with white matter lesion volume. CONCLUSIONS: Our routinely available imaging method detected many cortical lesions in patients with MS and was useful in their precise topographic characterization in the context of the gray matter-white matter junction. Routinely detectable cortical lesions were related to physical disability and cognitive impairment.

Seasonal prevalence of MS disease activity.

OBJECTIVE: This observational cohort study investigated the seasonal prevalence of multiple sclerosis (MS) disease activity (likelihood and intensity), as reflected by new lesions from serial T2-weighted MRI, a sensitive marker of subclinical disease activity. METHODS: Disease activity was assessed from the appearance of new T2 lesions on 939 separate brain MRI examinations in 44 untreated patients with MS. Likelihood functions for MS disease activity were derived, accounting for the temporal uncertainty of new lesion occurrence, individual levels of disease activity, and uneven examination intervals. Both likelihood and intensity of disease activity were compared with the time of year (season) and regional climate data (temperature, solar radiation, precipitation) and among relapsing and progressive disease phenotypes. Contrast-enhancing lesions and attack counts were also compared for seasonal effects. RESULTS: Unlike contrast enhancement or attacks, new T2 activity revealed a likelihood 2-3 times higher in March-August than during the rest of the year, and correlated strongly with regional climate data, in particular solar radiation. In addition to the likelihood or prevalence, disease intensity was also elevated during the summer season. The elevated risk season appears to lessen for progressive MS and occur about 2 months earlier. CONCLUSION: This study documents evidence of a strong seasonal pattern in subclinical MS activity based on noncontrast brain MRI. The observed seasonality in MS disease activity has implications for trial design and therapy assessment. The observed activity pattern is suggestive of a modulating role of seasonally changing environmental factors or season-dependent metabolic activity.

HLA B*44: protective effects in MS susceptibility and MRI outcome measures.

OBJECTIVE: In addition to the main multiple sclerosis (MS) major histocompatibility complex (MHC) risk allele (HLA DRB1*1501), investigations of the MHC have implicated several class I MHC loci (HLA A, HLA B, and HLA C) as potential independent MS susceptibility loci. Here, we evaluate the role of 3 putative protective alleles in MS: HLA A*02, HLA B*44, and HLA C*05. METHODS: Subjects include a clinic-based patient sample with a diagnosis of either MS or a clinically isolated syndrome (n = 532), compared to subjects in a bone marrow donor registry (n = 776). All subjects have 2-digit HLA data. Logistic regression was used to determine the independence of each allele's effect. We used linear regression and an additive model to test for correlation between an allele and MRI and clinical measures of disease course. RESULTS: After accounting for the effect of HLA DRB1*1501, both HLA A*02 and HLA B*44 are validated as susceptibility alleles (p(A*02) 0.00039 and p(B*44) 0.00092) and remain significantly associated with MS susceptibility in the presence of the other allele. Although A*02 is not associated with MS outcome measures, HLA B*44 demonstrates association with a better radiologic outcome both in terms of brain parenchymal fraction and T2 hyperintense lesion volume (p = 0.03 for each outcome). CONCLUSION: The MHC class I alleles HLA A*02 and HLA B*44 independently reduce susceptibility to MS, but only HLA B*44 appears to influence disease course, preserving brain volume and reducing the burden of T2 hyperintense lesions in subjects with MS.

Regional white matter atrophy--based classification of multiple sclerosis in cross-sectional and longitudinal data.

BACKGROUND AND PURPOSE: The different clinical subtypes of multiple sclerosis (MS) may reflect underlying differences in affected neuroanatomic regions. Our aim was to analyze the effectiveness of jointly using the inferior subolivary medulla oblongata volume (MOV) and the cross-sectional area of the corpus callosum in distinguishing patients with relapsing-remitting multiple sclerosis (RRMS), secondary-progressive multiple sclerosis (SPMS), and primary-progressive multiple sclerosis (PPMS). MATERIALS AND METHODS: We analyzed a cross-sectional dataset of 64 patients (30 RRMS, 14 SPMS, 20 PPMS) and a separate longitudinal dataset of 25 patients (114 MR imaging examinations). Twelve patients in the longitudinal dataset had converted from RRMS to SPMS. For all images, the MOV and corpus callosum were delineated manually and the corpus callosum was parcellated into 5 segments. Patients from the cross-sectional dataset were classified as RRMS, SPMS, or PPMS by using a decision tree algorithm with the following input features: brain parenchymal fraction, age, disease duration, MOV, total corpus callosum area and areas of 5 segments of the corpus callosum. To test the robustness of the classification technique, we applied the results derived from the cross-sectional analysis to the longitudinal dataset. RESULTS: MOV and central corpus callosum segment area were the 2 features retained by the decision tree. Patients with MOV >0.94 cm(3) were classified as having RRMS. Patients with progressive MS were further subclassified as having SPMS if the central corpus callosum segment area was <55.12 mm(2), and as having PPMS otherwise. In the cross-sectional dataset, 51/64 (80%) patients were correctly classified. For the longitudinal dataset, 88/114 (77%) patient time points were correctly classified as RRMS or SPMS. CONCLUSIONS: Classification techniques revealed differences in affected neuroanatomic regions in subtypes of multiple sclerosis. The combination of central corpus callosum segment area and MOV provides good discrimination among patients with RRMS, SPMS, and PPMS.

Incidence and factors associated with treatment failure in the CLIMB multiple sclerosis cohort study.

OBJECTIVE: To determine the rate of treatment failure in patients outside of a controlled treatment trial and to ascertain the factors physicians used to make this decision. METHODS: One hundred and thirty four patients with the diagnosis of relapsing-remitting (RR) multiple sclerosis (MS) or clinically isolated symptom (CIS) enrolled in the CLIMB study (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital) were treated with either interferon beta or glatiramer acetate as their initial treatment for MS. RESULTS: The probability of failing initial treatment within 3 years was 30%. Clinical activity, defined as relapses and/or progression in disability, determined treatment failure in 35.7% (n=10) of nonresponders. New T2 hyperintense or gadolinium-enhancing lesions on MRI was used to define treatment failure in 28.6% (n=8) and new MRI lesions were used in combination with clinical activity in 35.7% (n=10). Treatment failures had a higher T2 hyperintense lesion volume (p=0.015) and number of gadolinium-enhancing lesions (p=0.0001) on the enrollment MRI than responders. CONCLUSIONS: These observations demonstrate that treating physicians use both clinical and MRI parameters to define a response to treatment and initiation of a treatment change and that baseline MRI identified those with increased risk of treatment failure.

Spinal cord lesions and clinical status in multiple sclerosis: A 1.5 T and 3 T MRI study.

OBJECTIVE: Assess the relationship between spinal cord T2 hyperintense lesions and clinical status in multiple sclerosis (MS) with 1.5 and 3 T MRI. METHODS: Whole cord T2-weighted fast spin-echo MRI was performed in 32 MS patients [Expanded Disability Status Scale (EDSS) score (mean+/-SD: 2+/-1.9), range 0-6.5]. Protocols at 1.5 T and 3 T were optimized and matched on voxel size. RESULTS: Moderate correlations were found between whole cord lesion volume and EDSS score at 1.5 T (r(s)=.36, p=0.04), but not at 3 T (r(s)=0.13, p=0.46). Pyramidal Functional System Score (FSS) correlated with thoracic T2 lesion number (r(s)=.46, p=0.01) and total spinal cord lesion number (r(s)=0.37, p=0.04) and volume (r(s)=0.37, p=0.04) at 1.5 T. Bowel/bladder FSS correlated with T2 lesion volume and number in the cervical, thoracic, and total spine at 1.5 T (r(s) 0.40-0.57, all p<0.05). These MRI-FSS correlations were non-significant at 3 T. However, these correlation coefficients did not differ significantly between platforms (Choi's test p>0.05). Correlations between whole cord lesion volume and timed 25-foot walk were non-significant at 1.5 T and 3 T (p>0.05). Lesion number and volume did not differ between MRI platforms in the MS group (p>0.05). CONCLUSIONS: Despite the use of higher field MRI strength, the link between spinal lesions and MS disability remains weak. The 1.5 T and 3 T protocols yielded similar results for many comparisons.

Temporoparietal MR imaging measures of atrophy in subjects with mild cognitive impairment that predict subsequent diagnosis of Alzheimer disease.

BACKGROUND AND PURPOSE: Mild cognitive impairment (MCI) represents a transitional state between normal aging and Alzheimer disease (AD). Our goal was to determine if specific temporoparietal regions can predict the time to progress from MCI to AD. MATERIALS AND METHODS: MR images from 129 individuals with MCI were analyzed to identify the volume of 14 neocortical and 2 non-neocortical brain regions, comprising the temporal and parietal lobes. In addition, 3 neuropsychological test scores were included to determine whether they would provide independent information. After a mean follow-up time of 5 years, 44 of these individuals had progressed to a diagnosis of AD. RESULTS: Cox proportional hazards models demonstrated significant effects for 6 MR imaging regions with the greatest differences being the following: the entorhinal cortex (hazard ratio [HR] = 0.54, P < .001), inferior parietal lobule (hazard ratio [HR] = 0.64, P < .005), and middle temporal gyrus (HR = 0.64, P < .004), indicating decreased risk with larger volumes. A multivariable model showed that a combination of the entorhinal cortex (HR = 0.60, P < .001) and the inferior parietal lobule (HR = 0.62, P < .01) was the best predictor of time to progress to AD. A multivariable model reiterated the importance of including both MR imaging and neuropsychological variables in the final model. CONCLUSIONS: These findings reaffirm the importance of the entorhinal cortex and present evidence for the importance of the inferior parietal lobule as a predictor of time to progress from MCI to AD. The inclusion of neuropsychological performance in the final model continues to highlight the importance of using these measures in a complementary fashion.

CTLA4Ig treatment in patients with multiple sclerosis: an open-label, phase 1 clinical trial.

BACKGROUND: The modulation of costimulatory pathways represents an original therapeutic approach to regulate T cell-mediated autoimmune diseases by preventing or reducing autoantigen-driven T-cell activation in humans. Autoreactive CD4(+) T cells play a critical role in initiating the immune response leading to the chronic inflammation and demyelination characteristic of multiple sclerosis (MS). METHODS: We used IV infusions of CTLA4Ig to block the CD28/B7 T-cell costimulatory pathway in a phase 1 dose-escalation study in MS. Sixteen patients with relapsing-remitting MS received a single CTLA4Ig infusion and were monitored for up to 3 months after treatment. In an extension study, four additional subjects received four doses of CTLA4Ig. RESULTS: CTLA4Ig was well tolerated in patients with MS, and most adverse events were rated as mild. Immunologic assessment of the patients showed a reduction in myelin basic protein (MBP) proliferation within 2 months of infusion and decreased interferon-gamma production by MBP-specific lines. CONCLUSIONS: Inhibiting costimulatory molecule interactions by using CTLA4Ig seems safe in multiple sclerosis (MS), and the immunologic effects suggest that it may be a promising approach to regulate the inflammatory process associated with MS.

MRI measures of temporoparietal regions show differential rates of atrophy during prodromal AD.

BACKGROUND: MRI studies have demonstrated differential rates of atrophy in the entorhinal cortex and hippocampus during the prodromal phase of Alzheimer disease (AD). The current study was designed to determine whether a broader set of temporoparietal regions show differential rates of atrophy during the evolution of AD. METHODS: Sixteen regions of interest (ROIs) were analyzed on MRI scans obtained at baseline and follow-up in 66 subjects comprising three groups: controls = individuals who were cognitively normal at both baseline and follow-up; nonconverters = subjects with mild cognitive impairment (MCI) at both baseline and follow-up; converters had MCI at baseline but had progressed to AD at follow-up. RESULTS: Annualized percent change was analyzed with multivariate analysis of variance (MANOVA), covaried for age. The MANOVA demonstrated an effect of group (p = 0.004). Post hoc comparisons demonstrated greater rates of atrophy for converters vs nonconverters for six ROIs: hippocampus, entorhinal cortex, temporal pole, middle temporal gyrus, fusiform gyrus, and inferior temporal gyrus. Converters showed differentially greater rates of atrophy than controls in five of the same ROIs (and inferior parietal lobule). Rates of change in clinical status were correlated with the atrophy rates in these regions. Comparisons between controls and nonconverters demonstrated no differences. CONCLUSION: These results demonstrate that temporoparietal regions show differential rates of atrophy on MRI during prodromal Alzheimer disease (AD). MRI data correlate with measures of clinical severity and cognitive decline, suggesting the potential of these regions of interest as antemortem markers of prodromal AD.

Medulla oblongata volume: a biomarker of spinal cord damage and disability in multiple sclerosis.

BACKGROUND AND PURPOSE: While brain MR imaging is routinely performed, the MR imaging assessment of spinal cord pathology in multiple sclerosis (MS) is less frequent in clinical practice. The purpose of this study was to determine whether measurements of medulla oblongata volume (MOV) on routine brain MR imaging could serve as a biomarker of spinal cord damage and disability in MS. MATERIALS AND METHODS: We identified 45 patients with MS with both head and cervical spinal cord MR imaging and 29 age-matched and sex-matched healthy control subjects with head MR imaging. Disability was assessed by the expanded disability status scale (EDSS) and ambulation index (AI). MOV and upper cervical cord volume (UCCV) were manually segmented; semiautomated segmentation was used for brain parenchymal fraction (BPF). These measures were compared between groups, and linear regression models were built to predict disability. RESULTS: In the patients, MOV correlated significantly with UCCV (r = 0.67), BPF (r = 0.45), disease duration (r = -0.64), age (r = -0.47), EDSS score (r = -0.49) and AI (r = -0.52). Volume loss of the medulla oblongata was -0.008 cm(3)/year of age in patients with MS, but no significant linear relationship with age was found for healthy control subjects. The patients had a smaller MOV (mean +/- SD, 1.02 +/- 0.17 cm(3)) than healthy control subjects (1.15 +/- 0.15 cm(3)), though BPF was unable to distinguish between these 2 groups. MOV was smaller in patients with progressive MS (secondary- progressive MS, 0.88 +/- 0.19 cm(3) and primary-progressive MS, 0.95 +/- 0.30 cm(3)) than in patients with relapsing-remitting MS (1.08 +/- 0.15 cm(3)). A model including both MOV and BPF better predicted AI than BPF alone (P = .04). Good reproducibility in MOV measurements was demonstrated for intrarater (intraclass correlation coefficient, 0.97), interrater (0.79), and scan rescan data (0.81). CONCLUSION: MOV is associated with disability in MS and can serve as a biomarker of spinal cord damage.

Segmentation of subtraction images for the measurement of lesion change in multiple sclerosis.

BACKGROUND AND PURPOSE: Lesion volume change (LVC) assessment is essential in monitoring MS progression. LVC is usually measured by independently segmenting serial MR imaging examinations. Subtraction imaging has been proposed for improved visualization and characterization of lesion change. We compare segmentation of subtraction images (SSEG) with serial single time-point conventional segmentation (CSEG) by assessing the LVC relationship to brain atrophy and disease duration, as well as scan-rescan reproducibility and annual rates of lesion accrual. MATERIALS AND METHODS: Pairs of scans were acquired 1.5 to 4.7 years apart in 21 patients with multiple sclerosis (MS). Scan-rescan MR images were acquired within 30 minutes in 10 patients with MS. LVC was measured with CSEG and SSEG after coregistration and normalization. Coefficient of variation (COV) and Bland-Altman analyses estimated method reproducibility. Spearman rank correlations probed associations between LVC and other measures. RESULTS: Atrophy rate and net LVC were associated for SSEG (R = -0.446; P < .05) but not when using CSEG (R = -0.180; P = .421). Disease duration did not show an association with net lesion volume change per year measured by CSEG (R = -0.360; P = .11) but showed an inverse correlation with SSEG-derived measurements (R = -0.508; P < .05). Scan-rescan COV was lower for SSEG (0.98% +/- 1.55%) than for CSEG (8.64% +/- 9.91%). CONCLUSION: SSEG unveiled a relationship between T2 LVC and concomitant brain atrophy and demonstrated significantly higher measurement reproducibility. SSEG, a promising tool providing detailed analysis of subtle alterations in lesion size and intensity, may provide critical outcome measures for clinical trials of novel treatments, and may provide further insight into progression patterns in MS.

MR imaging intensity modeling of damage and repair in multiple sclerosis: relationship of short-term lesion recovery to progression and disability.

BACKGROUND AND PURPOSE: Formation of lesions in multiple sclerosis (MS) shows pronounced short-term fluctuation of MR imaging hyperintensity and size, a qualitatively known but poorly characterized phenomenon. With the use of time-series modeling of MR imaging intensity, our study relates the short-term dynamics of new T2 lesion formation to those of contrast enhancement and markers of long-term progression of disease. MATERIALS AND METHODS: We analyzed 915 examinations from weekly to monthly MR imaging in 40 patients with MS using a time-series model, emulating 2 opposing processes of T2 prolongation and shortening, respectively. Patterns of activity, duration, and residual hyperintensity within new T2 lesions were measured and evaluated for relationships to disability, atrophy, and clinical phenotype in long-term follow-up. RESULTS: Significant T2 activity was observed for 8 to 10 weeks beyond contrast enhancement, which suggests that T2 MR imaging is sensitive to noninflammatory processes such as degeneration and repair. Larger lesions showed longer subacute phases but disproportionally more recovery. Patients with smaller average peak lesion size showed trends toward greater disability and proportional residual damage. Higher rates of disability or atrophy were associated with subjects whose lesions showed greater residual hyperintensity. CONCLUSION: Smaller lesions appeared disproportionally more damaging than larger lesions, with lesions in progressive MS smaller and of shorter activity than in relapsing-remitting MS. Associations of lesion dynamics with rates of atrophy and disability and clinical subtype suggest that changes in lesion dynamics may represent a shift from inflammatory toward degenerative disease activity and greater proximity to a progressive stage, possibly allowing staging of the progression of MS earlier, before atrophy or disability develops.

Thalamic atrophy and cognition in multiple sclerosis.

OBJECTIVES: Recent studies have indicated that brain atrophy is more closely associated with cognitive impairment in multiple sclerosis (MS) than are conventional MRI lesion measures. Enlargement of the third ventricle shows a particularly strong correlation with cognitive impairment, suggesting clinical relevance of damage to surrounding structures, such as the thalamus. Previous imaging and pathology studies have demonstrated thalamic involvement in MS. In this study, we tested the hypothesis that thalamic volume is lower in MS than in normal subjects, and that thalamic atrophy in MS correlates with cognitive function. METHODS: We studied 79 patients with MS and 16 normal subjects. A subgroup of 31 MS subjects underwent cognitive testing. The thalamus was segmented in whole from three-dimensional MRI scans. We also determined whole brain atrophy (brain parenchymal fraction), third ventricular width, and whole brain T2-weighted (fluid-attenuated inversion recovery) hyperintense, T1 hypointense, and gadolinium-enhanced lesion volumes. RESULTS: Normalized thalamic volume was 16.8% lower in the MS group (p < 0.0001) vs controls. Cognitive performance in all domains was moderately to strongly related to thalamic volume in the MS group (r = 0.506 to 0.724, p < 0.005), and thalamic volume entered and remained in all regression models predicting cognitive performance. Thalamic volume showed a weak relationship to physical disability score (r = -0.316, p = 0.005). CONCLUSION: These findings suggest that thalamic atrophy is a clinically relevant biomarker of the neurodegenerative disease process in multiple sclerosis.

Cognitive dysfunction in patients with clinically isolated syndromes or newly diagnosed multiple sclerosis.

Cognitive dysfunction is common in patients with multiple sclerosis (MS), and has been associated with MRI measures of lesion burden and atrophy. Little is known about the prevalence of cognitive impairment in patients with early MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course are also unclear. This study used a brief battery of cognitive tests to determine the prevalence and pattern of cognitive impairment in patients with clinically isolated syndromes or newly diagnosed MS. The associations between cognitive impairment and MRI measures of disease severity early in the disease course were also examined. Ninety-two patients with clinically isolated syndromes or the diagnosis of MS within the last 3 years participating in the CLIMB study underwent a neurologic examination, neuropsychological evaluation and MRI at 1.5 T. Forty-nine percent of patients were impaired on one or more cognitive measures. There were no significant correlations between cognitive scores and MRI measures of disease severity including total T2 lesion volume, normal appearing white matter volume, grey matter volume, and brain parenchymal fraction. These findings suggest that cognitive impairment may predate the appearance of gross structural abnormalities on MRI and serve as an early marker of disease activity in MS.