Neuroimaging assessment of facility-bound severely-affected MS reveals the critical role of cortical gray matter pathology: results from the CASA-MS case-controlled study.

BACKGROUND: A subgroup of people with multiple sclerosis (pwMS) will develop severe disability. The pathophysiology underlying severe MS is unknown. The comprehensive assessment of severely affected MS (CASA-MS) was a case-controlled study that compared severely disabled in skilled nursing (SD/SN) (EDSS ≥ 7.0) to less-disabled (EDSS 3.0-6.5) community dwelling (CD) progressive pwMS, matched on age-, sex- and disease-duration (DDM). OBJECTIVES: To identify neuroimaging and molecular biomarker characteristics that distinguish SD/SN from DDM-CD progressive pwMS. METHODS: This study was carried at SN facility and at a tertiary MS center. The study collected clinical, molecular (serum neurofilament light chain, sNfL and glial acidic fibrillary protein, sGFAP) and MRI quantitative lesion-, brain volume-, and tissue integrity-derived measures. Statistical analyses were controlled for multiple comparisons. RESULTS: 42 SD/SN and 42 DDM-CD were enrolled. SD/SN pwMS showed significantly lower cortical volume (CV) (p < 0.001, d = 1.375) and thalamic volume (p < 0.001, d = 0.972) compared to DDM-CD pwMS. In a logistic stepwise regression model, the SD/SN pwMS were best differentiated from the DDM-CD pwMS by lower CV (p < 0.001) as the only significant predictor, with the accuracy of 82.3%. No significant differences between the two groups were observed for medulla oblongata volume, a proxy for spinal cord atrophy and white matter lesion burden, while there was a statistical trend for numerically higher sGFAP in SD/SN pwMS. CONCLUSIONS: The CASA-MS study showed significantly more gray matter atrophy in severe compared to less-severe progressive MS.

A multiscale assessment of bowel impairment in an Italian multiple sclerosis cohort.

Bowel dysfunctions (BD) in multiple sclerosis (MS) are under reported despite their clinical relevance. Scales usually applied do not thoroughly assess constipation and fecal incontinence. Instead, a proper qualitative and quantitative description of these symptoms might have relevant clinical and scientific consequences. The aim of this project is to study the prevalence of BD in a cohort of persons with MS (pwMS). Four-hundred and forty-seven pwMS (330 relapsing-remitting MS-RRMS and 117 progressive MS-PMS) were recruited. Three different questionnaires were administered: the neurogenic bowel dysfunction score (NBDS), the Wexner constipation scale (WexCon) and the Wexner incontinence scale (WexInc). All the scales were divided in subscores according to symptom severity. The prevalence of BD, considered as NBDS > 0, was 53.7%. Mean scores in pwMS group were as follows: NBDS 2.6 (SD 3.5), WexInc 1.1 (SD 2.4), WexCon 4.4 (SD 5.9). NBDS, WexCon and WexInc were significantly higher in PMS vs RRMS (p < 0.001), and significantly associated with disease duration, EDSS, multiple sclerosis severity score (p < 0.001), as well as with each other (p < 0.001). Our study confirms the presence of bowel dysfunctions in a large group of pwMS with a wide range of disability and their association with progressive disease phenotype and clinical disability.

Italian adaptation of the Edinburgh Social Cognition Test (ESCoT): A new tool for the assessment of theory of mind and social norm understanding.

The relevance of social cognition assessment has been formally described in the Diagnostic and Statistical Manual of Mental Disorders-5. However, social cognition tools evaluating different socio-cognitive components for Italian-speaking populations are lacking. The Edinburgh Social Cognition Test (ESCoT) is a new social cognition measure that uses animations of everyday social interactions to assess (i) cognitive theory of mind, (ii) affective theory of mind, (iii) interpersonal social norm understanding, and (iv) intrapersonal social norm understanding. Previous studies have shown that the ESCoT is a sensitive measure of social cognition in healthy and clinical populations in the United Kingdom. This work aimed to adapt and validate the ESCoT in an Italian population of healthy adults. A translation-back-translation procedure was followed to create and refine the Italian version. Then, 94 healthy adults (47 females, mean age 35 ± 15.9) completed the ESCoT, a battery of conventional social cognition tests (Yoni; Reading the Mind in the Eyes Strange Stories, and Social Norm Questionnaire, SNQ) and measures of intelligence and executive functions. Reliability, convergent validity, and predictors of performance on the ESCoT were examined. Results demonstrated good reliability of the ESCoT and an association between the ESCoT scores and some traditional social cognition tests (Yoni cognitive subscale, SNQ). Hierarchical regression results showed that the ESCoT total score was associated with age. Also, the ESCoT subscore (intrapersonal social norm understanding) was associated with education. These findings support the ESCoT as a valid tool testing social norm understanding, a reliable measure of social cognition for an adult Italian population, and provides further evidence that the ESCoT is sensitive to age- and education-related changes in social cognition, and it is a task not affected by general cognitive functioning.

Assessment of T2 lesion-based disease activity volume outcomes in predicting disease progression in multiple sclerosis over 10 years.

BACKGROUND: New/enlarging T2 lesion count and T2-lesion volume (LV) are used as conventional secondary endpoints in clinical trials of patients with multiple sclerosis (PwMS). However, those outcomes may have several limitations, such as inability to account for heterogeneity of lesion formation/enlargement frequency and their dynamic volumetric behavior. Measurement of volume rather than count of new/enlarging lesions may be more representative outcome of dynamic changes over time. OBJECTIVES: To investigate whether new/enlarging T2-LV is more predictive of confirmed disability progression (CDP), compared to total T2-LV or new/enlarging T2 lesion count over long-term follow-up. METHODS: We studied 176 early relapsing-remitting PwMS who were followed with annual MRI examinations over 10 years. T2-LV, new/enlarging T2-LV, and new/enlarging lesion count were determined. Cumulative count/volumes were obtained. 10-year CDP was confirmed after 48-weeks. ANCOVA analysis detected MRI outcome differences in stable (n = 76) and CDP (n = 100) groups at different time points, after correction for multiple comparisons. RESULTS: PwMS with CDP had greater cumulative new/enlarging T2-LV at 4 years (p = 0.049), and enlarging T2-LV at 4- (p = 0.039) and 6-year follow-up (p = 0.032), compared to stable patients. PwMS with CDP did not differ from stable ones in new/enlarging T2 lesion count or total T2-LV at any of the study timepoints. PwMS with Expanded Disability Status Scale change >2.0 had significantly greater enlarging T2 lesion count (p = 0.01) and enlarging T2-LV (p = 0.038) over the 10-year follow-up. CONCLUSION: Enlargement of T2 lesions is more strongly associated with long-term disability progression compared to other conventional T2 lesion-based outcomes.

MRI-based thalamic volumetry in multiple sclerosis using FSL-FIRST: Systematic assessment of common error modes.

BACKGROUND AND PURPOSE: FSL's FMRIB's Integrated Registration and Segmentation Tool (FSL-FIRST) is a widely used and well-validated tool. Automated thalamic segmentation is a common application and an important longitudinal measure for multiple sclerosis (MS). However, FSL-FIRST's algorithm is based on shape models derived from non-MS groups. As such, the present study sought to systematically assess common thalamic segmentation errors made by FSL-FIRST on MRIs from people with multiple sclerosis (PwMS). METHODS: FSL-FIRST was applied to generate thalamic segmentation masks for 890 MR images in PwMS. Images and masks were reviewed systematically to classify and quantify errors, as well as associated anatomical variations and MRI abnormalities. For cases with overt errors (n = 362), thalamic masks were corrected and quantitative volumetric differences were calculated. RESULTS: In the entire quantitative volumetric group, the mean volumetric error of FSL-FIRST was 2.74% (0.360 ml): among only corrected cases, the mean volumetric error was 6.79% (0.894 ml). The average percent volumetric error associated with seven error types, two anatomical variants, and motions artifacts are reported. Additional analyses showed that the presence of motion artifacts or anatomical variations significantly increased the probability of error (χ2  = 18.14, p < .01 and χ2  = 64.89, p < .001, respectively). Finally, thalamus volume error was negatively associated with degree of atrophy, such that smaller thalami were systematically overestimated (r = -.28, p < .001). CONCLUSIONS: In PwMS, FSL-FIRST thalamic segmentation miscalculates thalamic volumetry in a predictable fashion, and may be biased to overestimate highly atrophic thalami. As such, it is recommended that segmentations be reviewed and corrected manually when appropriate for specific studies.

Automated Assessment of the Substantia Nigra Pars Compacta in Parkinson's Disease: A Diffusion Tensor Imaging Study.

The substantia nigra (SN) pars compacta (SNpc) and pars reticulata (SNpr) are differentially affected in Parkinson's disease (PD). Separating the SNpc and SNpr is challenging with standard magnetic resonance imaging (MRI). Diffusion tensor imaging (DTI) allows for the characterization of SN microstructure in a non-invasive manner. In this study, 29 PD patients and 28 healthy controls (HCs) were imaged with 1.5T MRI for DTI. Images were nonlinearly registered to standard space and SNpc and SNpr DTI parameters were measured. ANCOVA and receiver operator characteristic (ROC) analyses were performed. Clinical associations were assessed with Spearman correlations. Multiple corrections were controlled for false discovery rate. PD patients presented with significantly increased SNpc axial diffusivity (AD) (1.207 ± 0.068 versus 1.156 ± 0.045, p = 0.024), with ROC analysis yielding an under the curve of 0.736. Trends with Unified Parkinson's Disease Rating Scale (UPDRS) III scores were identified for SNpc MD (rs = 0.449), AD (rs = 0.388), and radial diffusivity (rs = 0.391) (all p < 0.1). A trend between baseline SNpr MD and H&Y change (rs = 0.563, p = 0.081) over 2.9 years of follow-up was identified (n = 14). In conclusion, SN microstructure shows robust, clinically meaningful associations in PD.

Visual deficits and cognitive assessment of multiple sclerosis: confounder, correlate, or both?

BACKGROUND: The relationship between visual impairment and cognitive performance in multiple sclerosis (MS) remains poorly understood. OBJECTIVE: To determine associations between visual acuity and optical coherence tomography (OCT) measures with cognitive performance of MS patients and healthy controls (HCs). METHODS: 141 MS patients (with and without MS optic neuritis; MSON) and 50 HCs underwent neuropsychological, visual, and OCT testing. California Verbal Learning Test (CVLT-II), Brief Visuospatial Memory Test (BVMT-R), and Symbol Digit Modalities Test (SDMT) were used. Patients with test performance below - 1.5 standard deviations of the mean HCs scores were labeled as cognitive impairment. Visual ability was assessed with 100%, 2.5%, and 1.25% low-contrast letter acuity (LCLA) charts. OCT-derived peripapillary retinal nerve fiber layer (pRNFL) thickness, macular volume (MV), macular ganglion cell inner plexiform (mGCIP) thickness (as a sum of GC and IP layers), and macular inner nuclear layer (mINL) were computed. RESULTS: 100% and 2.5% LCLA associated with SDMT in MS and HCs (p < 0.001; and p < 0.012, respectively). In MSON patients, visually demanding tests were explained by pRNFL and macular volume for SDMT (ß = 0.172, p = 0.039 and ß = 0.27, p = 0.001) and MV for BVMT-R (ß = 0.21, p = 0.012). In non-MSON, only mINL was predictor of CVLT-II. pRNFL and MV predicted cognitive impairment with an accuracy of 72.2% (Negelkerke R2 = 0.234). These findings were driven by associations within the progressive MS subgroup. HC's SDMT performance was explained by mGCIP (ß = 0.316, p = 0.001). CONCLUSIONS: Both LCLA and OCT-based measures (pRNFL and macular volume) were associated with MS cognitive performance. OCT-based measures were also significant predictors of cognitive status in MS patients. mGCIP associated with cognitive performance in HCs.

Combined Assessment of Diffusion Parameters and Cerebral Blood Flow Within Basal Ganglia in Early Parkinson's Disease.

Diffusion tensor imaging (DTI) is a sensitive tool for detecting brain tissue microstructural alterations in Parkinson's disease (PD). Abnormal cerebral perfusion patterns have also been reported in PD patients using arterial spin labeling (ASL) MRI. In this study we aimed to perform a combined DTI and ASL assessment in PD patients within the basal ganglia, in order to test the relationship between microstructural and perfusion alterations. Fifty-two subjects participated in this study. Specifically, 26 PD patients [mean age (SD) = 66.7 (8.9) years, 21 males, median (IQR) Modified Hoehn and Yahr = 1.5 (1-1.6)] and twenty-six healthy controls [HC, mean age (SD) = 65.2 (7.5), 15 males] were scanned with 1.5T MRI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) maps were derived from diffusion-weighted images, while cerebral blood flow (CBF) maps were computed from ASL data. After registration to Montreal Neurological Institute standard space, FA, MD, AD, RD and CBF median values were extracted within specific regions of interest: substantia nigra, caudate, putamen, globus pallidus, thalamus, red nucleus and subthalamic nucleus. DTI measures and CBF were compared between the two groups. The relationship between diffusion parameters and CBF was tested with Spearman's correlations. False discovery rate (FDR)-corrected p-values lower than 0.05 were considered significant, while uncorrected p-values <0.05 were considered a trend. No significant FA, MD and RD differences were observed. AD was significantly increased in PD patients compared with HC in the putamen (p = 0.005, pFDR = 0.035). No significant CBF differences were found between PD patients and HC. Diffusion parameters were not significantly correlated with CBF in the HC group, while a significant correlation emerged for PD patients in the caudate nucleus, for all DTI measures (with FA: r = 0.543, pFDR = 0.028; with MD: r = -0.661, pFDR = 0.002; with AD: r = -0.628, pFDR = 0.007; with RD: r = -0.635, pFDR = 0.003). This study showed that DTI is a more sensitive technique than ASL to detect alterations in the basal ganglia in the early phase of PD. Our results suggest that, although DTI and ASL convey different information, a relationship between microstructural integrity and perfusion changes in the caudate may be present.

Assessment of mesoscopic properties of deep gray matter iron through a model-based simultaneous analysis of magnetic susceptibility and R2* - A pilot study in patients with multiple sclerosis and normal controls.

Most studies of brain iron relied on the effect of the iron on magnetic resonance (MR) relaxation properties, such as R2∗, and bulk tissue magnetic susceptibility, as measured by quantitative susceptibility mapping (QSM). The present study exploited the dependence of R2∗ and magnetic susceptibility on physical interactions at different length-scales to retrieve information about the tissue microenvironment, rather than the iron concentration. We introduce a method for the simultaneous analysis of brain tissue magnetic susceptibility and R2∗ that aims to isolate those biophysical mechanisms of R2∗ -contrast that are associated with the micro- and mesoscopic distribution of iron, referred to as the Iron Microstructure Coefficient (IMC). The present study hypothesized that changes in the deep gray matter (DGM) magnetic microenvironment associated with aging and pathological mechanisms of multiple sclerosis (MS), such as changes of the distribution and chemical form of the iron, manifest in quantifiable contributions to the IMC. To validate this hypothesis, we analyzed the voxel-based association between R2∗ and magnetic susceptibility in different DGM regions of 26 patients with multiple sclerosis and 33 age- and sex-matched normal controls. Values of the IMC varied significantly between anatomical regions, were reduced in the dentate and increased in the caudate of patients compared to controls, and decreased with normal aging, most strongly in caudate, globus pallidus and putamen.

Combined DTI-fMRI Analysis for a Quantitative Assessment of Connections Between WM Bundles and Their Peripheral Cortical Fields in Verbal Fluency.

Diffusion tensor imaging (DTI) tractography and functional magnetic resonance imaging (fMRI) are powerful techniques to elucidate the anatomical and functional aspects of brain connectivity. However, integrating these approaches to describe the precise link between structure and function within specific brain circuits remains challenging. In this study, a novel DTI-fMRI integration method is proposed, to provide the topographical characterization and the volumetric assessment of the functional and anatomical connections within the language circuit. In a group of 21 healthy elderly subjects (mean age 68.5 ± 5.8 years), the volume of connection between the cortical activity elicited by a verbal fluency task and the cortico-cortical fiber tracts associated with this function are mapped and quantified. An application of the method to a case study in neuro-rehabilitation context is also presented. Integrating structural and functional data within the same framework, this approach provides an overall view of white and gray matter when studying specific brain circuits.

Clinical relevance of brain atrophy assessment in multiple sclerosis. Implications for its use in a clinical routine.

INTRODUCTION: Brain atrophy measurement in multiple sclerosis (MS) has become an important outcome for determining patients at risk for developing physical and cognitive disability. AREAS COVERED: In this article, we discuss the methodological issues related to using this MRI metric routinely, in a clinical setting. Understanding trajectories of annualized whole brain, gray and white matter, thalamic volume loss, and enlargement of ventricular space in specific MS phenotypes is becoming increasingly important. Evidence is mounting that disease-modifying treatments exert a positive effect on slowing brain atrophy progression in MS. Expert Commentary: While there is a need to translate measurement of brain atrophy to clinical routine at the individual patient level, there are still a number of challenges to be met before this can actually happen, including how to account for biological confounding factors and pseudoatrophy, standardize acquisition and analyses parameters, which can influence the accuracy of the assessments.

Cardiovascular risk factors are associated with increased lesion burden and brain atrophy in multiple sclerosis.

BACKGROUND: Cardiovascular (CV) risk factors have been associated with changes in clinical outcomes in patients with multiple sclerosis (MS). OBJECTIVES: To investigate the frequency of CV risks in patients with MS and their association with MRI outcomes. METHODS: In a prospective study, 326 patients with relapsing-remitting MS and 163 patients with progressive MS, 61 patients with clinically isolated syndrome (CIS) and 175 healthy controls (HCs) were screened for CV risks and scanned on a 3T MRI scanner. Examined CV risks included hypertension, heart disease, smoking, overweight/obesity and type 1 diabetes. MRI measures assessed lesion volumes (LVs) and brain atrophy. Association between individual or multiple CV risks and MRI outcomes was examined adjusting for age, sex, race, disease duration and treatment status. RESULTS: Patients with MS showed increased frequency of smoking (51.7% vs 36.5%, p = 0.001) and hypertension (33.9% vs 24.7%, p=0.035) compared with HCs. In total, 49.9% of patients with MS and 36% of HCs showed ≥ 2 CV risks (p = 0.003), while the frequency of ≥ 3 CV risks was 18.8% in the MS group and 8.6% in the HCs group (p = 0.002). In patients with MS, hypertension and heart disease were associated with decreased grey matter (GM) and cortical volumes (p < 0.05), while overweight/obesity was associated with increased T1-LV (p < 0.39) and smoking with decreased whole brain volume (p = 0.049). Increased lateral ventricle volume was associated with heart disease (p = 0.029) in CIS. CONCLUSIONS: Patients with MS with one or more CV risks showed increased lesion burden and more advanced brain atrophy.

A pilot, longitudinal, 24-week study to evaluate the effect of interferon beta-1a subcutaneous on changes in susceptibility-weighted imaging-filtered phase assessment of lesions and subcortical deep-gray matter in relapsing-remitting multiple sclerosis.

BACKGROUND: Studies have shown a relationship between increased iron content and clinical progression, cognitive impairment, and brain atrophy in patients with multiple sclerosis. Altered phase, as determined by susceptibility-weighted imaging (SWI), can potentially capture iron content changes. OBJECTIVE: The objective of this study was to investigate phase changes in white matter (WM) lesions and subcortical deep-gray matter (SDGM) of patients with relapsing-remitting (RR) MS treated with interferon beta-1a administered subcutaneously versus untreated healthy controls (HCs). METHODS: We conducted a 24-week, nonrandomized, open-label pilot study of 23 patients with RRMS receiving interferon beta-1a administered subcutaneously and 15 HCs. Patients were imaged on a 3T scanner at baseline, 12, and 24 weeks; changes in phase behavior in WM lesions and regional SDGM [mean phase of low-phase voxels (MP-LPV)], and in SDGM volumes, were measured. Between- and within-group changes were tested using nonparametric statistics adjusted for multiple comparisons. RESULTS: The number (p = 0.003) and volume (p < 0.001) of phase WM lesions both significantly decreased among RRMS patients over 24 weeks. At baseline, MP-LPV was lower (suggestive of greater iron content) in total SDGM among RRMS patients versus HCs (p = 0.002). Week 24 MP-LPV changes from baseline were not significantly different between groups in total SDGM or any region except the putamen (-0.0025 radians in RRMS patients versus 0.0035 radians in HCs; p = 0.041). CONCLUSIONS: Over 24 weeks, phase lesions were reduced significantly in the RRMS group. These preliminary results suggest that SWI-filtered phase may become a useful tool for monitoring RRMS disease activity.

Longitudinal MRI and neuropsychological assessment of patients with clinically isolated syndrome.

Cognitive impairment (CI) may occur in clinically isolated syndrome (CIS) patients. While the relationship between CI and magnetic resonance imaging (MRI) has been investigated extensively in multiple sclerosis (MS), MRI correlates of CI in CIS patients are unknown. To investigate the evolution of CI and to determine brain MRI structural correlates associated with CI in CIS patients. This prospective 24-month observational study examined 81 CIS patients treated with 30 µg of intramuscular interferon beta 1a once a week. MRI acquisition and neuropsychological (NP) assessment were performed at baseline, 6, 12 and 24 months. Participants were tested with Czech-validated version of Minimal Assessment of Cognitive Function in MS battery and MRI measures of lesion activity and burden, and global, tissue-specific and regional brain atrophy were performed. Over 24 months, 36 CIS patients developed clinically definite MS (CDMS). CI was observed in 10 (12.3 %) CIS patients at baseline and at the 24 months follow-up. Eight CIS patients changed their CI status over the follow-up (four improved and four worsened). No significant difference in development of CI was detected between stable CIS patients and those who developed CDMS. In multivariate regression and mixed-effect model analyses, no significant relationship was found between NP and MRI parameters. The lack of significant relationship between MRI metrics and cognition in this group of CIS patients could be attributed to several factors including the cognitive reserve, effect of disease-modifying therapy and relatively short follow-up period.

Improved longitudinal gray and white matter atrophy assessment via application of a 4-dimensional hidden Markov random field model.

SIENA and similar techniques have demonstrated the utility of performing "direct" measurements as opposed to post-hoc comparison of cross-sectional data for the measurement of whole brain (WB) atrophy over time. However, gray matter (GM) and white matter (WM) atrophy are now widely recognized as important components of neurological disease progression, and are being actively evaluated as secondary endpoints in clinical trials. Direct measures of GM/WM change with advantages similar to SIENA have been lacking. We created a robust and easily-implemented method for direct longitudinal analysis of GM/WM atrophy, SIENAX multi-time-point (SIENAX-MTP). We built on the basic halfway-registration and mask composition components of SIENA to improve the raw output of FMRIB's FAST tissue segmentation tool. In addition, we created LFAST, a modified version of FAST incorporating a 4th dimension in its hidden Markov random field model in order to directly represent time. The method was validated by scan-rescan, simulation, comparison with SIENA, and two clinical effect size comparisons. All validation approaches demonstrated improved longitudinal precision with the proposed SIENAX-MTP method compared to SIENAX. For GM, simulation showed better correlation with experimental volume changes (r=0.992 vs. 0.941), scan-rescan showed lower standard deviations (3.8% vs. 8.4%), correlation with SIENA was more robust (r=0.70 vs. 0.53), and effect sizes were improved by up to 68%. Statistical power estimates indicated a potential drop of 55% in the number of subjects required to detect the same treatment effect with SIENAX-MTP vs. SIENAX. The proposed direct GM/WM method significantly improves on the standard SIENAX technique by trading a small amount of bias for a large reduction in variance, and may provide more precise data and additional statistical power in longitudinal studies.

Improved assessment of multiple sclerosis lesion segmentation agreement via detection and outline error estimates.

BACKGROUND: Presented is the method "Detection and Outline Error Estimates" (DOEE) for assessing rater agreement in the delineation of multiple sclerosis (MS) lesions. The DOEE method divides operator or rater assessment into two parts: 1) Detection Error (DE) -- rater agreement in detecting the same regions to mark, and 2) Outline Error (OE) -- agreement of the raters in outlining of the same lesion. METHODS: DE, OE and Similarity Index (SI) values were calculated for two raters tested on a set of 17 fluid-attenuated inversion-recovery (FLAIR) images of patients with MS. DE, OE, and SI values were tested for dependence with mean total area (MTA) of the raters' Region of Interests (ROIs). RESULTS: When correlated with MTA, neither DE (ρ = .056, p=.83) nor the ratio of OE to MTA (ρ = .23, p=.37), referred to as Outline Error Rate (OER), exhibited significant correlation. In contrast, SI is found to be strongly correlated with MTA (ρ = .75, p < .001). Furthermore, DE and OER values can be used to model the variation in SI with MTA. CONCLUSIONS: The DE and OER indices are proposed as a better method than SI for comparing rater agreement of ROIs, which also provide specific information for raters to improve their agreement.

A sensitive, noise-resistant method for identifying focal demyelination and remyelination in patients with multiple sclerosis via voxel-wise changes in magnetization transfer ratio.

Magnetization transfer imaging (MTI) provides a reliable and histopathologically validated means for identifying important tissue changes in multiple sclerosis (MS), including demyelination and remyelination. However, most approaches to date have been based on a priori regions of interest (ROIs) and have been relatively insensitive to small focal changes or competing processes. More recent techniques have sought to address this through a voxel-wise approach, but have been limited in their detection capabilities by the amount of noise in standard MTR images. To address this issue while remaining sensitive to local changes, we propose the use of the recently introduced threshold-free cluster enhancement (TFCE) technique in combination with a Monte Carlo estimation approach. TFCE is first applied to enhance individual voxels based on their level of local cluster support, and then Monte Carlo estimation is performed to allow meaningful statistical interpretation of the resulting TFCE values. We validated this technique in three complementary ways: healthy control scan-rescan analysis, analysis of a "gold standard" simulated dataset, and analysis of a group of MS patients and healthy volunteers with 1-year longitudinal MRI scans. Scan-rescan analysis demonstrated a very low false-positive rate (1.44 mL increasing and 1.48 mL decreasing at the optimal detection threshold). Simulated dataset analysis yielded an area under receiver-operating characteristic curve of 0.942 (compared to 0.801 for a more conventional voxel-wise thresholding analysis). Finally, analysis of the real subject population showed highly significant differences (p<0.001) in volume of decreasing MTR between patients and controls. The proposed method provides a valuable means for quantifying MS-related tissue changes, particularly demyelination and remyelination, in vivo and without the use of highly complex or experimental MRI acquisition techniques. It improves on the sensitivity of other approaches, and may increase the statistical power of studies investigating the effects of therapy on MRI outcomes in MS.

Application of hidden Markov random field approach for quantification of perfusion/diffusion mismatch in acute ischemic stroke.

The perfusion/diffusion 'mismatch model' in acute ischemic stroke provides the potential to more accurately understand the consequences of thrombolytic therapy on an individual patient basis. Few methods exist to quantify mismatch extent (ischemic penumbra) and none have shown a robust ability to predict infarcted tissue outcome. Hidden Markov random field (HMRF) approaches have been used successfully in many other applications. The aim of the study was to develop a method for rapid and reliable identification and quantification of perfusion/diffusion mismatch using an HMRF approach. An HMRF model was used in combination with automated contralateral identification to segment normal tissue from non-infarcted tissue with perfusion abnormality. The infarct was used as a seed point to initialize segmentation, along with the contralateral mirror tissue. The two seeds were then allowed to compete for ownership of all unclassified tissue. In addition, a novel method was presented for quantifying tissue salvageability by weighting the volume with the degree of hypoperfusion, allowing the penumbra voxels to contribute unequal potential damage estimates. Simulated and in vivo datasets were processed and compared with results from a conventional thresholding approach. Both simulated and in vivo experiments demonstrated a dramatic improvement in accuracy with the proposed technique. For the simulated dataset, the mean absolute error decreased from 171.9% with conventional thresholding to 2.9% for the delay-weighted HMRF approach. For the in vivo dataset, the mean absolute error decreased from 564.6% for thresholding to 34.2% for the delay-weighted HMRF approach. The described method represents a significant improvement over thresholding techniques.