Comparing Cognitive Profiles in Older Adults With Multiple Sclerosis and Alzheimer Disease: More Similarities Than Differences.

Background and Objectives: Up to 65% of people with multiple sclerosis (MS) experience disease-related cognitive impairment, but even after decades of research, still very little is known about the cognitive issues among older adults with MS (EwMS; individuals aged 60+). To date, few studies have attempted to characterize cognitive impairment in this group or compare EwMS with those with other neurodegenerative diseases. Our goal was to address this knowledge gap by comparing EwMS with individuals experiencing cognitive impairment due to probable Alzheimer disease (AD) with biomarker confirmation. Methods: We conducted an observational study of individuals seen for routine clinical care at the Cleveland Clinic. After excluding for potential confounding factors, 6 groups were assembled based on the results of their clinical workup and neuropsychological examination: cognitively normal, cognitively normal with MS, mild neurocognitive disorder (due to MS or AD), and major neurocognitive disorder (due to MS or AD). These groups were compared in terms of cognitive test performance, percentage of the group impaired on specific cognitive skills, and rates of cognitive impairment. Results: The sample comprised 140 individuals (64 EwMS and 76 demographically matched individuals from a memory clinic). Among those with mild neurocognitive disorder, differences between MS and AD were marked. However, in those with major neurocognitive disorder, these differences largely disappeared, except persistent performance differences on a measure of rote verbal memory. EwMS outperformed those with AD on memory tests at each level of cognitive impairment. EwMS also exhibited both subcortical and cortical deficits, rather than solely subcortical deficits. Discussion: The overall characterization of the cognitive profile of MS may be different than once described, involving both classically cortical and subcortical functions. Clinically, our results suggest that distinguishing between the cognitive effects of MS and AD at more severe levels of cognitive impairment may be less reliable than once thought. Future work to replicate these findings in other samples and deepen the understanding of cognition in older individuals with MS is needed.

Association Between Disease-Modifying Therapy and Information Processing Speed in Multiple Sclerosis.

BACKGROUND: Cognitive impairment (CI) is common in multiple sclerosis (MS). Processing speed (PS) is often affected, making it an ideal target for monitoring CI. This study aims to evaluate the association between disease-modifying therapy (DMT) use and intensity and longitudinal changes in Processing Speed Test (PST) scores for individuals with MS. METHODS: A retrospective analysis of individual PST scores at a single MS center was conducted. Individuals with 2 or more PST assessments were included. Scores on the PST were compared longitudinally between those who had been on a DMT for 2 or more years and those who had been off a DMT for 2 or more years and between those on high-efficacy DMTs and those on low-/moderate-efficacy DMTs. A linear regression model was approximated to evaluate the rate of cognitive change over time. A propensity score adjustment was conducted using a multivariable logistic regression. RESULTS: The cohort was 642 individuals, 539 on DMT and 103 off DMT. Median age and disease duration was 49.7 (IQR 42.4-57.9) and 16.6 years (IQR 9.3-23.0) in the DMT group, and 58.9 (IQR 52.2-65.3) and 20.0 years (IQR 14.1-31.4) in the non-DMT group. Both cohorts were predominantly female (75% DMT, 79.6% non-DMT), with a mean of 4 assessments (IQR 3-5), and an average monitoring duration of 1.9 years (1.2-2.4) in the DMT group, and 1.8 years (1.4-2.4) in the non-DMT group. After adjusting for multiple factors, DMT status and intensity were not found to be significant predictors of longitudinal PST change. CONCLUSIONS: Neither DMT status nor intensity was a significant predictor of cognitive processing speed over a period of approximately 2 years. Future prospective studies are needed to further support these findings.

High-resolution diffusion tensor imaging of the fornix predicts memory function in multiple sclerosis.

Background: Cognitive dysfunction is a known symptom of multiple sclerosis (MS), with memory recognized as a frequently impacted domain. Here, we used high-resolution MRI at 7 tesla to build on cross-sectional work by evaluating the longitudinal relationship of diffusion tensor imaging (DTI) measures of the fornix to episodic memory performance. Methods: A sample of 80 people with multiple sclerosis (mean age 51.9 ± 8.1 years; 24% male) underwent baseline clinical evaluation, neuropsychological assessment, and MRI. Sixty-four participants had follow-up neuropsychological testing after 1-2 years. Linear regression was used to assess the relationship of baseline imaging measures to follow-up episodic memory performance, measured using the Selective Reminding Test and Brief Visuospatial Memory Test. A reduced prediction model included cognitive function at baseline, age, sex, and disease course. Results: Radial (ß = -0.222, p < 0.026; likelihood ratio test (LRT) p < 0.018), axial (ß = -0.270, p < 0.005; LRT p < 0.003), and mean (ß = -0.242, p < 0.0139; LRT p < 0.009) diffusivity of the fornix significantly added to the model, with follow-up analysis indicating that a longer prediction interval may increase accuracy. Conclusion: These results suggest that fornix DTI has predictive value specific to memory function in MS and warrants additional investigation in the drive to develop predictors of disease progression.

Longitudinal myelin content measures of slowly expanding lesions using 7T MRI in multiple sclerosis.

BACKGROUND AND PURPOSE: Slowly expanding lesions (SELs) are thought to represent a subset of chronic active lesions and have been associated with clinical disability, severity, and disease progression. The purpose of this study was to characterize SELs using advanced magnetic resonance imaging (MRI) measures related to myelin and neurite density on 7 Tesla (T) MRI. METHODS: The study design was retrospective, longitudinal, observational cohort with multiple sclerosis (n = 15). Magnetom 7T scanner was used to acquire magnetization-prepared 2 rapid acquisition gradient echo and advanced MRI including visualization of short transverse relaxation time component (ViSTa) for myelin, quantitative magnetization transfer (qMT) for myelin, and neurite orientation dispersion density imaging (NODDI). SELs were defined as lesions showing ≥12% of growth over 12 months on serial MRI. Comparisons of quantitative measures in SELs and non-SELs were performed at baseline and over time. Statistical analyses included two-sample t-test, analysis of variance, and mixed-effects linear model for MRI metrics between lesion types. RESULTS: A total of 1075 lesions were evaluated. Two hundred twenty-four lesions (21%) were SELs, and 216 (96%) of the SELs were black holes. At baseline, compared to non-SELs, SELs showed significantly lower ViSTa (1.38 vs. 1.53, p < .001) and qMT (2.47 vs. 2.97, p < .001) but not in NODDI measures (p > .27). Longitudinally, only ViSTa showed a greater loss when comparing SEL and non-SEL (p = .03). CONCLUSIONS: SELs have a lower myelin content relative to non-SELs without a difference in neurite measures. SELs showed a longitudinal decrease in apparent myelin water fraction reflecting greater tissue injury.

Natalizumab reduces loss of gray matter and thalamic volume in patients with relapsing-remitting multiple sclerosis: A post hoc analysis from the randomized, placebo-controlled AFFIRM trial.

BACKGROUND: Loss of brain gray matter fractional volume predicts multiple sclerosis (MS) progression and is associated with worsening physical and cognitive symptoms. Within deep gray matter, thalamic damage is evident in early stages of MS and correlates with physical and cognitive impairment. Natalizumab is a highly effective treatment that reduces disease progression and the number of inflammatory lesions in patients with relapsing-remitting MS (RRMS). OBJECTIVE: To evaluate the effect of natalizumab on gray matter and thalamic atrophy. METHODS: A combination of deep learning-based image segmentation and data augmentation was applied to MRI data from the AFFIRM trial. RESULTS: This post hoc analysis identified a reduction of 64.3% (p = 0.0044) and 64.3% (p = 0.0030) in mean percentage gray matter volume loss from baseline at treatment years 1 and 2, respectively, in patients treated with natalizumab versus placebo. The reduction in thalamic fraction volume loss from baseline with natalizumab versus placebo was 57.0% at year 2 (p < 0.0001) and 41.2% at year 1 (p = 0.0147). Similar findings resulted from analyses of absolute gray matter and thalamic fraction volume loss. CONCLUSION: These analyses represent the first placebo-controlled evidence supporting a role for natalizumab treatment in mitigating gray matter and thalamic fraction atrophy among patients with RRMS. CLINICALTRIALS.GOV IDENTIFIER: NCT00027300URL: https://clinicaltrials.gov/ct2/show/NCT00027300.

Differentiating multiple sclerosis from non-specific white matter changes using a convolutional neural network image classification model.

BACKGROUND: The diagnosis of multiple sclerosis (MS) relies heavily on neuroimaging with magnetic resonance imaging (MRI) and exclusion of mimics. This can be a challenging task due to radiological overlap in several disorders and may require ancillary testing or longitudinal follow up. One of the most common radiological MS mimickers is non-specific white matter disease (NSWMD). We aimed to develop and evaluate models leveraging machine learning algorithms to help distinguish MS and NSWMD. METHODS: All adult patients who underwent MRI brain using a demyelinating protocol with available electronic medical records between 2015 and 2019 at Cleveland Clinic affiliated facilities were included. Diagnosis of MS and NSWMD were assessed from clinical documentation. Those with a diagnosis of MS and NSWMD were matched using total T2 lesion volume (T2LV) and used to train models with logistic regression and convolutional neural networks (CNN). Performance metrices were reported for each model. RESULTS: A total of 250 NSWMD MRI scans were identified, and 250 unique MS MRI scans were matched on T2LV. Cross validated logistic regression model was able to use 20 variables (including spinal cord area, regional volumes, and fractions) to predict MS compared to NSWMD with 68.0% accuracy while the CNN model was able to classify MS compared to NSWMD in two independent validation and testing cohorts with 77% and 78% accuracy on average. CONCLUSION: Automated methods can be used to differentiate MS compared to NSWMD. These methods can be used to supplement currently available diagnostic tools for patients being evaluated for MS.

Ibudilast reduces slowly enlarging lesions in progressive multiple sclerosis.

BACKGROUND: Ibudilast has shown beneficial effects on several imaging outcomes in progressive multiple sclerosis (MS). Slowly enlarging lesions are a proposed imaging biomarker of compartmentalized inflammation within chronic active lesions. OBJECTIVE: To assess the treatment effect of ibudilast on slowly enlarging lesion volumes over 96 weeks from a phase II clinical trial of ibudilast (Secondary and Primary Progressive Ibudilast NeuroNEXT Trial in Multiple Sclerosis [SPRINT-MS]). METHODS: In total, 255 participants with progressive MS from 28 sites were randomized to oral ibudilast or placebo. Participants with at least four analyzable magnetic resonance imaging (MRI) were included. Slowly enlarging lesions were quantified using Jacobian determinant maps. A linear model was used to assess the effect of ibudilast. Magnetization transfer ratio within slowly enlarging lesions was assessed to determine the effect of ibudilast on tissue integrity. RESULTS: In total, 195 participants were included in this analysis. Ibudilast significantly decreased slowly enlarging lesion volume (23%, p = 0.003). Ibudilast also reduced magnetization transfer ratio change in slowly enlarging lesions: 0.22%/year, p = 0.04. CONCLUSION: Ibudilast showed a significant effect on baseline volume of lesions that were slowly enlarging and magnetization transfer ratio in slowly enlarging lesions. The results support the use of slowly enlarging lesions for assessment of compartmentalized inflammation represented by chronic active lesions and provide further support for the neuroprotective effects of ibudilast in progressive MS.

Associations Between Cognitive Impairment and Neuroimaging in Patients with Multiple Sclerosis.

OBJECTIVE: Multiple sclerosis (MS) is a debilitating inflammatory and neurodegenerative disease which commonly involves cognitive dysfunction. Magnetic resonance imaging (MRI) studies have shown that patients with MS (pwMS) have diffuse patterns of brain atrophy, however, the relationship between the presentation of cognitive dysfunction and brain tissue loss remains understudied. Given the integral function of thalamus as a central nervous system relay center and its involvement in various brain circuits, thalamic atrophy may play a key role in the development and progression of cognitive dysfunction. The purpose of this study is to examine the relationship between cognitive impairment in pwMS and thalamic atrophy. METHODS: A total of 121 pwMS who had neuropsychological testing and quantitative MRI within 1 year of each were retrospectively identified. Grouped LASSO linear regression with 10-fold cross validation was used to estimate each neuropsychological test score with thalamic volume as the focal predictor and all other demographic and MRI metrics as covariates. RESULTS: Rates of impairment ranged from 19% to 44%. Results showed notable associations between thalamic volume and Symbol Digit Modalities Test (ß = 0.11), Brief Visuospatial Memory Test, delayed (ß = 0.12), California Verbal Learning Test, delayed and total (ß = 0.24 and ß = 0.15 respectively), and Trail Making Test Part A (ß = -0.01), after adjusting for covariates. CONCLUSIONS: These findings demonstrate an independent association between thalamic volumes and processing speed and memory performance, after accounting for demographic, clinical, and other MRI variables, among pwMS.

Brain volume increase after discontinuing natalizumab therapy: Evidence for reversible pseudoatrophy.

BACKGROUND: The phenomenon of pseudoatropy after initiation of anti-inflammatory therapy is believed to be reversible, but a rebound in brain volume following cessation of highly-effective therapy has not been reported. OBJECTIVES: To evaluate brain volume change in a treatment interruption study (RESTORE) in which relapsing-remitting multiple sclerosis (RRMS) patients were randomized to switch from natalizumab to placebo, from natalizumab to once-monthly intravenous methylprednisolone (IVMP), or to remain on natalizumab. METHODS: T2 lesion volume (T2LV), baseline normalized brain volumes, and follow-up percent brain volume changes (PBVC) were calculated. Approximate T2 relaxation-time (pT2) was calculated within the brain mask and the T2 lesions to estimate changes in water content. Linear mixed effects models were used to detect differences in T2LV, pT2 in whole brain, pT2 in T2-weighted lesions, and PBVC among the placebo, natalizumab, and IVMP groups. We also estimated contributions of T2LV and pT2 (in whole brain and T2 lesions) to PBVC. RESULTS: T2LV increased in the placebo group (by 0.66 ml/year, p<0.0001) and IVMP (+1.98 ml/year, p = 0.05) groups relative to the natalizumab group. The rates of PBVC were significantly different: -0.239%/year with continued natalizumab and +0.126 %/year after switch to placebo (p = 0.03), while the IVMP group showed brain volume loss (-0.74 %/ year, p = 0.08). pT2 was not statistically different between the groups (p ≥ 0.29) and did not have significant effects on PBVC (p ≥ 0.25). CONCLUSION: The increase in the brain volume in patients witching from natalizumab to placebo is consistent with reversal of so-called pseudoatrophy after starting natalizumab.

Magnetic resonance fingerprinting in multiple sclerosis.

BACKGROUND: In this cross sectional study, we used MRF to investigate tissue properties of normal-appearing white matter, gray matter, and lesions in relapsing remitting MS (n = 21), secondary progressive MS (n = 16) and healthy controls (n = 9). A FISP-based MRF sequence was used for acquisition, imaging time 5 min 15 s. MRF T1 and T2 relaxation times were measured from lesional tissue, normal-appearing frontal white matter, corpus callous, thalamus, and caudate. Differences between healthy controls and MS were examined using ANCOVA adjusted for age and sex. Spearman rank correlations were assessed between T1 and T2 relaxation times and clinical measures. OBJECTIVES: To examine brain T1 and T2 values using magnetic resonance fingerprinting (MRF) in healthy controls and MS. METHODS: The subjects included 21 relapsing-remitting (RR) MS, 16 secondary progressive (SP) MS, and 9 age- and sex-matched HC without manifest neurological disease participating in a longitudinal MRI study. A 3T/ FISP-based MRF sequence was acquired. Regions of interest were drawn for lesions and normal appearing white matter. ANCOVA adjusted for age and sex were used to compare the groups with significance set at 0.05. RESULTS: A step-wise increase in T1 and T2 relaxation times was found between healthy controls, relapsing remitting MS, and secondary progressive MS. Significant differences were found in T1 and T2 between MS and healthy controls in the frontal normal-appearing white matter, corpus callosum, and thalamus (p < 0.04 for all). Significant differences in T1 and T2 between RR and SPMS were found in the frontal normal-appearing white matter and T2 lesions (p < 0.02 for all). T1 relaxation from the frontal normal-appearing white matter correlated with the Expanded Disability Status Scale [ρ = 0.62, p < 0.001], timed 25 foot walk (ρ = 0.45, p = 0.01), 9 hole peg test (ρ = 0.62, p < 0.001), and paced auditory serial addition test (ρ = -0.4, p = 0.01). CONCLUSION: These results suggest that MRF may be a clinically feasible quantitative approach for characterizing tissue damage in MS.

Effect of ibudilast on thalamic magnetization transfer ratio and volume in progressive multiple sclerosis.

BACKGROUND: Thalamic volume (TV) is a sensitive biomarker of disease burden of injury in multiple sclerosis (MS) and appears to reflect overall lesion loads. Ibudilast showed significant treatment effect on brain atrophy and magnetization transfer ratio (MTR) of normal-appearing brain tissue but not in new/enlarging T2 lesion in the SPRINT-MS randomized clinical trial. OBJECTIVE: To evaluate the effect of ibudilast on thalamic tissue integrity and volume in the SPRINT-MS. METHODS: A total of 255 participants with progressive MS were randomized to oral ibudilast or placebo, and thalamic MTR and normalized TV over 96 weeks were quantified. Mixed-effect modeling assessed treatment effects on the thalamic MTR and TV, separately. Similarly, the measures were compared between the participants with confirmed disability progression (CDP). RESULTS: Ibudilast's treatment effect was observed compared to placebo for thalamic MTR (p = 0.03) but not for TV (p = 0.68) while TV correlated with T2 lesion volume (p < 0.001). CDP associated with thalamic MTR (p = 0.04) but not with TV (p = 0.7). CONCLUSION: Ibudilast showed an effect on thalamic MTR, which was associated with CDP, suggesting a clinically relevant effect on thalamic tissue integrity. However, the treatment effect was not observed in TV, suggesting that thalamic atrophy is more closely associated with global inflammatory activity than local tissue integrity. CLINICALTRIALS.GOV: NCT01982942.

The impact of cigarette smoking on cognitive processing speed and brain atrophy in multiple sclerosis.

BACKGROUND: Smoking is associated with an increased risk of multiple sclerosis (MS) and disability worsening. The relationship between smoking, cognitive processing speed, and brain atrophy remains uncertain. OBJECTIVE: To quantify the impact of smoking on processing speed and brain volume in MS and to explore the longitudinal relationship between smoking and changes in processing speed. METHODS: A retrospective study of MS patients who completed the processing speed test (PST) between September 2015 and March 2020. Demographics, disease characteristics, smoking history, and quantitative magnetic resonance imaging (MRI) were collected. Cross-sectional associations between smoking, PST performance, whole-brain fraction (WBF), gray matter fraction (GMF), and thalamic fraction (TF) were assessed using multivariable linear regression. The longitudinal relationship between smoking and PST performance was assessed by linear mixed modeling. RESULTS: The analysis included 5536 subjects of whom 1314 had quantitative MRI within 90 days of PST assessment. Current smokers had lower PST scores than never smokers at baseline, and this difference persisted over time. Smoking was associated with reduced GMF but not with WBF or TF. CONCLUSION: Smoking has an adverse relationship with cognition and GMF. Although causality is not demonstrated, these observations support the importance of smoking cessation counseling in MS management.

Quantitative CTA vascular calcification, atherosclerosis burden, and stroke mechanism in patients with ischemic stroke.

BACKGROUND: Vascular calcification is recognized as the advanced stage of atherosclerosis burden. We hypothesized that vascular calcium quantification in CT angiography (CTA) would be helpful to differentiate large artery atherosclerosis (LAA) from other stroke etiology in patients with ischemic stroke. METHODS: We studied 375 acute ischemic stroke patients (200 males, mean age 69.9 years) who underwent complete CTA images of the aortic arch, neck, and head. The automatic artery and calcification segmentation method measured calcification volumes in the intracranial internal carotid artery (ICA), cervical carotid artery, and aortic arch using deep-learning U-net model and region-grow algorithms. We investigated the correlations and patterns of vascular calcification in the different vessel beds among stroke etiology by age category (young: <65 years, intermediate: 65-74 years, older ≥75 years). RESULTS: Ninety-five (25.3%) were diagnosed with LAA according to TOAST criteria. Median calcification volumes were higher by increasing the age category in each vessel bed. One-way ANOVA with Bonferroni correction showed calcification volumes in all vessel beds were significantly higher in LAA compared with other stroke subtypes in the younger subgroup. Calcification volumes were independently associated with LAA in intracranial ICA (OR; 2.89, 95% CI 1.56-5.34, P = .001), cervical carotid artery (OR; 3.40, 95% CI 1.94-5.94, P < .001) and aorta (OR; 1.69, 95%CI 1.01-2.80, P = .044) in younger subsets. By contrast, the intermediate and older subsets did not show a significant relationship between calcification volumes and stroke subtypes. CONCLUSION: Atherosclerosis calcium volumes in major vessels were significantly higher in LAA compared to non-LAA stroke in younger age.

Identification of acute aortic syndromes based on cross-sectional variability of Hounsfield units.

BACKGROUND: A characteristic feature of communicating aortic dissections (CD) is the dissection flap between the true and false lumen. However, in intramural hematomas (IMH) a flap is not visible. We aimed to determine if cross-sectional HU variability allow reliable identification of aortic dissections including IMH. METHODS: We included 362 patients presenting with acute chest pain (CP) or respiratory distress (RD) and underwent contrast-enhanced CTA with or without ECG-gating. In the derivation group we included 72 CP patients with and 74 without AAS. In the validation group we included 108 CP or RD patients with and 108 without AAS. The adventitial border of the aorta was visually identified and measurements were performed at 6 locations along the ascending and descending aorta. At each cross-section 5 circular ROI measurements of HU were made and the maximum HU difference calculated. RESULTS: In the derivation and validation group the maximum difference in HUs at any one location was significantly higher for AAS subjects than controls (validation group: median = 128.5 vs. 34.0, p-value Wilcoxon two-sample test <0.001). In the validation group, the estimated AUC was 0.939 with 95% CIs of [0.906, 0.972], indicating that the maximum difference in HUs is a strong predictor of AAS (p < 0.001). CONCLUSION: Our data provide evidence that cross-sectional variability of Hounsfield Unit reliably identifies aortic dissection including IMH in dedicated ECG-gated aorta scans but also non-gated chest CTs with limited aortic contrast enhancement. These results suggest that this approach could be feasible for an automated algorithm for identification of AAS.

Deep learning-based automatic pipeline for quantitative assessment of thigh muscle morphology and fatty infiltration.

PURPOSE: Fast and accurate thigh muscle segmentation from MRI is important for quantitative assessment of thigh muscle morphology and composition. A novel deep learning (DL) based thigh muscle and surrounding tissues segmentation model was developed for fully automatic and reproducible cross-sectional area (CSA) and fat fraction (FF) quantification and tested in patients at 10 years after anterior cruciate ligament reconstructions. METHODS: A DL model combining UNet and DenseNet was trained and tested using manually segmented thighs from 16 patients (32 legs). Segmentation accuracy was evaluated using Dice similarity coefficients (DSC) and average symmetric surface distance (ASSD). A UNet model was trained for comparison. These segmentations were used to obtain CSA and FF quantification. Reproducibility of CSA and FF quantification was tested with scan and rescan of six healthy subjects. RESULTS: The proposed UNet and DenseNet had high agreement with manual segmentation (DSC >0.97, ASSD < 0.24) and improved performance compared with UNet. For hamstrings of the operated knee, the automated pipeline had largest absolute difference of 6.01% for CSA and 0.47% for FF as compared to manual segmentation. In reproducibility analysis, the average difference (absolute) in CSA quantification between scan and rescan was better for the automatic method as compared with manual segmentation (2.27% vs. 3.34%), whereas the average difference (absolute) in FF quantification were similar. CONCLUSIONS: The proposed method exhibits excellent accuracy and reproducibility in CSA and FF quantification compared with manual segmentation and can be used in large-scale patient studies.

"It's on the tip of my tongue!" exploring confrontation naming difficulties in patients with multiple sclerosis.

BACKGROUND: Naming difficulty is commonly reported by patients with multiple sclerosis (pwMS). Though many cognitive batteries recommended for pwMS include fluency tasks, they do not include naming tasks. The aim of this study was to examine the prevalence of naming impairment in pwMS by using a measure of confrontation naming and to identify correlates with neuroimaging. METHODS: One-hundred-eighty-five pwMS (Mage = 48.75 ± 11.23) completed neuropsychological testing and fifty had brain MRI scans within one year of neuropsychological testing. Controlling for demographic variables, partial correlations and hierarchical regressions with language tests as the outcome variables and neuroimaging variables as predictors were performed. RESULTS: Performance on language tasks ranged within low average to average, with impairment most frequently found on a measure of confrontation naming (Boston Naming Test [BNT];27.6%), followed by a measure of phonemic fluency (Controlled Oral Word Association Test [COWAT]; 24.3%) and semantic fluency (animals [AF]; 18.3%). In the subset of patients with neuroimaging, thalamic volume had the strongest relationship with language variables, followed by white matter volume and T2 lesion volume. Language variables had no association with fractional gray matter volume. Of the language measures, BNT demonstrated the strongest relationship with MRI variables, followed by AF. There were no significant associations between neuroimaging variables and COWAT. Regression results revealed that fractional thalamic volume significantly contributed to BNT scores after adjusting for demographics, while T2 lesion volume predicted AF and no neuroimaging variables emerged as predictors for COWAT after controlling for demographics. CONCLUSIONS: Objective naming impairment is common in pwMS and are more strongly associated with neuroimaging of MS brain pathology than verbal fluency tasks that are commonly used in cognitive batteries for pwMS. Continued research on language (especially naming) deficits and neuroimaging correlates (particularly thalamic involvement) in pwMS is needed.

Gadolinium-based contrast agent exposures and physical and cognitive disability in multiple sclerosis.

BACKGROUND AND PURPOSE: The clinical correlation of gadolinium-based contrast agents (GBCAs) has not been well studied in multiple sclerosis (MS). We investigated the extent to which the number of GBCA administrations relates to self-reported disability and performance measures. METHODS: A cohort of MS patients was analyzed in this retrospective observational study. The main outcome was the association between the cumulative number of GBCA exposures (linear or macrocyclic GBCA), Patient-Determined Disease Steps (PDDS), and measures of physical and cognitive performance (walking speed test, manual dexterity test [MDT], and processing speed test [PST]). The analysis was performed first cross-sectionally and then longitudinally. RESULTS: The cross-sectional data included 1059 MS patients with a mean age of 44.0 years (standard deviation = 11.2). While the contrast ratio in globus pallidus weakly correlated with PDDS, MDT, and PST in a univariate correlational analysis (coefficients, 95% confidence interval [CI] = 0.11 [0.04, 0.18], 0.15 [0.08, 0.21], and -0.16 [-0.10, -0.23], respectively), the associations disappeared after covariate adjustment. A significant association was found between number of linear GBCA administrations and PDDS (coefficient [CI] = -0.131 [-0.196, -0.067]), and MDT associated with macrocyclic GBCA administrations (-0.385 [-0.616, -0.154]), but their signs indicated better outcomes in patients with greater GBCA exposures. The longitudinal data showed no significant detrimental effect of macrocyclic GBCA exposures. CONCLUSION: No detrimental effects were observed between GBCA exposure and self-reported disability and standardized objective measures of physical and cognitive performance. While several weak associations were found, they indicated benefit on these measures.

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

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

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.