Leorah Freeman’s research while affiliated with University of Texas at Austin and other places

Background and Purpose The central vein sign (CVS) is a diagnostic imaging biomarker for multiple sclerosis (MS). FLAIR* is a combined MRI contrast that provides high conspicuity for CVS at 3 Tesla (3T), enabling its sensitive and accurate detection in clinical settings. This study evaluated whether CVS conspicuity of 3T FLAIR* is reliable across imaging sites and MRI vendors and whether gadolinium (Gd) contrast increases CVS conspicuity. Methods A cross‐sectional, multicenter study recruited adults referred for possible diagnosis of MS at 10 sites. FLAIR* contrast was generated using high‐resolution T2*‐weighted (acquired pre‐ and post‐injection of Gd) and T2‐weighted fluid‐attenuated inversion recovery (T2‐FLAIR) brain images at 3T from two MRI vendors. Lesions and veins were segmented to compute lesion‐to‐vein contrast‐to‐noise ratio (CNR lesion‐to‐vein ), a quantitative measure of CVS conspicuity. CNR lesion‐to‐vein measures for pre‐ and post‐Gd FLAIR* were compared across sites and vendors. Results Eighty‐seven participants from nine sites were included in the analysis. There was no significant difference in mean CNR lesion‐to‐vein between sites for pre‐Gd ( p ‐value = 0.07) or post‐Gd ( p ‐value = 0.27) FLAIR*. There were also no significant differences between vendors for pre‐Gd ( p ‐value = 0.10) or post‐Gd ( p ‐value = 0.31) FLAIR*. Patient‐level pairwise differences in CNR lesion‐to‐vein between pre‐Gd and post‐Gd FLAIR* revealed a significant increase for post‐Gd FLAIR* ( p ‐value < 0.001). Conclusions CVS conspicuity on 3T FLAIR* is consistent across imaging sites and MRI vendors. Moreover, Gd‐based contrast agent significantly improved CVS conspicuity on 3T FLAIR*. These findings support the implementation of FLAIR* in clinical settings for MS.

Background and Purpose Paramagnetic rim lesions (PRLs) are an MRI biomarker of chronic inflammation in people with multiple sclerosis (MS). PRLs may aid in the diagnosis and prognosis of MS. However, manual identification of PRLs is time‐consuming and prone to poor interrater reliability. To address these challenges, the Automated Paramagnetic Rim Lesion (APRL) algorithm was developed to automate PRL detection. The primary objective of this study is to evaluate the accuracy of APRL for detecting PRLs in a multicenter setting. Methods We applied APRL to a multicenter dataset, which included 3‐Tesla MRI acquired in 92 participants (43 with MS, 14 with clinically isolated syndrome [CIS]/radiologically isolated syndrome [RIS], 35 without RIS/CIS/MS). Subsequently, we assessed APRL's performance by comparing its results with manual PRL assessments carried out by a team of trained raters. Results Among the 92 participants, expert raters identified 5637 white matter lesions and 148 PRLs. The automated segmentation method successfully captured 115 (78%) of the manually identified PRLs. Within these 115 identified lesions, APRL differentiated between manually identified PRLs and non‐PRLs with an area under the curve (AUC) of .73 (95% confidence interval [CI]: [.68, .78]). At the subject level, the count of APRL‐identified PRLs predicted MS diagnosis with an AUC of .69 (95% CI: [.57, .81]). Conclusion Our study demonstrated APRL's capability to differentiate between PRLs and lesions without paramagnetic rims in a multicenter study. Automated identification of PRLs offers greater efficiency over manual identification and could facilitate large‐scale assessments of PRLs in clinical trials.

Background and objectives Studies measuring the role of magnetic resonance imaging (MRI) in therapeutic decision-making are rare in people with multiple sclerosis (pwMS). This study aimed to measure the association between MRI utilization and disease-modifying therapy (DMT) switches in pwMS. Methods This retrospective cohort study identified pwMS in 2018 from a de-identified national claims database. PwMS who received MRI in 2018 were compared to pwMS not receiving MRI in 2018. PwMS were observed for six months to assess the incidence of DMT switches. Results The study sample consisted of 11,972 pwMS. 3,931 (32.8%) pwMS received at least one MRI in 2018. Overall, MRI utilization increased the odds of switching DMT (OR = 1.49, 1.79, and 3.01 for 1, 2, and ≥ 3 CNS locations imaged). For those on injectable or platform DMT, any MRI utilization increased the odds of switching DMT (OR = 1.54, 2.00, and 3.48 for 1, 2, and ≥ 3 locations imaged). For those on oral DMT, only receiving MRI of 2 or ≥ 3 locations increased the odds of a DMT switch (OR = 1.36, 1.89, and 2.40 for 1, 2, and ≥ 3 locations). Finally, for pwMS on infusible therapies, there was little evidence that MRI changed the odds of a DMT switch. Discussion Among pwMS on injectable or oral DMT, imaging more CNS locations increased the odds of switching DMT after adjusting for age and relapse incidence. For pwMS on high-efficacy infusible DMTs, MRI did not change the odds of switching DMT but remains essential for safety monitoring.

Background and purpose: The central vein sign (CVS) is a proposed diagnostic imaging biomarker for multiple sclerosis (MS). The proportion of white matter lesions exhibiting the CVS (CVS+) is higher in patients with MS compared to its radiological mimics. Evaluation for CVS+ lesions in prior studies have been performed by manual rating, an approach that is time-consuming and has variable inter-rater reliability. Accurate automated methods would facilitate efficient assessment for CVS. The objective of this study was to compare the performance of an automated CVS detection method with manual rating for the diagnosis of MS. Materials and methods: 3T MRI was acquired in 86 participants undergoing evaluation for MS in a 9-site multicenter study. Participants presented with either typical or atypical clinical syndromes for MS. An automated CVS detection method was employed and compared to manual rating, including total CVS+ proportion and a simplified counting method in which experts visually identified up to 6 CVS+ lesions using FLAIR* contrast (a voxel-wise product of T2 FLAIR and post-contrast T2*-EPI images). Results: Automated CVS processing was completed in 79 of 86 participants (91%), of whom 28 (35%) fulfilled the 2017 McDonald criteria at the time of imaging. The area under the receiver-operator characteristic curve (AUC) for discrimination between participants with and without MS for the automated CVS approach was 0.78 (95% confidence interval: [0.67,0.88]). This was not significantly different from simplified manual counting methods (select6*) (0.80 [0.69,0.91]) or manual assessment of total CVS+ proportion (0.89 [0.82,0.96]). In a sensitivity analysis excluding 11 participants whose MRI exhibited motion artifact, the AUC for the automated method was 0.81 [0.70,0.91], which was not statistically different from that for select6* (0.79 [0.68,0.92]) or manual assessment of total CVS+ proportion (0.89 [0.81,0.97]). Conclusions: Automated CVS assessment was comparable to manual CVS scoring for differentiating patients with MS from those with other diagnoses. Large, prospective, multicenter studies utilizing automated methods and enrolling the breadth of disorders referred for suspicion of MS are needed to determine optimal approaches for clinical implementation of an automated CVS detection method. Abbreviations: CVS= central vein sign; CVS+ = white matter lesions exhibiting the CVS; MRI = magnetic resonance imaging; MS = multiple sclerosis; T2 FLAIR = T2 fluid-attenuated inversion recovery; T2*-EPI = T2*-weighted 3D echo planar imaging; FLAIR* = a voxel-wise product of T2 FLAIR and post-contrast T2*-EPI images; select6* = simplified counting method in which experts visually identified up to 6 CVS+ lesions on FLAIR* imaging.

Background Cerebrospinal fluid (CSF) oligoclonal bands (OCB) are a diagnostic biomarker in multiple sclerosis (MS). The central vein sign (CVS) is an imaging biomarker for MS that may improve diagnostic accuracy. Objectives The objective of the study is to examine the diagnostic performance of simplified CVS methods in comparison to OCB in participants with clinical or radiological suspicion for MS. Methods Participants from the CentrAl Vein Sign in MS (CAVS-MS) pilot study with CSF testing were included. Select-3 and Select-6 (counting up to three or six CVS+ lesions per scan) were rated on post-gadolinium FLAIR* images. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value for Select-3, Select-6, OCB, and combinations thereof were calculated for MS diagnosis at baseline and at 12 months. Results Of 53 participants, 25 were OCB+. At baseline, sensitivity for MS diagnosis was 0.75 for OCB, 0.83 for Select-3, and 0.71 for Select-6. Specificity for MS diagnosis was 0.76 for OCB, 0.48 for Select-3, and 0.86 for Select-6. At 12 months, PPV for MS diagnosis was 0.95 for Select-6 and 1.00 for Select-6 with OCB+ status. Discussion Results suggest similar diagnostic performance of simplified CVS methods and OCB. Ongoing studies will refine whether CVS could be used in replacement or in conjunction with OCB.

Background People with multiple sclerosis (pwMS) are at risk of concurrently using multiple central nervous system (CNS)-active drugs, yet the prevalence of CNS-active polypharmacy remains unmeasured in pwMS. Objective The objective is to measure the prevalence of CNS-active polypharmacy in pwMS. Methods This serial, cross-sectional study measured CNS-active polypharmacy in people with MS in the United States from 2008 to 2021 using insurance claims data. CNS-active polypharmacy was defined as the concurrent prescription of ⩾3 CNS-active drugs for >30 continuous days. CNS-active drugs included antidepressants, antiepileptics, antipsychotics, benzodiazepines, nonbenzodiazepine benzodiazepine receptor agonist hypnotics, opioids, and skeletal muscle relaxants. Results The number of subjects included at each time point ranged from 23,917 subjects in 2008 to 55,797 subjects in 2021. In 2021, subjects with CNS-active polypharmacy were more likely to be 46–65 years of age and have CNS-related comorbidities compared to those without CNS-active polypharmacy. From 2008 to 2021, the age-adjusted prevalence of CNS-active polypharmacy among female subjects increased from 19.8% (95% confidence interval (CI) = 19.1–20.4) to 26.4% (95% CI = 25.9–26.8) versus 15.9% (95% CI = 14.8–17.0) to 18.6% (95% CI = 17.9–19.2) in male subjects. Conclusion The prevalence of CNS-active polypharmacy has increased among people with MS with a growing disparity by sex.

Background Effective and safe treatment options for multiple sclerosis (MS) are still needed. Montelukast, a leukotriene receptor antagonist (LTRA) currently indicated for asthma or allergic rhinitis, may provide an additional therapeutic approach. Objective The study aimed to evaluate the effects of montelukast on the relapses of people with MS (pwMS). Methods In this retrospective case–control study, two independent longitudinal claims datasets were used to emulate randomized clinical trials (RCTs). We identified pwMS aged 18–65 years, on MS disease-modifying therapies concomitantly, in de-identified claims from Optum’s Clinformatics® Data Mart (CDM) and IQVIA PharMetrics® Plus for Academics. Cases included 483 pwMS on montelukast and with medication adherence in CDM and 208 in PharMetrics Plus for Academics. We randomly sampled controls from 35,330 pwMS without montelukast prescriptions in CDM and 10,128 in PharMetrics Plus for Academics. Relapses were measured over a 2-year period through inpatient hospitalization and corticosteroid claims. A doubly robust causal inference model estimated the effects of montelukast, adjusting for confounders and censored patients. Results pwMS treated with montelukast demonstrated a statistically significant 23.6% reduction in relapses compared to non-users in 67.3% of emulated RCTs. Conclusion Real-world evidence suggested that montelukast reduces MS relapses, warranting future clinical trials and further research on LTRAs’ potential mechanism in MS.