Concurrent administration of serotonergic antidepressants and ozanimod in participants with relapsing multiple sclerosis from the open-label extension DAYBREAK trial.

BACKGROUND: Monoamine oxidase (MAO) inhibitors can interact with selective serotonin reuptake inhibitors (SSRIs)/serotonin-norepinephrine reuptake inhibitors (SNRIs). There is clinical interest surrounding use of ozanimod with SSRIs/SNRIs because the major metabolites of ozanimod are weak inhibitors of MAO-B in vitro. OBJECTIVE: To evaluate the incidence of treatment-emergent adverse events (TEAEs) potentially related to serotonin accumulation (SA) during concomitant ozanimod and SSRI/SNRI use by performing analyses of data from an open-label, oral ozanimod 0.92 mg trial (DAYBREAK; NCT02576717). METHODS: SA narrow (serotonin syndrome, neuroleptic malignant syndrome, and hyperthermia malignant) and broad (terms potentially associated with SA) MedDRA v24.0 searches were performed using TEAE data from participants with relapsing multiple sclerosis who entered DAYBREAK from phase 3 studies (cutoff February 1, 2022). Incidences of TEAEs matching terms from each search were stratified by SSRI/SNRI use. RESULTS: Of 2257 DAYBREAK participants, 274 (12.1%) used an SSRI/SNRI. No participants had TEAEs matching the SA narrow search terms. There was no significant difference in the percentage of participants with ⩾1 TEAE matching the SA broad search for those on versus off SSRIs/SNRIs (on: 12.4%, n = 34/274; off: 15.6%, n = 310/1982, nominal p = 0.1630). CONCLUSION: MedDRA searches showed no increase in TEAEs potentially associated with SA with concomitant SSRI/SNRI and ozanimod use.

Thalamic atrophy measured by artificial intelligence in a multicentre clinical routine real-word study is associated with disability progression.

BACKGROUND: The thalamus is a key grey matter structure, and sensitive marker of neurodegeneration in multiple sclerosis (MS). Previous reports indicated that thalamic volumetry using artificial intelligence (AI) on clinical-quality T2-fluid-attenuated inversion recovery (FLAIR) images alone is fast and reliable. OBJECTIVE: To investigate whether thalamic volume (TV) loss, measured longitudinally by AI, is associated with disability progression (DP) in patients with MS, participating in a large multicentre study. METHODS: The DeepGRAI (Deep Grey Rating via Artificial Intelligence) Registry is a multicentre (30 USA sites), longitudinal, observational, retrospective, real-word study of relapsing-remitting (RR) MS patients. Each centre enrolled between 30 and 35 patients. Brain MRI exams acquired at baseline and follow-up on 1.5T or 3T scanners with no prior standardisation were collected. TV measurement was performed on T2-FLAIR using DeepGRAI, and on two dimensional (D)-weighted and 3D T1-weighted images (WI) by using FMRIB's Integrated Registration and Segmentation Tool software where possible. RESULTS: 1002 RRMS patients were followed for an average of 2.6 years. Longitudinal TV analysis was more readily available on T2-FLAIR (96.1%), compared with 2D-T1-WI (61.8%) or 3D-T1-WI (33.2%). Over the follow-up, DeepGRAI TV loss was significantly higher in patients with DP, compared with those with disability improvement (DI) or disease stability (-1.35% in DP, -0.87% in DI and -0.57% in Stable, p=0.045, Bonferroni-adjusted, age-adjusted and follow-up time-adjusted analysis of covariance). In a regression model including MRI scanner change, age, sex, disease duration and follow-up time, DP was associated with DeepGRAI TV loss (p=0.022). CONCLUSIONS: Thalamic atrophy measured by AI in a multicentre clinical routine real-word setting is associated with DP over mid-term follow-up.

Thalamic atrophy and dysconnectivity are associated with cognitive impairment in a multi-center, clinical routine, real-word study of people with relapsing-remitting multiple sclerosis.

BACKGROUND: Prior research has established a link between thalamic pathology and cognitive impairment (CI) in people with multiple sclerosis (pwMS). However, the translation of these findings to pwMS in everyday clinical settings has been insufficient. OBJECTIVE: To assess which global and/or thalamic imaging biomarkers can be used to identify pwMS at risk for CI and cognitive worsening (CW) in a real-world setting. METHODS: This was an international, multi-center (11 centers), longitudinal, retrospective, real-word study of people with relapsing-remitting MS (pwRRMS). Brain MRI exams acquired at baseline and follow-up were collected. Cognitive status was evaluated using the Symbol Digit Modalities Test (SDMT). Thalamic volume (TV) measurement was performed on T2-FLAIR, as well as on T1-WI, when available. Thalamic dysconnectivity, T2-lesion volume (T2-LV), and volumes of gray matter (GM), whole brain (WB) and lateral ventricles (LVV) were also assessed. RESULTS: 332 pwMS were followed for an average of 2.8 years. At baseline, T2-LV, LVV, TV and thalamic dysconnectivity on T2-FLAIR (p < 0.016), and WB, GM and TV volumes on T1-WI (p < 0.039) were significantly worse in 90 (27.1 %) CI vs. 242 (62.9 %) non-CI pwRRMS. Greater SDMT decline over the follow-up was associated with lower baseline TV on T2-FLAIR (standardized ß = 0.203, p = 0.002) and greater thalamic dysconnectivity (standardized ß = -0.14, p = 0.028) in a linear regression model. CONCLUSIONS: PwRRMS with thalamic atrophy and worse thalamic dysconnectivity present more frequently with CI and experience greater CW over mid-term follow-up in a real-world setting.

Therapy effect on AI-derived thalamic atrophy using clinical routine MRI protocol: A longitudinal, multi-center, propensity-matched multiple sclerosis study.

BACKGROUND: The effect of disease modifying therapies (DMTs) on brain atrophy in persons with multiple sclerosis (pwMS) is typically investigated in highly standardized clinical trial settings or single-center academic institutions. We aimed at utilizing artificial intelligence (AI)-based volumetric analysis on routine unstandardized T2-FLAIR scans in determining the effect of DMTs on lateral ventricular volume (LVV) and thalamic volume (TV) changes in pwMS. METHODS: The DeepGRAI (Deep Gray Rating via Artificial Intelligence) registry is a multi-center, longitudinal, observational, real-word study with a convenience sample of 1002 relapsing-remitting (RR) pwMS from 30 United States sites. Brain MRI exams acquired as part of the routine clinical management were collected at baseline and on average at 2.6-years follow-up. The MRI scans were acquired either on 1.5T or 3T scanners with no prior harmonization. TV was determined using the DeepGRAI tool and lateral ventricular volume LVV was measured using NeuroSTREAM software. RESULTS: After propensity matching based on baseline age, disability and time of follow-up, untreated pwRRMS had significantly greater TV change when compared to treated pwRRMS (-1.2% vs. -0.3%, p = 0.044). PwRRMS treated with high-efficacy DMTs had significant and two-fold lower% LVV change when compared to pwRRMS treated on moderate-efficacy DMTs (3.5% vs. 7.0%, p = 0.001). PwRRMS who stopped DMT during the follow-up had significantly greater annualized% TV change compared to pwRRMS who remained on their DMT (-0.73% vs. -0.14%, p = 0.012) and significantly greater annualized% LVV change (3.4% vs. 1.7%, p = 0.047). These findings were also observed in a propensity analysis that additionally incorporated matching for scanner model at both baseline and follow-up visits. CONCLUSIONS: LVV and TV measured on T2-FLAIR scans can detect treatment-induced short-term neurodegenerative changes measured in a real-word unstandardized, multicenter, clinical routine setting.

DeepGRAI (Deep Gray Rating via Artificial Intelligence): Fast, feasible, and clinically relevant thalamic atrophy measurement on clinical quality T2-FLAIR MRI in multiple sclerosis.

BACKGROUND: Thalamic volume loss is a key marker of neurodegeneration in multiple sclerosis (MS). T2-FLAIR MRI is a common denominator in clinical routine MS imaging, but current methods for thalamic volumetry are not applicable to it. OBJECTIVE: To develop and validate a robust algorithm to measure thalamic volume using clinical routine T2-FLAIR MRI. METHODS: A dual-stage deep learning approach based on 3D U-net (DeepGRAI - Deep Gray Rating via Artificial Intelligence) was created and trained/validated/tested on 4,590 MRI exams (4288 2D-FLAIR, 302 3D-FLAIR) from 59 centers (80/10/10 train/validation/test split). As training/test targets, FIRST was used to generate thalamic masks from 3D T1 images. Masks were reviewed, corrected, and aligned into T2-FLAIR space. Additional validation was performed to assess inter-scanner reliability (177 subjects at 1.5 T and 3 T within one week) and scan-rescan-reliability (5 subjects scanned, repositioned, and then re-scanned). A longitudinal dataset including assessment of disability and cognition was used to evaluate the predictive value of the approach. RESULTS: DeepGRAI automatically quantified thalamic volume in approximately 7 s per case, and has been made publicly available. Accuracy on T2-FLAIR relative to 3D T1 FIRST was 99.4% (r = 0.94, p < 0.001,TPR = 93.0%, FPR = 0.3%). Inter-scanner error was 3.21%. Scan-rescan error with repositioning was 0.43%. DeepGRAI-derived thalamic volume was associated with disability (r = -0.427,p < 0.001) and cognition (r = -0.537,p < 0.001), and was a significant predictor of longitudinal cognitive decline (R2 = 0.081, p = 0.024; comparatively, FIRST-derived volume was R2 = 0.080, p = 0.025). CONCLUSIONS: DeepGRAI provides fast, reliable, and clinically relevant thalamic volume measurement on multicenter clinical-quality T2-FLAIR images. This indicates potential for real-world thalamic volumetry, as well as quantification on legacy datasets without 3D T1 imaging.

Effects of testosterone metabolites on copulation, medial preoptic dopamine, and NOS-immunoreactivity in castrated male rats.

The medial preoptic area (MPOA) is an important integrative site for male sexual behavior. Dopamine (DA) is released in the MPOA of male rats shortly before and during copulation. In a previous study, we identified 17beta-estradiol (E(2)) as the metabolite of testosterone (T) that maintains MPOA basal extracellular DA levels. However, the presence of dihydrotestosterone (DHT), an androgenic metabolite of T, is required for the female-induced increase in MPOA DA observed during copulation. Recently, we reported that assays of MPOA tissue DA content showed that castrates actually had more stored DA than did gonadally intact males. Therefore, the reduction in extracellular levels in castrates was not due to decreased availability of DA; most likely it was due to decreased release. Furthermore, T upregulates neuronal nitric oxide synthase (nNOS) in the MPOA. NO has been implicated in the regulation of DA release in the MPOA. It is not known, however, which metabolite(s) of T regulate(s) tissue stores of DA and/or nNOS in the MPOA of male rats. The present experiments were designed to test the following: (1) whether E(2), DHT, or the combination of the two influences MPOA DA tissue levels, an indication of stored DA, in male rat castrates; and (2) whether E(2), DHT, or the combination of the two influences NOS-ir in the MPOA of castrated male rats. The results indicate that E(2) up-regulates nNOS-ir in the MPOA and maintains tissue content of DA at levels similar to those in T-treated rats. DHT did not influence nNOS-ir, while attenuating the effect of castration on tissue DA content.