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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. [ABSTRACT FROM AUTHOR]

Background and purpose: Cerebellar damage is a valuable predictor of disability, particularly in progressive multiple sclerosis. It is not clear if it could be an equally useful predictor of motor disability worsening in the relapsing‐remitting phenotype. Aim: We aimed to determine whether cerebellar damage is an equally useful predictor of motor disability worsening in the relapsing‐remitting phenotype. Methods: Cerebellar lesion loads and volumes were estimated using baseline magnetic resonance imaging from the CombiRx trial (n = 838). The relationship between cerebellar damage and time to disability worsening (confirmed disability progression [CDP], timed 25‐foot walk test [T25FWT] score worsening, nine‐hole peg test [9HPT] score worsening) was tested in stagewise and stepwise Cox proportional hazards models, accounting for demographics and supratentorial damage. Results: Shorter time to 9HPT score worsening was associated with higher baseline Expanded Disability Status Scale (EDSS) score (hazard ratio [HR] 1.408, p = 0.0042) and higher volume of supratentorial and cerebellar T2 lesions (HR 1.005 p = 0.0196 and HR 2.211, p = 0.0002, respectively). Shorter time to T25FWT score worsening was associated with higher baseline EDSS (HR 1.232, p = 0.0006). Shorter time to CDP was associated with older age (HR 1.026, p = 0.0010), lower baseline EDSS score (HR 0.428, p < 0.0001) and higher volume of supratentorial T2 lesions (HR 1.024, p < 0.0001). Conclusion: Among the explored outcomes, single time‐point evaluation of cerebellar damage only allows the prediction of manual dexterity worsening. In clinical studies the selection of imaging biomarkers should be informed by the outcome of interest. [ABSTRACT FROM AUTHOR]

The article focuses on the study conducted to examine the central nervous system myelin with the help of positron emission tomography. It states that the myelin repair occurs in demyelinating diseases, that allows restoration of rapid nerve conduction. Further it states that imaging of myelin tracts in vivo improves the monitoring of demyelinating diseases including multiple sclerosis.