Abstract
Multiple Sclerosis (MS) is a chronic autoimmune disease that primarily affects the central nervous system and is predominantly diagnosed in adults, making pediatric cases rare and underrepresented in medical research. This paper introduces the first publicly available MRI dataset specifically dedicated to pediatric multiple sclerosis lesion segmentation. The dataset comprises longitudinal MRI scans from 9 pediatric patients, each with between one and six timepoints, with a total of 28 MRI scans. It includes T1-weighted (MPRAGE), T2-weighted, and FLAIR sequences. Additionally, it provides clinical data and initial symptoms for each patient, offering valuable insights into disease progression. Lesion segmentation was performed by senior experts, ensuring high-quality annotations. To demonstrate the dataset's reliability and utility, we evaluated two deep learning models, achieving competitive segmentation performance. This dataset aims to advance research in pediatric MS, improve lesion segmentation models, and contribute to federated learning approaches.