Clinical Research Directory

Immune Checkpoint Inhibitor Nivolumab in People With Recurrent Select Rare CNS Cancers

Background: More than 130 primary tumors of the central nervous system (CNS) have been identified. Most affect less than 1,000 people in the United States each year. Because these tumors are so rare, there are few proven therapies. This study will test whether the immunotherapy drug nivolumab is an effective treatment for people with rare CNS tumors. Objectives: To learn if stimulating the immune system using the drug nivolumab can shrink tumors in people with rare CNS (brain or spine) tumors or increase the time it takes for these tumors to grow or spread. Eligibility: Adults whose rare CNS tumor has returned. Design: Individuals will be screened: * Heart and blood tests * Physical and neurological exam * Hepatitis tests * Pregnancy test * Magnetic resonance imaging (MRI). They will lay in a machine that takes pictures. * Tumor tissue sample. This can be from a previous procedure. At the start of the study, participants will have blood tests. They will answer questions about their symptoms and their quality of life. Individuals will get nivolumab in a vein every 2 weeks for up to 64 weeks. Individuals will have monthly blood tests. Every other month they will have an MRI and a neurologic function test. They will also answer questions about their quality of life. Genetic tests will be done on individuals' tumor tissue. Individuals will be contacted if any clinically important results are found. After treatment ends, individuals will be monitored for up to 5 years. They will have a series of MRIs and neurological function tests. They will be asked to report any symptoms they experience....

AI-Assisted MRI Molecular Subtyping in Pediatric Brain Tumors

This multicenter observational cohort study aims to develop and validate an artificial intelligence (AI)-assisted diagnostic system for preoperative molecular subtyping of pediatric brain tumors using routine magnetic resonance imaging (MRI). The study will include seven major pediatric brain tumor categories: glioma, medulloblastoma, ependymoma, atypical teratoid/rhabdoid tumor (AT/RT), intracranial germ cell tumors, craniopharyngioma, and choroid plexus tumors. The study includes a retrospective cohort for model development and internal/external validation, and a prospective cohort for further validation. Retrospective data will be collected from pediatric patients who underwent first surgical treatment between January 1, 2020 and December 31, 2025. Prospective enrollment will begin on July 15, 2026, with an anticipated sample size of 150 participants. The AI system will analyze preoperative MRI sequences, including T1-weighted, contrast-enhanced T1-weighted, T2-weighted, and FLAIR images, to predict key molecular markers and integrated diagnostic categories. The primary objective is to evaluate the diagnostic performance of the AI system for prespecified molecular prediction tasks using postoperative histopathology and molecular testing as the reference standard. Secondary objectives include assessing agreement with integrated diagnosis, comparing performance against blinded radiologists, and exploring prognostic associations of AI-predicted subgroups.