Conventional imaging methods, such as CT and MRI, are limited in evaluating GIST response to imatinib, as they mainly reflect tumor size and fail to capture early metabolic or molecular changes. This study investigates GISTs from a metabolic perspective by integrating hyperpolarized (HP) 13C-MRI, metabolomics, and radiomics. HP 13C-MRI enables real-time monitoring of metabolic flux in vivo, while NMR-based metabolomics provides systemic insights. In this single-center, prospective observational cohort study, 30 GIST patients receiving imatinib will undergo pre-treatment CT, HP 13C-MRI, metabolomics, and biopsy. Early response will be assessed at one month, with routine evaluation at four months. Patients will be categorized as responders or non-responders, and multi-omics data will be analyzed using machine learning. The study hypothesizes that metabolic changes detected by HP 13C-MRI can predict treatment response, offering reproducible, quantifiable metrics to improve evaluation and patient care.