RESUMEN
Objectives: To develop a mutation-based radiomics signature to predict response to imatinib in Gastrointestinal Stromal Tumors (GISTs). Methods: Eighty-two patients with GIST were enrolled in this retrospective study, including 52 patients from one center that were used to develop the model, and 30 patients from a second center to validate it. Reference standard was the mutational status of tyrosine-protein kinase (KIT) and platelet-derived growth factor α (PDGFRA). Patients were dichotomized in imatinib sensitive (group 0 - mutation in KIT or PDGFRA, different from exon 18-D842V), and imatinib non-responsive (group 1 - PDGFRA exon 18-D842V mutation or absence of mutation in KIT/PDGFRA). Initially, 107 texture features were extracted from the tumor masks of baseline computed tomography scans. Different machine learning methods were then implemented to select the best combination of features for the development of the radiomics signature. Results: The best performance was obtained with the 5 features selected by the ANOVA model and the Bayes classifier, using a threshold of 0.36. With this setting the radiomics signature had an accuracy and precision for sensitive patients of 82 % (95 % CI:60-95) and 90 % (95 % CI:73-97), respectively. Conversely, a precision of 80 % (95 % CI:34-97) was obtained in non-responsive patients using a threshold of 0.9. Indeed, with the latter setting 4 patients out of 5 were correctly predicted as non-responders. Conclusions: The results are a first step towards using radiomics to improve the management of patients with GIST, especially when tumor tissue is unavailable for molecular analysis or when molecular profiling is inconclusive.
RESUMEN
Cancer immunotherapy with immune-checkpoint inhibitors (ICIs) has emerged as an effective treatment for different types of cancer. ICIs are monoclonal antibodies that inhibit the signaling pathway that suppress antitumor T-cell activity. Patients benefit from increased overall and progression-free survival, but the enhancement of normal immunity can result in autoimmune manifestations, called immune-related adverse events (IRAEs), which may lead to a discontinuation of cancer therapy and to severe also life-threating events. IRAEs may affect any organs or system in the human body, being the gastrointestinal (GI) tract one of the most involved districts. Imaging plays an important role in recognizing GI IRAEs and radiologist should be familiar with the main spectrum of radiological appearance. Indeed, early detection of GI IRAEs is crucial for proper patient management and reduces morbidity and mortality. The purpose of this review is to present the most relevant imaging manifestation of GI IRAEs.