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ABSTRACT: 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.
SUBMITTER: Cappello G
PROVIDER: S-EPMC10362081 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
Cappello Giovanni G Giannini Valentina V Cannella Roberto R Tabone Emanuele E Ambrosini Ilaria I Molea Francesca F Damiani Nicolò N Landolfi Ilenia I Serra Giovanni G Porrello Giorgia G Gozzo Cecilia C Incorvaia Lorena L Badalamenti Giuseppe G Grignani Giovanni G Merlini Alessandra A D'Ambrosio Lorenzo L Bartolotta Tommaso Vincenzo TV Regge Daniele D
European journal of radiology open 20230710
<h4>Objectives</h4>To develop a mutation-based radiomics signature to predict response to imatinib in Gastrointestinal Stromal Tumors (GISTs).<h4>Methods</h4>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 di ...[more]