| Autor: |
Giovanni Cappello, Valentina Giannini, Roberto Cannella, Emanuele Tabone, Ilaria Ambrosini, Francesca Molea, Nicolò Damiani, Ilenia Landolfi, Giovanni Serra, Giorgia Porrello, Cecilia Gozzo, Lorena Incorvaia, Giuseppe Badalamenti, Giovanni Grignani, Alessandra Merlini, Lorenzo D’Ambrosio, Tommaso Vincenzo Bartolotta, Daniele Regge |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
European Journal of Radiology Open, Vol 11, Iss , Pp 100505- (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2352-0477 |
| DOI: |
10.1016/j.ejro.2023.100505 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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