Development of a Radiomic-Based Model Predicting Lymph Node Involvement in Prostate Cancer Patients
Résumé
In patients with prostate cancer, lymph node involvement is a risk factor of relapse. Current guidelines recommend extended lymph node dissection to better stage the disease. However, such a surgical procedure is associated with a higher morbidity than limited lymph node dissection. A better selection of patients is thus essential. Radiomics features are quantitative features automatically extracted from medical imaging. Combining clinical and radiomics features, a machine learning-based model seemed to provide added predictive performance compared to state of the art models regarding the risk prediction of lymph-node involvement in prostate cancer patients.
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