Radiomic involves testing the associations of a large number of quantitative imaging features with clinical characteristics. Our aim was to extract a radiomic signature from axial T2-weighted (T2-W) magnetic resonance imaging (MRI) of the whole prostate able to predict oncological and radiological scores in prostate cancer (PCa).
This study included 65 patients with localized PCa treated with radiotherapy (RT) between 2014 and 2018. For each patient, the T2-W MRI images were normalized with the histogram intensity scale standardization method. Features were extracted with the IBEX software. The association of each radiomic feature with risk class, T-stage, Gleason score (GS), extracapsular extension (ECE) score, and Prostate Imaging Reporting and Data System (PI-RADS v2) score was assessed by univariate and multivariate analysis.
Forty-nine out of 65 patients were eligible. Among the 1702 features extracted, 3 to 6 features with the highest predictive power were selected for each outcome. This analysis showed that texture features were the most predictive for GS, PI-RADS v2 score, and risk class; intensity features were highly associated with T-stage, ECE score, and risk class, with areas under the receiver operating characteristic curve (ROC AUC) ranging from 0.74 to 0.94.
MRI-based radiomics is a promising tool for prediction of PCa characteristics. Although a significant association was found between the selected features and all the mentioned clinical/radiological scores, further validations on larger cohorts are needed before these findings can be applied in the clinical practice.
• A radiomic model was used to classify PCa aggressiveness. • Radiomic analysis was performed on T2-W magnetic resonance images of the whole prostate gland. • The most predictive features belong to the texture (57%) and intensity (43%) domains.
European radiology. 2020 Aug 27 [Epub ahead of print]
Simone Giovanni Gugliandolo, Matteo Pepa, Lars Johannes Isaksson, Giulia Marvaso, Sara Raimondi, Francesca Botta, Sara Gandini, Delia Ciardo, Stefania Volpe, Giulia Riva, Damari Patricia Rojas, Dario Zerini, Paola Pricolo, Sarah Alessi, Giuseppe Petralia, Paul Eugene Summers, Frnacesco Alessandro Mistretta, Stefano Luzzago, Federica Cattani, Ottavio De Cobelli, Enrico Cassano, Marta Cremonesi, Massimo Bellomi, Roberto Orecchia, Barbara Alicja Jereczek-Fossa
Division of Radiotherapy, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Division of Radiotherapy, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy. ., Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Medical Physics Unit, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Division of Radiology, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Department of Oncology and Hemato-Oncology, University of Milan, Via Festa del Perdono 7, 20122, Milan, Italy., Division of Urology, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Breast Imaging Division, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Radiation Research Unit, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy., Scientific Directorate, IEO, European Institute of Oncology IRCCS, Via Ripamonti 435, 20141, Milan, Italy.