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Use of Magnetic Resonance Imaging and Biopsy Data to Guide Sampling Procedures for Prostate Cancer Biobanking
Published on: October 10, 2019
Cone-beam computed tomography-based radiomics in prostate cancer: a mono-institutional study
Davide Giovanni Bosetti1, Lorenzo Ruinelli2, Maria Antonietta Piliero3
1Radiation Oncology Clinic, Oncology Institute of Southern Switzerland, Via Gallino, 6500, Bellinzona, Switzerland. davidegiovanni.bosetti@eoc.ch.
Purpose:
The purpose of the reported study was to investigate the value of cone-beam computed tomography (CBCT)-based radiomics for risk stratification and prediction of biochemical relapse in prostate cancer.
Methods:
The study population consisted of 31 prostate cancer patients. Radiomics features were extracted from weekly CBCT scans performed for verifying treatment position. From the data, logistic-regression models were learned for establishing tumor stage, Gleason score, level of prostate-specific antigen, and risk stratification, and for predicting biochemical recurrence. Performance of the learned models was assessed using the area under the receiver operating characteristic curve (AUC-ROC) or the area under the precision-recall curve (AUC-PRC).
Results:
Results suggest that the histogram-based Energy and Kurtosis features and the shape-based feature representing the standard deviation of the maximum diameter of the prostate gland during treatment are predictive of biochemical relapse and indicative of patients at high risk.
Conclusion:
Our results suggest the usefulness of CBCT-based radiomics for treatment definition in prostate cancer.

