To derive and evaluate the association of prostate shape distension descriptors from T2-weighted MRI (T2WI) with prostate cancer (PCa) biochemical recurrence (BCR) post-radical prostatectomy (RP) independently and in conjunction with texture radiomics of PCa.
This retrospective study comprised 133 PCa patients from two institutions who underwent 3T-MRI prior to RP and were followed up with PSA measurements for ≥3 years. A 3D shape atlas-based approach was adopted to derive prostate shape distension descriptors from T2WI, and these descriptors were used to train a random forest classifier (CS ) to predict BCR. Texture radiomics was derived within PCa regions of interest from T2WI and ADC maps, and another machine learning classifier (CR ) was trained for BCR. An integrated classifier CS + R was then trained using predictions from CS and CR . These models were trained on D1 (N = 71, 27 BCR+) and evaluated on independent hold-out set D2 (N = 62, 12 BCR+). CS + R was compared against pre-RP, post-RP clinical variables, and extant nomograms for BCR-free survival (bFS) at 3 years.
CS + R resulted in a higher AUC (0.75) compared to CR (0.70, p = 0.04) and CS (0.69, p = 0.01) on D2 in predicting BCR. On univariable analysis, CS + R achieved a higher hazard ratio (2.89, 95% CI 0.35-12.81, p < 0.01) compared to other pre-RP clinical variables for bFS. CS + R , pathologic Gleason grade, extraprostatic extension, and positive surgical margins were associated with bFS (p < 0.05). CS + R resulted in a higher C-index (0.76 ± 0.06) compared to CAPRA (0.69 ± 0.09, p < 0.01) and Decipher risk (0.59 ± 0.06, p < 0.01); however, it was comparable to post-RP CAPRA-S (0.75 ± 0.02, p = 0.07).
Radiomic shape descriptors quantifying prostate surface distension complement texture radiomics of prostate cancer on MRI and result in an improved association with biochemical recurrence post-radical prostatectomy.
Frontiers in oncology. 2022 May 20*** epublish ***
Rakesh Shiradkar, Soumya Ghose, Amr Mahran, Lin Li, Isaac Hubbard, Pingfu Fu, Sree Harsha Tirumani, Lee Ponsky, Andrei Purysko, Anant Madabhushi
Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States., GE Global Research, Niskayuna, NY, United States., Department of Urology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States., Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States., Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States., Department of Abdominal Imaging and Nuclear Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, United States.