Prostate Surface Distension and Tumor Texture Descriptors From Pre-Treatment MRI Are Associated With Biochemical Recurrence Following Radical Prostatectomy: Preliminary Findings.

Abstract

Objective:

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.

Methods:

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.

Results:

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).

Conclusions:

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.

• Authors: Rakesh Shiradkar, Soumya Ghose, Amr Mahran, Lin Li, Isaac Hubbard, Pingfu Fu, Sree Harsha Tirumani, Lee Ponsky, Andrei Purysko, Anant Madabhushi
• Journal: Frontiers in oncology (Front Oncol) Vol. 12 Pg. 841801 ( 2022) ISSN: 2234-943X [Print] Switzerland
• PMID: 35669420 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Shiradkar, Ghose, Mahran, Li, Hubbard, Fu, Tirumani, Ponsky, Purysko and Madabhushi.