Abstract
Adjuvant radiotherapy after prostatectomy was recently challenged by early salvage radiotherapy, which highlighted the need for biomarkers to improve risk stratification. Therefore, we developed an MRI ADC map-derived radiomics model to predict biochemical recurrence (BCR) and BCR-free survival (bRFS) after surgery. Our goal in this work was to externally validate this radiomics-based prediction model. Experimental Design: A total of 195 patients with a high recurrence risk of prostate cancer (pT3-4 and/or R1 and/or Gleason’s score > 7) were retrospectively included in two institutions. Patients with postoperative PSA (Prostate Specific Antigen) > 0.04 ng/mL or lymph node involvement were excluded. Radiomics features were extracted from T2 and ADC delineated tumors. A total of 107 patients from Institution 1 were used to retrain the previously published model. The retrained model was then applied to 88 patients from Institution 2 for external validation. BCR predictions were evaluated using AUC (Area Under the Curve), accuracy, and bRFS using Kaplan–Meier curves. Results: With a median follow-up of 46.3 months, 52/195 patients experienced BCR. In the retraining cohort, the clinical prediction model (combining the number of risk factors and postoperative PSA) demonstrated moderate predictive power (accuracy of 63%). The radiomics model (ADC-based SZEGLSZM) predicted BCR with an accuracy of 78% and allowed for significant stratification of patients for bRFS (p < 0.0001). In Institution 2, this radiomics model remained predictive of BCR (accuracy of 0.76%) contrary to the clinical model (accuracy of 0.56%). Conclusions: The recently developed MRI ADC map-based radiomics model was validated in terms of its predictive accuracy of BCR and bRFS after prostatectomy in an external cohort.
Highlights
Prostate cancer (PCa) is the most common cancer among men with approximately 191,900 patients expected to be diagnosed in 2020 in the United States, and more than 33,000 deaths annually [1]
Biochemical recurrence (BCR) occurs in 50% of these patients, especially those with high-risk features, such as locally advanced disease (T3-4), positive margins (R1), and high Gleason scores, with biochemical recurrence (BCR) being a surrogate of metastatic relapse and cancer-specific death [3]
ART was recently challenged by early salvage radiotherapy with no significant benefit emerging for the use of Adjuvant radiotherapy (aRT) for BCR-free survival, highlighting the need for additional biomarkers to enable patient selection [8,9,10]
Summary
Prostate cancer (PCa) is the most common cancer among men with approximately 191,900 patients expected to be diagnosed in 2020 in the United States, and more than 33,000 deaths annually [1]. Biochemical recurrence (BCR) occurs in 50% of these patients, especially those with high-risk features, such as locally advanced disease (T3-4), positive margins (R1), and high Gleason scores, with BCR being a surrogate of metastatic relapse and cancer-specific death [3]. ART was recently challenged by early salvage radiotherapy (esRT) with no significant benefit emerging for the use of aRT for BCR-free survival, highlighting the need for additional biomarkers to enable patient selection [8,9,10]. The natural history of relapse after RP is heterogeneous even in patients with high-risk features and may reflect a broad range of underlying tumor pathophysiological processes. Geometrical, or textural metrics providing quantitative measurements of tumor intensity, shape, and heterogeneity, which may reflect intratumoral histopathological properties and provide prognostic information in several pathologies, including
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