Focal Therapy of Prostate Cancer: Use of Artificial Intelligence to Define Tumour Volume and Predict Treatment Outcomes

Objectives: The aim of this study is to evaluate new software (Unfold AI) in the estimation of prostate tumour volume (TV) and prediction of focal therapy outcomes.

Subjects/patients And Methods: Subjects were 204 men with prostate cancer (PCa) of grade groups 2-4 (GG ≥ 2), who were enrolled in a trial of partial gland cryoablation (PGA) at UCLA from 2017 to 2022. Magnetic resonance imaging (MRI)-guided biopsy (MRGB) was performed at diagnosis and at 6 and 18 months following PGA. Utilising Unfold AI (FDA-cleared 2022), which generates a 3D map of GG ≥ 2 PCa margins, we retrospectively estimated TV for each patient. TV was compared against conventional baseline variables as a correlate of a successful primary outcome-defined here as the absence of GG ≥ 2 on follow-up MRGB at 6 months. Secondary outcomes were MRGB at 18 months and failure-free survival, that is, lack of metastasis or salvage whole gland therapy. Receiver operating curves and multivariate analysis were used to determine significance.

Results: A successful primary outcome was observed in 77.7% of patients. Significant correlates of a successful ablation were percent pattern 4 and TV; areas under the curve (AUCs) were 0.60 and 0.73, respectively. GG was not a correlate of success (AUC = 0.51). A TV of 1.5 cc provided the optimal combination of sensitivity (55.8%) and specificity (85.7%) at 6 months. TV was also significantly associated with secondary outcomes. In multivariate analysis, TV was the variable most associated with 6- and 18-month biopsy success (adjusted odds ratios [aORs] were 6.1 and 4.2). Utilising TV ≤ 1.5 cc as a PGA criterion would have prevented 72% of failures at the cost of 42% of successes.

Conclusion: The AI-based software Unfold AI estimates TV, which is significantly associated with biopsy outcomes after focal cryoablation. The rate of treatment success is inversely related to TV.