Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes
Abstract 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...
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Wiley
2025-01-01
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| Series: | BJUI Compass |
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| Online Access: | https://doi.org/10.1002/bco2.456 |
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| author | Wayne G. Brisbane Alan M. Priester Anissa V. Nguyen Mark Topoozian Sakina Mota Merdie K. Delfin Samantha Gonzalez Kyla P. Grunden Shannon Richardson Shyam Natarajan Leonard S. Marks |
| author_facet | Wayne G. Brisbane Alan M. Priester Anissa V. Nguyen Mark Topoozian Sakina Mota Merdie K. Delfin Samantha Gonzalez Kyla P. Grunden Shannon Richardson Shyam Natarajan Leonard S. Marks |
| author_sort | Wayne G. Brisbane |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-abf17c4c9c5d426b94a753fb2cf59e44 |
| institution | Kabale University |
| issn | 2688-4526 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | BJUI Compass |
| spelling | doaj-art-abf17c4c9c5d426b94a753fb2cf59e442025-01-31T00:14:32ZengWileyBJUI Compass2688-45262025-01-0161n/an/a10.1002/bco2.456Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomesWayne G. Brisbane0Alan M. Priester1Anissa V. Nguyen2Mark Topoozian3Sakina Mota4Merdie K. Delfin5Samantha Gonzalez6Kyla P. Grunden7Shannon Richardson8Shyam Natarajan9Leonard S. Marks10Department of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USAAvenda Health Culver City California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USADepartment of Urology, Institute of Urologic Oncology UCLA Los Angeles California USAAbstract 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.https://doi.org/10.1002/bco2.456artificial intelligencefocal therapyMRIprostate cancertumour volume |
| spellingShingle | Wayne G. Brisbane Alan M. Priester Anissa V. Nguyen Mark Topoozian Sakina Mota Merdie K. Delfin Samantha Gonzalez Kyla P. Grunden Shannon Richardson Shyam Natarajan Leonard S. Marks Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes BJUI Compass artificial intelligence focal therapy MRI prostate cancer tumour volume |
| title | Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes |
| title_full | Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes |
| title_fullStr | Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes |
| title_full_unstemmed | Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes |
| title_short | Focal therapy of prostate cancer: Use of artificial intelligence to define tumour volume and predict treatment outcomes |
| title_sort | focal therapy of prostate cancer use of artificial intelligence to define tumour volume and predict treatment outcomes |
| topic | artificial intelligence focal therapy MRI prostate cancer tumour volume |
| url | https://doi.org/10.1002/bco2.456 |
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