652-01-005 / 652-01-005 ISMRM Abstract

Integrated Machine Learning Model for Predicting Prostate Cancer Progression from mpMRI Radiomics and Clinical Data

Primary: Body - Prostate

Secondary: Analysis Methods - Classification and Prediction

652-01-005 · Prognostication and Predictive Value of MR Biomarkers · Thursday, 14 May, 8:30 AM–10:06 AM · Power Pitch Theatre 2

Keywords: Prostate cancer Radiomics analysis Machine learning classification Multiparametric MRI (mp-MRI) Active Surveillance

Accepted

Sohaib Naim^1,2, Siriluck Satonkiatngam¹, Hyun S Lim¹, Qi Miao¹, Kai Zhao¹, Katarina Chiam¹, Wayne G Brisbane³, Leonard S Marks³, Steven S Raman¹, Holden H Wu^1,2, KyungHyun Sung^1,2

¹Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, United States of America

²Physics and Biology in Medicine Interdepartmental Program, David Geffen School of Medicine at UCLA, Los Angeles, United States of America

³Department of Urology, David Geffen School of Medicine at UCLA, Los Angeles, United States of America

Presenting Author: Raymi O Ramirez

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References

1. De Vos, I. I., Luiting, H. B., & Roobol, M. J. (2023). Active Surveillance for Prostate Cancer: Past, Current, and Future Trends. Journal of Personalized Medicine, 13(4), 629. https://doi.org/10.3390/jpm13040629 [doi]

2. Sushentsev, N., Rundo, L., Abrego, L., Li, Z., Nazarenko, T., Warren, A. Y., Gnanapragasam, V. J., Sala, E., Zaikin, A., Barrett, T., & Blyuss, O. (2023). Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance. European Radiology, 33(6), 3792-3800. https://doi.org/10.1007/s00330-023-09438-x [doi]

3. Caglic, I., Sushentsev, N., Syer, T., Lee, K.-L., & Barrett, T. (2024). Biparametric MRI in prostate cancer during active surveillance: is it safe? European Radiology, 34(10), 6217-6226. https://doi.org/10.1007/s00330-024-10770-z [doi]

4. Sushentsev, N., Rundo, L., Blyuss, O., Gnanapragasam, V. J., Sala, E., & Barrett, T. (2021). MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance. Scientific Reports, 11(1). https://doi.org/10.1038/s41598-021-92341-6 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/652-01-005