Quantitative Multiparametric PSMA PET MR to Optimize Treatment Planning for Partial Gland Ablation of Prostate Cancer

Prostate cancer (PCa) is the most common non-cutaneous cancer in American men. Aggressive local therapy of high-grade cancer reduces cancer mortality by up to 50%, but radical therapies such as radical prostatectomy incur side effects that can significantly impact quality of life. Focal ablation has lower morbidity than radical therapy, but its effectiveness is ultimately limited by the accuracy of PCa mapping based on image-guided biopsies. Accurate detection of the full burden of disease is critical to creating an ablation plan that will address all malignant areas. Imaging is critical for accurate assessment of tumor location, size, and boundaries. Multiparametric MRI (mpMRI), consisting of T2-weighted, diffusion-weighted (DWI), and dynamic contrast- enhanced imaging, has rapidly become an essential component of PCa staging and treatment planning. However, mpMRI fails to detect more than 30% of high-grade (Gleason ³ 7) tumors and most low-grade tumors. The diagnostic accuracy of mpMRI is also limited by its reliance on mostly qualitative image interpretation, as well as technical shortcoming such as sensitivity to patient motion and limited spatial resolution. The goal of the proposed project is to improve the accuracy of imaging for partial gland ablation tumor mapping by integrating quantitative MRI (qMRI) and PSMA-PET. A novel MR Multitasking technique will be optimized to simultaneously acquire coregistered prostate T1, T2, and ADC maps. Our advanced imaging will include a high-resolution DWI sequence (hrDWI), which we’ve previously shown improves spatial resolution 5- fold and captures 60% of tumors not visible on standard mpMRI. Coregistered qMRI and PSMA-PET data at the pixel level will be analyzed using machine learning to create empirically derived algorithms and tumor map visualizations for detecting and characterizing PCa using histopathology as the reference. The clinical impact of the proposed qMRI+PET diagnostic framework will be confirmed in a randomized clinical trial in patients undergoing partial gland ablation. The central hypothesis is that qMRI combined with PSMA-PET (qMRI+PET) improves the diagnostic accuracy of prostate cancer when compared to standard mpMRI, leading to better outcomes of partial gland ablation. The proposed project will develop next-generation noninvasive diagnostic imaging to accurately detect and characterize prostate tumors using quantitative MRI combined with PSMA- PET. More accurate tumor mapping is expected to improve focal ablation therapeutic strategies, leading to better treatment outcomes while avoiding the morbidity of radical therapies. Project Number: 1R01CA305424-01A1 | Fiscal Year: 2026 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Debiao Li (+1 co-PI) | Institution: CEDARS-SINAI MEDICAL CENTER, LOS ANGELES, CA | Award Amount: $709,677 | Activity Code: R01 | Study Section: Imaging Guided Interventions and Surgery Study Section[IGIS] View on NIH RePORTER: https://reporter.nih.gov/project-details/11368925