Meeting Banner
Abstract #5105

Real-time prostate cancer risk stratification and scan tailoring using deep learning on abbreviated prostate MRI: A prospective evaluation

Patricia M. Johnson1,2, Tarun Dutt1, Amanpreet Singh Saimbhi1, Luke Ginocchio1, Kai Tobias Block1, Daniel K. Sodickson1,2, Sumit Chopra1, Angela Tong1, and Hersh Chandarana1,2
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States

Synopsis

Keywords: Diagnosis/Prediction, Prostate

Motivation: MRI is valuable for detecting and managing Prostate Cancer (PCa), but its use is limited by long scan times. While DCE helps with staging and biopsy guidance, its value only applies if PCa is present.

Goal(s): We aim to develop a DL model that identifies csPCa from bpMRI scans in real-time, determining whether DCE is needed.

Approach: We trained a DL model using bpMRI to provide feedback directly at the MRI scanner, guiding the need for further imaging.

Results: In a prospective test, the model achieved an AUC of 0.86 for PI-RADS ≥ 3. Sensitivity and specificity for csPCa were 0.92 and 0.47.

Impact: This study demonstrates that a DL model can guide the selective use of mpMRI based on bpMRI, optimizing resources. This approach could streamline PCa screening, improve patient care, and inspire further research into adaptive and personalized MRI protocols.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.

Keywords