Improving PI-RADS rating with Zoomed Diffusion-Weighted Imaging in Deep Learning CAD Systems
Motivation: The clinical accuracy of the Prostate Imaging Reporting and Data System (PI-RADS) rating by deep-learning-based computer-aided diagnosis (DL-CAD) models need further enhancement for improved prostate cancer (PCa) detection and fewer unnecessary biopsies. Goal(s): This study aimed to achieve more precise PI-RADS rating for PCa lesions by using zoomed diffusion-weighted imaging (z-DWI) in DL-CAD models. Approach: We compared the diagnostic performance and PI-RADS rating of DL-CAD using advanced z-DWI vs. conventional DWI and extended this analysis to radiological practice. Results: z-DWI improved the PI-RADS rating of PCa lesions by DL-CAD based on superior diagnostic performance compared with conventional DWI. Impact: Deep-learning-based computer-aided diagnosis using zoomed diffusion-weighted imaging provides more accurate PI-RADS rating than conventional DWI, correlating MRI-detected lesions with prostate cancer (PCa) from biopsy. This can help minimize unnecessary biopsies for benign lesions while facilitating timely PCa treatment.
Authors
- Thomas Benkert (ORCID: https://orcid.org/0000-0002-3794-5580)
- Heinrich von Busch (ORCID: https://orcid.org/0000-0003-0469-1622)
- Jungong Zhao (ORCID: https://orcid.org/0000-0001-5823-2179)
- Haining Long (ORCID: https://orcid.org/0009-0006-4597-7458)
- Pengyi Xing
- Yichen Lu
- Lisong Dai (ORCID: https://orcid.org/0000-0003-3608-9732)
- Robert Grimm (ORCID: https://orcid.org/0000-0002-1233-8215)
- Zhonghua Hu (ORCID: https://orcid.org/0000-0002-0117-7081)
- W.P. Zhu (ORCID: https://orcid.org/0000-0001-8379-2282)
- Lei Hu (ORCID: https://orcid.org/0000-0002-9124-5411)
- Zhihan Xu (ORCID: https://orcid.org/0000-0003-4057-8299)
- Liming Wei (ORCID: https://orcid.org/0000-0002-4219-278X)
- Caixia Fu (ORCID: https://orcid.org/0000-0002-5595-6347)
- Cancan Xu (ORCID: https://orcid.org/0000-0001-6597-2562)
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2024-11-26
- DOI
- https://doi.org/10.58530/2024/4809
- Primary Topic
- Integrated Circuits and Semiconductor Failure Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00