Improved prostate cancer diagnosis: upgraded prostate imaging reporting and data system (PI-RADS) scores by zoomed diffusion-weighted imaging enhance deep-learning-based computer-aided diagnosis accuracy
z-DWI, in comparison to f-DWI, enhances the diagnostic performance of DL-CAD for PCa, assigning higher PI-RADS scores to malignant lesions. Despite offering limited improvement for radiologists using DL-CAD, z-DWI shows promise in enhancing the detection of csPCa.
Authors
- Tobias Penzkofer (ORCID: https://orcid.org/0000-0001-9591-8575)
- 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)
- David Winkel (ORCID: https://orcid.org/0000-0001-7051-8022)
- Edyta Szurowska (ORCID: https://orcid.org/0000-0002-7042-4381)
- Ali Kamen (ORCID: https://orcid.org/0000-0002-1928-2410)
- Moon Hyung Choi (ORCID: https://orcid.org/0000-0001-5962-4772)
- Fergus V. Coakley (ORCID: https://orcid.org/0000-0001-7455-8427)
- Ivan Shabunin
- Haining Long (ORCID: https://orcid.org/0009-0006-4597-7458)
- Angela Tong (ORCID: https://orcid.org/0000-0002-4733-3414)
- Pengyi Xing
- HenkJan J. Huisman (ORCID: https://orcid.org/0000-0001-6753-3221)
- Yichen Lu
- Dieter Szolar (ORCID: https://orcid.org/0000-0001-9228-0166)
- Lisong Dai (ORCID: https://orcid.org/0000-0003-3608-9732)
- Robert Grimm (ORCID: https://orcid.org/0000-0002-1233-8215)
- Bin Lou (ORCID: https://orcid.org/0000-0002-4687-8519)
- 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)
- Steven M. Shea (ORCID: https://orcid.org/0000-0002-0360-4884)
- 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)
- Lei Wang (ORCID: https://orcid.org/0009-0006-8680-3737)
Institutions
- Loyola University Medical Center (US)
- Radboud University Nijmegen (NL)
- Shanghai Jiao Tong University (CN)
- University of Basel (CH)
- Radboud University Medical Center (NL)
- Digital China Health (China) (CN)
- Key Laboratory of Guangdong Province (CN)
- Geriatrische Gesundheitszentren (AT)
- Shanghai Sixth People's Hospital (CN)
- Guangdong Academy of Medical Sciences (CN)
- Siemens Healthcare (United States) (US)
- Siemens Healthineers (Germany) (DE)
- Guangdong Provincial People's Hospital (CN)
- Shanghai Institute of Process Automation Instrumentation (China) (CN)
- The Catholic University of Korea Seoul St. Mary's Hospital (KR)
- Siemens (China) (CN)
- New York University (US)
- Southern Medical University (CN)
- Gdańsk Medical University (PL)
- Charité - Universitätsmedizin Berlin (DE)
- Catholic University of Korea (KR)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-03-01
- DOI
- https://doi.org/10.21037/qims-24-1263
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China