Prostate Cancer Risk Prediction Model Using Clinical and Magnetic Resonance Imaging–Related Findings: Impact of Combining Lesions’ Locations and Apparent Diffusion Coefficient Values
Adding lesions-level findings improved the csPCa discrimination in the development but not the validation cohort. Interfacility differences impeded model generalization, including the distribution of reported ADC values and PI-RADS score-level csPCa proportion.
Authors
- Jordan D. LeGout (ORCID: https://orcid.org/0000-0003-3608-726X)
- Mitchell R. Humphreys (ORCID: https://orcid.org/0000-0003-3252-9518)
- Adam T. Froemming (ORCID: https://orcid.org/0000-0001-7706-8060)
- Naoki Takahashi (ORCID: https://orcid.org/0000-0002-7946-6078)
- Akira Kawashima (ORCID: https://orcid.org/0000-0003-4686-8369)
- Panagiotis Korfiatis (ORCID: https://orcid.org/0000-0003-2516-1751)
- Jason R. Klug
- Hirotsugu Nakai (ORCID: https://orcid.org/0000-0002-2080-5901)
- Derek J. Lomas (ORCID: https://orcid.org/0000-0003-3386-6866)
- Chandler Dora (ORCID: https://orcid.org/0000-0002-9248-1328)
- Hiroaki Takahashi (ORCID: https://orcid.org/0000-0002-5848-7654)
Institutions
- Jacksonville College (US)
- WinnMed (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- Journal of Computer Assisted Tomography
- Published
- 2024-11-13
- DOI
- https://doi.org/10.1097/rct.0000000000001679
- Citations
- 2
- Primary Topic
- Prostate Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.84