Transition-zone PSA-density calculated from MRI deep learning prostate zonal segmentation model for prediction of clinically significant prostate cancer-Reference-Cited by-同舟云学术

Transition-zone PSA-density calculated from MRI deep learning prostate zonal segmentation model for prediction of clinically significant prostate cancer

Published:2024-06-19 Issue:10 Volume:49 Page:3722-3734
ISSN:2366-0058
Container-title:Abdominal Radiology
language:en
Short-container-title:Abdom Radiol

Author:

Kuanar Shiba,Cai Jason,Nakai Hirotsugu,Nagayama Hiroki,Takahashi Hiroaki,LeGout Jordan,Kawashima Akira,Froemming Adam,Mynderse Lance,Dora Chandler,Humphreys Mitchell,Klug Jason,Korfiatis Panagiotis,Erickson Bradley,Takahashi Naoki^ORCID

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00261-024-04301-z.pdf

Reference35 articles.

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2. Frisbie JW, Van Besien AJ, Lee A, et al (2023) PSA density is complementary to prostate MP-MRI PI-RADS scoring system for risk stratification of clinically significant prostate cancer. Prostate Cancer Prostatic Dis 26:347–352. https://doi.org/https://doi.org/10.1038/s41391-022-00549-y

3. Deniffel D, Healy GM, Dong X, et al (2021) Avoiding Unnecessary Biopsy: MRI-based Risk Models versus a PI-RADS and PSA Density Strategy for Clinically Significant Prostate Cancer. Radiology 300:369–379. https://doi.org/https://doi.org/10.1148/radiol.2021204112

4. Kotb AF, Spaner S, Crump T, Hyndman ME (2018) The role of mpMRI and PSA density in patients with an initial negative prostatic biopsy. World J Urol 36:2021–2025. https://doi.org/https://doi.org/10.1007/s00345-018-2341-4

5. Remzi M, Djavan B, Wammack R, et al (2003) Can total and transition zone volume of the prostate determine whether to perform a repeat biopsy? Urology 61:161–166. https://doi.org/https://doi.org/10.1016/s0090-4295(02)02099-x