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

Purpose: To develop a deep learning (DL) zonal segmentation model of prostate MR from T2-weighted images and evaluate TZ-PSAD for prediction of the presence of csPCa (Gleason score of 7 or higher) compared to PSAD. Methods: 1020 patients with a prostate MRI were randomly selected to develop a DL zon...

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Publicado en:	Abdominal Radiology Vol. 49; no. 10; pp. 3722 - 3735
Autores principales:	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
Formato:	Journal Article
Publicado:	Springer Nature Oct2024
Acceso en línea:	Ver este registro en EBSCOhost