Deep learning whole‐gland and zonal prostate segmentation on a public MRI dataset

R Cuocolo, A Comelli, A Stefano… - Journal of Magnetic …, 2021 - Wiley Online Library
Background Prostate volume, as determined by magnetic resonance imaging (MRI), is a
useful biomarker both for distinguishing between benign and malignant pathology and can …

Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI

E Thimansson, J Bengtsson, E Baubeta, J Engman… - European …, 2023 - Springer
Objectives Prostate volume (PV) in combination with prostate specific antigen (PSA) yields
PSA density which is an increasingly important biomarker. Calculating PV from MRI is a time …

Decreased prostate MRI cancer detection rate due to moderate to severe susceptibility artifacts from hip prosthesis

H Nakai, H Takahashi, DA Adamo, JD LeGout… - European …, 2024 - Springer
Objectives To evaluate the impact of susceptibility artifacts from hip prosthesis on cancer
detection rate (CDR) in prostate MRI. Materials and methods This three-center retrospective …

Prostate volume estimation on MRI: accuracy and effects of ellipsoid and bullet-shaped measurements on PSA density

A Stanzione, A Ponsiglione, GA Di Fiore, SG Picchi… - Academic …, 2021 - Elsevier
Rationale and Objectives PSA density (PSAd), an important decision-making parameter for
patients with suspected prostate cancer (PCa), is dependent on magnetic resonance …

Comparison of PI-RADS versions 2.0 and 2.1 for MRI-based calculation of the prostate volume

S Ghafoor, AS Becker, S Woo, PIC Andrieu… - Academic …, 2021 - Elsevier
Rationale and Objectives Prostate gland volume (PGV) should be routinely included in MRI
reports of the prostate. The recently updated Prostate Imaging Reporting and Data System …

Biparametric MRI-based radiomics for noninvastive discrimination of benign prostatic hyperplasia nodules (BPH) and prostate cancer nodules: a bio-centric …

Y Lu, R Yuan, Y Su, Z Liang, H Huang, Q Leng… - Scientific Reports, 2025 - nature.com
To investigate the potential of an MRI-based radiomic model in distinguishing malignant
prostate cancer (PCa) nodules from benign prostatic hyperplasia (BPH)-, as well as …

Clinical and prostate multiparametric magnetic resonance imaging findings as predictors of general and clinically significant prostate cancer risk: A retrospective …

M Massanova, R Vere, S Robertson, F Crocetto… - Current …, 2023 - journals.lww.com
Background To evaluate the predictive values of Prostate Imaging Reporting and Data
System version 2 (PI-RADS v2), prostate-specific antigen (PSA) level, PSA density (PSAD) …

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

S Kuanar, J Cai, H Nakai, H Nagayama… - Abdominal …, 2024 - Springer
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 …

New diagnostic model for clinically significant prostate cancer in biopsy-naïve men with PIRADS 3

C Huang, F Qiu, D Jin, X Wei, Z Chen, X Wang… - Frontiers in …, 2022 - frontiersin.org
Purpose The aim of this study was to explore a new model of clinical decision-making to
predict the occurrence of clinically significant prostate cancer (csPCa). Patients and Methods …

Quantitative Evaluation of Apparent Diffusion Coefficient Values, ISUP Grades and Prostate-Specific Antigen Density Values of Potentially Malignant PI-RADS Lesions

N Spadarotto, A Sauck, N Hainc, I Keller, H John… - Cancers, 2023 - mdpi.com
Simple Summary This study demonstrated a correlation between the apparent diffusion
coefficient (ADC) of diffusion-weighted images and potentially malignant prostate lesions …