Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment

Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment

Abstract This bicenter retrospective analysis included 162 patients who had undergone prostate biopsy following prebiopsy MRI, excluding those with PCa identified only in the peripheral zone (PZ). DLR T2WI achieved a 69% reduction in scan time relative to TSE T2WI. The intermethod agreement between...

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Bibliographic Details
Main Authors: Dong Hwan Kim, Moon Hyung Choi, Young Joon Lee, Sung Eun Rha, Marcel Dominik Nickel, Hyun-Soo Lee, Dongyeob Han
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Deep learning-based reconstruction
Acceleration
Prostate cancer
Magnetic resonance imaging
T2-weighted imaging
Staging
Online Access:https://doi.org/10.1038/s41598-024-79348-5
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https://doi.org/10.1038/s41598-024-79348-5

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