Asset Details
Do you wish to reserve the book?
Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment
Do you wish to request the book?
Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment
2024
Overview
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 the two T2WI sets in terms of the Prostate Imaging Reporting and Data System (PI-RADS) classification and extraprostatic extension (EPE) grade was measured using the intraclass correlation coefficient (ICC) and diagnostic performance was assessed with the area under the receiver operating characteristic curve (AUC). Clinically significant PCa (csPCa) was found in 74 (45.7%) patients. Both T2WI methods showed high intermethod agreement for the overall PI-RADS classification (ICC: 0.907–0.949), EPE assessment (ICC: 0.925–0.957) and lesion size measurement (ICC: 0.980–0.996). DLR T2WI and TSE T2WI showed similar AUCs (0.666–0.814 versus 0.684–0.832) for predicting EPE. The AUCs for detecting csPCa with DLR T2WI (0.834–0.935) and TSE T2WI (0.891–0.935) were comparable in 139 patients with TZ lesions with no significant differences (
P
> 0.05). The findings suggest that DLR T2WI is an efficient alternative for TZ lesion assessment, offering reduced scan times without compromising diagnostic accuracy.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ Aged
/ Biopsy
/ Deep learning-based reconstruction
/ Humanities and Social Sciences
/ Humans
/ Lesions
/ Magnetic Resonance Imaging - methods
/ Male
/ Prostate
/ Prostate - diagnostic imaging
/ Prostatic Neoplasms - diagnosis
/ Prostatic Neoplasms - diagnostic imaging
/ Prostatic Neoplasms - pathology
/ Science
/ Staging
