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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Nature Portfolio
2024-11-01
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| Online Access: | https://doi.org/10.1038/s41598-024-79348-5 |
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| author | Dong Hwan Kim Moon Hyung Choi Young Joon Lee Sung Eun Rha Marcel Dominik Nickel Hyun-Soo Lee Dongyeob Han |
| author_facet | Dong Hwan Kim Moon Hyung Choi Young Joon Lee Sung Eun Rha Marcel Dominik Nickel Hyun-Soo Lee Dongyeob Han |
| author_sort | Dong Hwan Kim |
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| description | 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 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. |
| format | Article |
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| spelling | doaj-art-e2aded2b21164452aee15b6c698eb5de2025-08-20T02:08:19ZengNature PortfolioScientific Reports2045-23222024-11-0114111010.1038/s41598-024-79348-5Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessmentDong Hwan Kim0Moon Hyung Choi1Young Joon Lee2Sung Eun Rha3Marcel Dominik Nickel4Hyun-Soo Lee5Dongyeob Han6Department of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDepartment of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDepartment of Radiology, Eunpyeong St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDepartment of Radiology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of KoreaDiagnostic Imaging, Siemens Healthineers AGSiemens Healthineers LtdSiemens Healthineers LtdAbstract 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.https://doi.org/10.1038/s41598-024-79348-5Deep learning-based reconstructionAccelerationProstate cancerMagnetic resonance imagingT2-weighted imagingStaging |
| spellingShingle | Dong Hwan Kim Moon Hyung Choi Young Joon Lee Sung Eun Rha Marcel Dominik Nickel Hyun-Soo Lee Dongyeob Han Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment Scientific Reports Deep learning-based reconstruction Acceleration Prostate cancer Magnetic resonance imaging T2-weighted imaging Staging |
| title | Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| title_full | Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| title_fullStr | Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| title_full_unstemmed | Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| title_short | Deep learning-accelerated T2WI of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| title_sort | deep learning accelerated t2wi of the prostate for transition zone lesion evaluation and extraprostatic extension assessment |
| topic | Deep learning-based reconstruction Acceleration Prostate cancer Magnetic resonance imaging T2-weighted imaging Staging |
| url | https://doi.org/10.1038/s41598-024-79348-5 |
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