High-resolution deep learning-reconstructed T2-weighted imaging for the improvement of image quality and extraprostatic extension assessment in prostate MRI
Sebastian Gassenmaier, Franziska Katharina Staber, Stephan Ursprung, Judith Herrmann, Sebastian Werner, Andreas Lingg, Lisa C. Adams, Haidara Almansour, Konstantin Nikolaou, Saif Afat

TL;DR
This study shows that high-resolution T2-weighted imaging with deep learning improves prostate MRI quality and cancer detection accuracy.
Contribution
The novel use of deep learning-reconstructed high-resolution T2-weighted imaging improves prostate MRI quality and extraprostatic extension assessment.
Findings
T2HR significantly improved lesion contours, prostate border delineation, and overall image quality compared to standard T2.
Motion artifacts were worse in T2HR, but diagnostic confidence and PI-RADS scoring showed strong agreement between radiologists.
EPE detection marginally increased with T2HR, though histopathological validation was limited.
Abstract
This study evaluates the impact of high-resolution T2-weighted imaging (T2HR) combined with deep learning image reconstruction (DLR) on image quality, lesion delineation, and extraprostatic extension (EPE) assessment in prostate multiparametric MRI (mpMRI). This retrospective study included 69 patients who underwent mpMRI of the prostate on a 3 T scanner with DLR between April 2023 and March 2024. Routine mpMRI protocols adhering to the Prostate Imaging Reporting and Data System (PI-RADS) v2.1 were used, including an additional T2HR sequence [2 mm slice thickness, 4:31 min vs. 4:12 min for standard T2 (T2S)]. The image datasets were evaluated by two radiologists using a Likert scale ranging from 1 to 5, with 5 being the best for sharpness, lesion contours, motion artifacts, prostate border delineation, overall image quality, and diagnostic confidence. PI-RADS scoring and EPE suspicion…
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Taxonomy
TopicsProstate Cancer Diagnosis and Treatment · Prostate Cancer Treatment and Research · Advanced Radiotherapy Techniques
