# High-resolution deep learning-reconstructed T2-weighted imaging for the improvement of image quality and extraprostatic extension assessment in prostate MRI

## 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.

## Key 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 were analyzed. The statistical methods used included the Wilcoxon signed-rank test and Cohen's kappa for inter-reader agreement.

T2HR significantly improved lesion contours (medians of 5 vs. 4, p < 0.001), prostate border delineation (medians of 5 vs. 4, p < 0.001), and overall image quality (medians of 5 vs. 4, p < 0.001) compared to T2S. However, motion artifacts were significantly worse in T2HR. Substantial inter-reader agreement was observed in the PI-RADS scoring. EPE detection marginally increased with T2HR, though histopathological validation was limited.

T2HR imaging with DLR enhances image quality, lesion delineation, and diagnostic confidence without significantly prolonged acquisition time. It shows potential for improving EPE assessment in prostate cancer but requires further validation in larger studies.