Prospective and multi-reader evaluation of deep learning reconstruction-based accelerated rectal MRI: image quality, diagnostic performance, and reading time.

Abstract

To evaluate deep learning reconstruction (DLR)-based accelerated rectal magnetic resonance imaging (MRI) compared with standard MRI. Patients with biopsy-confirmed rectal adenocarcinoma between November/2022 and May/2023 in a single centre were prospectively enrolled for an intra-individual comparison between standard fast spin-echo (FSE_standard) and DLR-based FSE (FSE_DL) sequences. Quantitative and qualitative image quality metrics of the pre-therapeutic MRIs were evaluated in all patients; diagnostic performance and evaluating time for T-staging, N-staging, extramural vascular invasion (EMVI), and mesorectal fascia (MRF) status was further analysed in patients undergoing curative surgery, with histopathologic results as the diagnostic gold standard. A total of 117 patients were enrolled, with 60 patients undergoing curative surgery. FSE_DL reduced the acquisition time by 65% than FSE_standard. FSE_DL exhibited higher signal-to-noise ratios, contrast-to-noise ratio, and subjective scores (noise, tumour margin clarity, visualisation of bowel wall layering and MRF, overall image quality, and diagnostic confidence) than FSE_standard (p < 0.001). Reduced artefacts were observed in FSE_DL for patients without spasmolytics (p < 0.05). FSE_DL provided higher T-staging accuracy by junior readers than FSE_standard (reader 1, 58.33% vs 70.00%, p = 0.016; reader 3, 60.00% vs 76.67%, p = 0.021), with similar N-staging, EMVI, and MRF performance. No significant difference was observed for senior readers. FSE_DL exhibited shorter diagnostic time in all readers' T-staging and overall evaluation, and junior readers' EMVI and MRF (p < 0.05). FSE_DL provided improved image quality, reading time, and junior radiologists' T-staging accuracy than FSE_standard, while reducing the acquisition time by 65%. DLR is clinically applicable for rectal MRI, providing improved image quality with shorter scanning time, which may ease the examination burden. It is beneficial for diagnostic optimisation in improving junior radiologists' T-staging accuracy and reading time. The rising incidence of rectal cancer has demanded enhanced efficiency and quality in imaging examinations. FSE_DL demonstrated superior image quality and had a 65% reduced acquisition time. FSE_DL can improve the diagnostic accuracy of T-staging and reduce the reading time for assessing rectal cancer.