Feasibility of artificial intelligence-assisted fast magnetic resonance imaging technology in the ankle joint injury: a comparison of the proton density-weighted image

SiHan XuWenJuan CaoLuYi WangPangXing GuoChen Hong Hai^*YuHai Cao^*

• the second hospital of dalian medical university, Daliam, China

Objective To evaluate the image quality and diagnostic efficacy of proton density-weighted MRI with intelligent quick magnetic resonance (iQMR) technology in the ankle joint injury. Materials and methods Forty-six patients with ankle injuries were prospectively enrolled, and proton density-weighted fat suppression imaging was performed on a 3.0 T MRI scanner using both an iQMR protocol (48.28 s) and a Conventional protocol (113.00 s), respectively. The original image was processed using iQMR to improve spatial resolution and reduce noise interference. Thus, four sets of images (iQMR raw, iQMR-processed, Conventional raw, and Conventional-processed) were generated. Image quality and diagnostic efficacy were assessed by objective metrics (signal-to-noise ratio, SNR and contrast-to-noise ratio, CNR), subjective scores (tissue edge clarity/sharpness, signal uniformity, fat suppression uniformity, vascular pulsation artifacts, and overall image quality), and ligaments/tendons injury grade. Results The SNRs (tibia, talus, etc.) and CNRs (talus-flexor hallucis longus , etc.) of iQMR-processed images were significantly higher than those of Conventional raw images (P < 0.05), except for the SNR of Achilles tendon (P > 0.05). And the iQMR-processed images were superior to the Conventional raw images in the scores of edge clarity/sharpness, signal uniformity and overall image quality (P < 0.05), with no significant differences in fat suppression uniformity and vascular pulsation artifacts (P > 0.05). There was no significant difference among the four groups of images in ligaments/tendons injury grading (P > 0.05), but the iQMR-processed images improved diagnostic confidence [κ (kappa) = 0.919]. Conclusion The iQMR technology can effectively shorten the scan time, improve the image quality without affecting the diagnostic accuracy, which is especially suitable for the motion artifacts-sensitive patients and optimizes clinical workflow.