Validation and feasibility of fast knee MRI using a deep learning-assisted 3D iterative image enhancement system

利用深度学习辅助的3D迭代图像增强系统验证和评估快速膝关节MRI的可行性

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Abstract

BACKGROUND: Fast magnetic resonance imaging (MRI) can significantly improve patient tolerance and examination efficiency, but it may compromise image quality. This study investigated the feasibility of using a deep learning-assisted three-dimensional iterative image enhancement (DL-3DIIE) system to achieve high-resolution fast imaging of the knee. METHODS: This prospective study included participants scheduled for knee MRI plain scans at the Northern Jiangsu People's Hospital between September 2023 and January 2024. The participants underwent knee MRI with both conventional and fast scans. Three MRI protocols were compared: conventional MRI, fast MRI with reduced acquisition parameters, and DL-3DIIE MRI, which enhanced fast images with deep learning to improve overall image quality. Image quality was assessed subjectively (quality scores) and objectively using peak signal-to-noise ratio (PSNR), multi-scale structural similarity index (MS-SSIM), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). RESULTS: The analysis included 134 patients (mean age 55.1±9.5 years; 46.3% male). For both sagittal proton density weighted imaging-fast spin echo (PDWI-FSE) and T1 weighted imaging-fast spin echo (T1WI-FSE) sequences, DL-3DIIE MRI achieved significantly higher SNRs and CNRs across all tissues and tissue contrasts compared with both conventional and fast MRI (all P<0.05). Quantitative metrics of image quality were also improved, with PSNR and MS-SSIM significantly higher for DL-3DIIE MRI than fast MRI in all sequences (all P<0.001). Subjective image quality assessment demonstrated that DL-3DIIE MRI yielded significantly higher scores for lesion conspicuity, margin delineation, and overall diagnostic confidence compared with conventional MRI (all P<0.05). CONCLUSIONS: DL-3DIIE MRI provides superior quantitative and subjective image quality compared with both conventional and fast MRI, including higher SNR, CNR, PSNR, and MS-SSIM, as well as improved lesion and margin visibility. These findings support the potential of DL-3DIIE to accelerate knee MRI while preserving or improving diagnostic performance.

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