AI-assisted accelerated MRI of the ankle: clinical practice assessment

European Radiology Experimental

Original Article

Qiang Zhao¹  Jiajia Xu¹  Qizheng Wang¹  Yuqing Zhao¹  Huishu Yuan¹  Dan Yu²  Yu Xin Yang² 

[1] Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian District, 100191, Beijing, People’s Republic of China;United Imaging Research Institute of Intelligent Imaging, Beijing, People’s Republic of China;

关键词: Acceleration;    Ankle;    Artificial intelligence;    Magnetic resonance imaging;    Musculoskeletal diseases;   

DOI  :  10.1186/s41747-023-00374-5

 received in 2023-04-25, accepted in 2023-08-04,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundHigh-spatial resolution magnetic resonance imaging (MRI) is essential for imaging ankle joints. However, the clinical application of fast spin-echo sequences remains limited by their lengthy acquisition time. Artificial intelligence-assisted compressed sensing (ACS) technology has been recently introduced as an integrative acceleration solution. We compared ACS-accelerated 3-T ankle MRI to conventional methods of compressed sensing (CS) and parallel imaging (PI) .MethodsWe prospectively included 2 healthy volunteers and 105 patients with ankle pain. ACS acceleration factors for ankle protocol of T1-, T2-, and proton density (PD)-weighted sequences were optimized in a pilot study on healthy volunteers (acceleration factor 3.2–3.3×). Images of patients acquired using ACS and conventional acceleration methods were compared in terms of acquisition times, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective image quality, and diagnostic agreement. Shapiro-Wilk test, Cohen κ, intraclass correlation coefficient, and one-way ANOVA with post hoc tests (Tukey or Dunn) were used.ResultsACS acceleration reduced the acquisition times of T1-, T2-, and PD-weighted sequences by 32−43%, compared with conventional CS and PI, while maintaining image quality (mostly higher SNR with p < 0.004 and higher CNR with p < 0.047). The diagnostic agreement between ACS and conventional sequences was rated excellent (κ = 1.00).ConclusionsThe optimum ACS acceleration factors for ankle MRI were found to be 3.2–3.3× protocol. The ACS allows faster imaging, yielding similar image quality and diagnostic performance.Relevance statementAI-assisted compressed sensing significantly accelerates ankle MRI times while preserving image quality and diagnostic precision, potentially expediting patient diagnoses and improving clinical workflows.Key points• AI-assisted compressed sensing (ACS) significantly reduced scan duration for ankle MRI.• Similar image quality achieved by ACS compared to conventional acceleration methods.• A high agreement by three acceleration methods in the diagnosis of ankle lesions was observed.Graphical Abstract

【 授权许可】

CC BY   
© European Society of Radiology (ESR) 2023

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