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ORIGINAL RESEARCH article

Front. Med.
Sec. Nuclear Medicine
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1480196
This article is part of the Research Topic Recent developments in artificial intelligence and radiomics View all articles

Feasibility of knee MRI protocol using AI-assisted Iterative algorithm protocols: comparison with standard MRI protocols

Provisionally accepted
Hailong Liu Hailong Liu Yanxia Chen Yanxia Chen Meng Zhang Meng Zhang Hai bu Hai bu Fenghan Lin Fenghan Lin Jun Chen Jun Chen Mengqiang Xiao Mengqiang Xiao *Jie Chen Jie Chen *
  • Guangdong Provincial Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China

The final, formatted version of the article will be published soon.

    Objective: To evaluate the image quality and diagnostic performance of AI-assisted iterative algorithm protocols (AIIA) in accelerated fast spin-echo magnetic resonance imaging (MRI) versus standard (SD) fast spin-echo MRI for clinical 3.0T rapid knee scans.Materials and Methods: The accelerated sequence, which includes fat-suppression proton density-weighted imaging (FS-PDWI), T2-weighted imaging (T2WI), and T1-weighted imaging (T1WI), was used in conjunction with the SD sequence in 61 patients who underwent MRI scans. SD images were processed using standard reconstruction techniques, while accelerated images utilized AIIA reconstruction.Quantitative assessments of image quality were conducted, measuring noise levels,signal-to-noise ratio (SNR) and contrast signal-to-noise ratio (CNR). Additionally, subjective evaluations were performed using a Likert five-point scale to assess image quality.Results: The SD group completed the entire knee scan in 466 seconds, while the AIIA group completed the scan in 312 seconds. Compared to the SD group, the AIIA group had a noticeably higher SNR of T1WI in the femur and subpatellar fat pad (P=0.04, 0.001). On the other hand, T2WI femur SNR was noticeably higher in the SD group (P=0.004) . Measurements of SNR ,CNR and other noise levels showed no statistically significant changes. Compared to the SD group, the AIIA group had significantly higher subjective image quality scores for every sequence (P＜0.05). There was a modest to large intraclass correlation value (ICC = 0.65-0.90) for the anomalies that were examined among readers. Both the AIIA and SD procedures were shown to have comparable diagnostic performance for meniscal and cruciate ligament rupture (p > 0.05).Conclusion: Images processed using AIIA reconstruction were acquired faster while maintaining comparable image quality and diagnostic capability, meeting the requirements for clinical diagnosis.

    Keywords: Iterative algorithm, Knee, artificial intelligence, Magnetic Resonance Imaging, Acceleration technique

    Received: 13 Aug 2024; Accepted: 11 Oct 2024.

    Copyright: © 2024 Liu, Chen, Zhang, bu, Lin, Chen, Xiao and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Mengqiang Xiao, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China
    Jie Chen, Guangdong Provincial Hospital of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China

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