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• Clinical Articles •
Study on application value of proton density weighted imaging accelerated with artificial intelligence‐compressed sensing in assessing cartilage injury in osteoarthritis of the knee
PAN Ke  HUANG Xiaohua  LIU Nian  LEI Lixing  LIU Qianqian 

Cite this article as: Pan K, Huang XH, Liu N, et al. Study on application value of proton density weighted imaging accelerated with artificial intelligence‐compressed sensing in assessing cartilage injury in osteoarthritis of the knee[J]. Chin J Magn Reson Imaging, 2022, 13(10): 138-143, 156. DOI:10.12015/issn.1674-8034.2022.10.021.


[Abstract] Objective To explore the value of proton density weighted imaging (PDWI) accelerated with artificial intelligence-compressed sensing (ACS) for semiquantitatively assessing cartilage of the knee in osteoarthritis.Materials and Methods Seventy-four subjects were scanned with 3 T MRI scanner, undergoing three-plane PDWI accelerated with parallel imaging (PI), compressed sensing (CS) and ACS, respectively. The subjective image quality evaluation was performed by two radiologists using a 4‐point scale. The cartilage was divided into 14 regions. The two readers mentioned above graded cartilage abnormalities using an 8-point scale. In 15 of the subjects, the cartilages in 3 regions were graded twice at least a month apart. The Friedman test was used to analyze the differences of subjective image quality scores among PI, CS and ACS. Intra‐class correlation coefficient (ICC) was applied to assess consistency in grading cartilage abnormalities of CS‐PI and ACS‐PI. The specificity and sensitivity of CS and ACS in grading total articular cartilage injury were calculated. Cohen's Kappa was used to analyze intra‐reader agreement.Results Three‐plane PDWI accelerated with, PI, CS, ACS were acquired in 428 s, 375 s and 155 s, respectively. The subjective scores of the three-plane images were not different among the three groups (P=0.607, 0.174, 0.529, respectively). The agreement grading cartilage abnormalities in 14 regions of CS-PI, ACS‐PI were excellent (ICC ranging 0.969-0.995 and 0.951-0.987, respectively). Removing the regions with negative diagnosis in the three groups, the agreement in grading cartilage abnormalities of CS-PI, ACS-PI were still excellent (ICC ranging 0.868-0.939 and 0.842-0.948, respectively). The specificity of CS and ACS was 99.6% and 98.2%, respectively. The range of sensitivity of CS and ACS in grade 1-6 was 42.3%-100.0% and 17.3%-87.9%, respectively. Grading cartilage abnormalities showed perfect agreement (κ≥0.803) in 3 regions of 15 subjects for PI, CS and ACS.Conclusions ACS greatly accelerates multi‐plane MRI PDWI sequences while ensuring image quality, and achieve comparable diagnostic performance with sequences accelerated with parallel imaging in semi‐quantitative evaluation of multi‐region cartilage injury in knee osteoarthritis.
[Keywords] knee joint；osteoarthritis；articular cartilage；artificial intelligence-compressed sensing；proton density weighted imaging；magnetic resonance imaging

PAN Ke   HUANG Xiaohua   LIU Nian   LEI Lixing   LIU Qianqian*  

Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, China

Liu QQ, E-mail: 296131626@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Applied Technology Research and Development Project of Nanchong (No. 20YFZJ0108); Scientific Research Development Program of Affiliated Hospital of North Sichuan Medical College (No. 2022JC017).
Received  2022-06-15
Accepted  2022-10-08
DOI: 10.12015/issn.1674-8034.2022.10.021
Cite this article as: Pan K, Huang XH, Liu N, et al. Study on application value of proton density weighted imaging accelerated with artificial intelligence‐compressed sensing in assessing cartilage injury in osteoarthritis of the knee[J]. Chin J Magn Reson Imaging, 2022, 13(10): 138-143, 156. DOI:10.12015/issn.1674-8034.2022.10.021.

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