Heliyon (Sep 2024)

Quantitative assessment of rotator cuff injuries using synthetic MRI and IDEAL-IQ imaging techniques

  • Zhaorong Tian,
  • Yabo Ni,
  • Hua He,
  • Bo Tian,
  • Rui Gong,
  • Fenling Xu,
  • Zhijun Wang

Journal volume & issue
Vol. 10, no. 17
p. e37307

Abstract

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Purpose: To evaluate synthetic magnetic resonance imaging (SyMRI) and iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL-IQ) imaging for a comprehensive evaluation of rotator cuff injuries (RCI). Methods: Ninety-seven patients with RCI were classified into four groups based on the arthroscopic results: (grade II), partial tear (grade III), complete tear (grade IV), and controls (grade I). T1 (Transverse Relaxation Time 1), T2 (Transverse Relaxation Time 2), proton density (PD), and fat fraction (FF) were evaluated using SyMRI and IDEAL-IQ. Measurement reliability was assessed using intraclass correlation coefficients (ICC). The diagnostic potential for grading RCI was evaluated using ordinal regression and ROC analyses. Results: A high measurement reliability (ICC > 0.7) was observed across subregions. T1 and T2 significantly varied across grades, particularly T2 in the lateral subregion between grades III and IV (P < 0.001) and the central subregion between grades II and III (P < 0.001). ROC analyses yielded valuable diagnostic accuracy, including T2 in the lateral subregion with an AUC of 0.891, distinguishing grade I from grade IV. Positive correlations were found between T2 values in specific shoulder subregions and injury grade (r = 0.615 for lateral, r = 0.542 for medial, both P < 0.001). In grade IV, FF was notably increased in the supraspinatus, infraspinatus, and subscapularis muscles compared with grades I-III. There were no significant FF variations in the teres minor muscle among grades. Conclusions: Quantitative MRI parameters from SyMRI and IDEAL-IQ, especially T2 and FF, may classify and assess RCI severity. The results could help improve the accuracy of diagnosing different grades of RCI, offering clinicians additional tools for improving patient outcomes through personalized medicine.

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