A new modified MR dual precision positioning of thin-slice oblique sagittal fat suppression proton density weighted imaging: its diagnostic accuracy in anterior cruciate ligament injury

Author:

Li Kun,Jhonatan Felix Young,Yu Zhaohui,Liu Jiachen,Huang Lixin,Yang Huilin,Du Jun

Abstract

AbstractTo evaluate the diagnostic accuracy of a new modified MR dual precision positioning of thin-slice oblique sagittal fat suppression proton density-weighted imaging (DPP-TSO-Sag-FS-PDWI) sequence in detecting ACL injuries and its grades compared to standard sequences using arthroscopy as the standard reference. 42 patients enrolled in this retrospective study received the 1.5-T MRI with standard sequences and the new modified DPP-TSO-Sag-FS-PDWI sequence, and their arthroscopy results was recorded. The Mc Nemer-Bowker and weighted Kappa was performed to compare the consistency of MRI diagnosis with arthroscopic results. Finally, the diagnostic accuracy was calculated based on the true positive, true negative, false negative and false positive values. The diagnostic consistency of the DPP-TSO-Sag-FS-PDWI were higher than standard sequences for both reader 1 (K = 0.876 vs. 0.620) and reader 2 (K = 0.833 vs. 0.683) with good diagnostic repeatability (K = 0.794 vs. 0.598). Furthermore, the DPP-TSO-Sag-FS-PDWI can classify and diagnose three grades of ACL injury [the sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value were more than 84%], especially for grade II injury as the PPV was superior for reader 1 (92.3% vs. 53.9%) and reader 2 (84.6% vs. 69.2%). The new modified DPP-TSO-Sag-FS-PDWI sequence can display the ACL injury on one or continuous levels by maximizing the acquisition of complete ligament shape and true anatomical images, and excluding the influence of anatomical differences between individuals. It can improve the diagnostic accuracy with good repeatability and classify three grades of the ACL injury.

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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