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Published in: Journal of Orthopaedic Surgery and Research 1/2024

Open Access 01-12-2024 | Magnetic Resonance Imaging | Research article

Factors influencing the posterior cruciate ligament buckling phenomenon—a multiple linear regression analysis of bony and soft tissue structures of the knee joint

Authors: Jiaying Zhang, Tianwen Huang, Zhenyu Jia, Yangyang Yang, Tsung-Yuan Tsai, Pingyue Li

Published in: Journal of Orthopaedic Surgery and Research | Issue 1/2024

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Abstract

Purpose

To determine whether posterior cruciate ligament (PCL) buckling (angular change) is associated with anterior cruciate ligament (ACL) status (intact or ruptured), meniscal bone angle (MBA), anterior tibial translation (ATT), body weight, femoral-tibial rotation (FTR), posterior tibial slope (PTS), PCL length and femoral-tibial distance (FTD) and to identify the factors that have the greatest influence.

Methods

All enrolled participants were scanned with a 3.0 T, 8-channel coil MRI system (Magnetom Verio; Siemens). Bone and soft tissue parameters were measured by MIMICS software for each subject and each measured parameter was correlated with PCL buckling phenomena. The correlated and statistically significant parameters were then analyzed by multiple linear regression to determine the magnitude of the effect of the different parameters on the PCL buckling phenomenon.

Results

A total of 116 subjects (50 ACL ruptured and 66 age, weight and height matched volunteers with uninjured knees) were enrolled. Among all measured parameters, there were 8 parameters that correlated with PCL angle (PCLA), of which ACL status had the strongest correlation with PCLA (r = − 0.67, p =  < 0.001); and 7 parameters that correlated with PCL-posterior femoral cortex angle (PCL-PCA), of which ATT had the strongest correlation with PCL-PCA (r = 0.69, p =  < 0.001). PCLIA was not significantly correlated with any of the measured parameters. Multiple linear regression analyses revealed four parameters can explain PCLA, of which ACL status had the strongest effect on PCLA (absolute value of standardized coefficient Beta was 0.508). Three parameters can explain PCL-PCA, of which ATT had the strongest effect on PCLIA (r = 0.69, p = < 0.001), ATT has the greatest effect on PCL-PCA (absolute value of normalized coefficient Beta is 0.523).

Conclusions

PCLA may be a simple and easily reproducible and important supplement for the diagnosis of ACL injury; PCL-PCA is a simple and easily reproducible and important complementary tool for the detection of ATT. The use of PCLA is more recommended to aid in the diagnosis of ACL injury.
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Metadata
Title
Factors influencing the posterior cruciate ligament buckling phenomenon—a multiple linear regression analysis of bony and soft tissue structures of the knee joint
Authors
Jiaying Zhang
Tianwen Huang
Zhenyu Jia
Yangyang Yang
Tsung-Yuan Tsai
Pingyue Li
Publication date
01-12-2024
Publisher
BioMed Central
Published in
Journal of Orthopaedic Surgery and Research / Issue 1/2024
Electronic ISSN: 1749-799X
DOI
https://doi.org/10.1186/s13018-024-04739-3

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