Zhang Jiaying, Huang Tianwen, Jia Zhenyu, Yang Yangyang, Tsai Tsung-Yuan, Li Pingyue
Department of Graduate School, Guangzhou University of Chinese Medicine, 12 Airport Road, Guangzhou, 510405, Guangdong, People's Republic of China.
Guangdong Key Lab of Orthopedic Technology and Implant, General Hospital of Southern Theater Command of PLA, The First School of Clinical Medicine, Southern Medical University, Guangzhou, People's Republic of China.
J Orthop Surg Res. 2024 May 3;19(1):277. doi: 10.1186/s13018-024-04739-3.
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.
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.
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).
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.
确定后交叉韧带（PCL）屈曲（角度变化）是否与前交叉韧带（ACL）状态（完整或断裂）、半月板骨角度（MBA）、胫骨前移（ATT）、体重、股胫旋转（FTR）、胫骨后倾（PTS）、PCL长度和股胫距离（FTD）相关，并确定影响最大的因素。
所有纳入的参与者均使用3.0T、8通道线圈MRI系统（Magnetom Verio；西门子）进行扫描。通过MIMICS软件为每个受试者测量骨骼和软组织参数，并将每个测量参数与PCL屈曲现象相关联。然后通过多元线性回归分析相关且具有统计学意义的参数，以确定不同参数对PCL屈曲现象的影响程度。
共纳入116名受试者（50名ACL断裂者和66名年龄、体重和身高匹配的膝关节未受伤志愿者）。在所有测量参数中，有8个参数与PCL角度（PCLA）相关，其中ACL状态与PCLA的相关性最强（r = -0.67，p = <0.001）；有7个参数与PCL-股骨后皮质角度（PCL-PCA）相关，其中ATT与PCL-PCA的相关性最强（r = 0.69，p = <0.001）。PCLIA与任何测量参数均无显著相关性。多元线性回归分析显示，四个参数可解释PCLA，其中ACL状态对PCLA的影响最强（标准化系数Beta的绝对值为0.508）。三个参数可解释PCL-PCA，其中ATT对PCLIA的影响最强（r = 0.69，p = <0.001），ATT对PCL-PCA的影响最大（标准化系数Beta的绝对值为0.523）。
PCLA可能是诊断ACL损伤的一种简单、易于重复且重要的补充方法；PCL-PCA是检测ATT的一种简单、易于重复且重要的辅助工具。更推荐使用PCLA来辅助诊断ACL损伤。
