Background Anterior cruciate ligament (ACL) injuries have been increasing significantly over time. The relationship between the ACL injury and the knee joint structures is poorly understood. The purpose of this study is to examine whether the measurements of different structures in the knee joint are linked with ACL injury in affected patients. Methods This retrospective case–control study included patients who suffered from ACL tears and underwent magnetic resonance imaging (MRI). A control group of patients with no knee pathologies on MRI was included. Fourteen knee variables, including lateral meniscus (LM) posterior horn height, length, depth, and volume; medial meniscus (MM) posterior horn height, length, depth, and volume; lateral and medial (MFC) femoral condyle sphere diameter; lateral and medial tibial plateau length; and patella tendon horizontal and vertical diameter, were collected. A multivariate logistic regression including LM posterior horn depth, MM posterior horn length, MM volume, MFC sphere diameter, and patella tendon horizontal diameter and receiver operating characteristic curve, was used to compare the two groups. Results A total of 85 patients were included in our study; 54 suffered from ACL injuries and 31 as a control group with normal knee MRI. Logistic regression revealed that increased LM posterior horn depth (OR = 1.27; 95% CI = 1.03–1.56; p = 0.028), decreased MM posterior horn length (OR = 0.71; 95% CI = 0.55–0.93; p = 0.013), and MFC sphere diameter (OR = 1.20; 95% CI = 1.01–1.43; p = 0.035) were independent risk factors for ACL rupture. The MFC sphere diameter yielded the highest area under the curve: 0.747 (95% CI, 0.632–0.862). No difference was found in the other measurements between the two groups. Conclusions Concerning the difference in anatomical variations, the lateral meniscus posterior horn depth and medial femoral condyle sphere diameter were higher, while medial meniscus posterior horn length was lower in patients with an ACL injury. These structural knee measurements could have a possible increase in the likelihood of sustaining an ACL injury and can be used by clinicians to predict ACL injury.
There is a paucity of osteometric standards for sex estimation from unknown skeletal remains in Jordan and the sexual dimorphism of the sternum has not yet been investigated. The aim of this study was to evaluate the sexual dimorphism in sternal measurements using 3D multidetector computed tomography (MDCT), and to assess their reliability for sex estimation in a Jordanian population. A total of 600 MDCT scans (300 males and 300 females) were used and a total of 8 sternal measurements were studied (manubrium length, sternal body length, combined length of manubrium and body, corpus sterni width at 1st and 3rd sternebrae, sternal index and area). Sexual dimorphism was evaluated by means of discriminant function analyses. Significant sexual dimorphism was found mainly in middle-aged and older adults. Including all subjects, multivariate, and stepwise functions gave an overall accuracy of 83.0% and 84.0%, respectively. Additionally, multivariate and stepwise analyses were conducted separately for each age group. The accuracy of sex estimation in multivariate analysis (all variables) varied from 63.2% in the young, and 83.7% in the middle adults to 84.9% for older adults. In stepwise analysis, the highest accuracy rates were provided by only sternal area in young adults (81.6%), and sternal area combined with sternal body length in middle-aged and older adults (84.2% and 85.3%, respectively). The best sex discriminator using univariate analysis (single variable) was sternal area followed by sternal body length (84.0% and 80.8% respectively). Notably, univariate analyses for most variables gave relatively higher classification accuracies in females but were poor at predicting males in the sample (sex bias ranged between −6.4% and −20%). Our data suggest that dimorphism in the human sternum increases with advancing age and separate discriminant functions are needed for each age group in Jordanians. In addition, multivariate and stepwise analyses using sternum gave higher classification accuracies with comparatively lower sex biases compared to univariate analyses.
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