Comparative analysis of computer-aided imaging collaboration: MRI versus CT for detection of knee joint injuries in athletes

Abstract

ObjectiveThis study aims to compare the diagnostic efficacy of collaborative computer-aided (CAD) imaging diagnosis techniques in detecting knee joint injuries among athletes. The focus is on analyzing the differences in diagnostic performance between Magnetic Resonance Imaging (MRI) and Multilayer Spiral Computed Tomography (MSCT). The objective is to assess the performance of these two imaging modalities in diagnosing knee joint injuries. MethodsA total of 242 suspected knee joint injury patients were enrolled in the study. The patients underwent MRI and MSCT examinations using a self-developed Knee Joint Injury CAD system for auxiliary diagnosis. The Knee Joint Injury CAD system, employing the Monte Carlo and Markov chain algorithms, was utilized to analyze MRI and CT images, assisting physicians in fracture diagnosis. False-positive annotations were removed through discussions and consultations among physicians to obtain independent detection results. Arthroscopy was utilized as the gold standard. The diagnostic results for MRI and CT assisted by the CAD software were recorded, and metrics such as diagnostic sensitivity, specificity, and overall accuracy were calculated. Furthermore, the accuracy of diagnosing bone and ligament injuries was analyzed. ResultsThe MRI diagnostic sensitivity of the collaborative Knee Joint Injury CAD system was 94.75%, with a specificity of 97.42% and an accuracy of 96.01%. In contrast, the diagnostic sensitivity of the collaborative Knee Joint Injury CAD system for MSCT was 89.36%, with a specificity of 85.71% and an accuracy of 89.86%. A comparison between the two detection methods reveals that MRI outperforms CT in terms of imaging quality but requires a longer examination time. The average imaging quality score for MRI was 6.89 ± 0.27, with an average examination time of 28.71 ± 7.64 minutes. On the other hand, the average imaging quality score for CT was 6.71 ± 0.42, with an average examination time of 9.95 ± 2.42 min. ConclusionIn diagnosing knee joint injuries, the collaborative Knee Joint Injury CAD system with MRI assistance in computer-aided medical diagnosis demonstrates higher diagnostic sensitivity, specificity, and accuracy compared to the collaborative Knee Joint Injury CAD system with MSCT. Therefore, the clinical application of a collaborative Knee Joint Injury CAD system with MRI exhibits superior diagnostic performance in knee joint injuries, especially in detecting ligament and soft tissue injuries. However, it is worth noting that a collaborative Knee Joint Injury CAD system with MRI has a higher imaging quality score and longer examination time. The trade-off between these factors needs to be considered in clinical practice, and the choice of imaging technology should be based on specific circumstances.