Article: Deep learning-assisted diagnosis of femoral trochlear dysplasia based on magnetic resonance imaging measurements.
World journal of clinical cases
2023 Volume 11, Issue 7, Page(s) 1477–1487
Abstract: Background: Femoral trochlear dysplasia (FTD) is an important risk factor for patellar instability. Dejour classification is widely used at present and relies on standard lateral X-rays, which are not common in clinical work. Therefore, magnetic ... ...
Abstract | Background: Femoral trochlear dysplasia (FTD) is an important risk factor for patellar instability. Dejour classification is widely used at present and relies on standard lateral X-rays, which are not common in clinical work. Therefore, magnetic resonance imaging (MRI) has become the first choice for the diagnosis of FTD. However, manually measuring is tedious, time-consuming, and easily produces great variability. Aim: To use artificial intelligence (AI) to assist diagnosing FTD on MRI images and to evaluate its reliability. Methods: We searched 464 knee MRI cases between January 2019 and December 2020, including FTD ( Results: The accuracy, sensitivity, specificity, positive predictive value and negative predictive value of the AI model ranged from 0.74-0.96. All values were superior to junior doctors and intermediate doctors, similar to senior doctors. However, diagnostic time was much lower than that of junior doctors and intermediate doctors. Conclusion: The diagnosis of FTD on knee MRI can be aided by AI and can be achieved with a high level of accuracy. |
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Language | English |
Publishing date | 2023-03-12 |
Publishing country | United States |
Document type | Journal Article |
ISSN | 2307-8960 |
ISSN | 2307-8960 |
DOI | 10.12998/wjcc.v11.i7.1477 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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