AUTHOR=Sha Jia , Huang Luyu , Chen Yaopeng , Fan Zongzhi , Lin Jincong , Yang Qinghai , Li Yi , Yan Yabo TITLE=Clinical thought-based software for diagnosing developmental dysplasia of the hip on pediatric pelvic radiographs JOURNAL=Frontiers in Pediatrics VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2023.1080194 DOI=10.3389/fped.2023.1080194 ISSN=2296-2360 ABSTRACT=Background

The common methods of radiographic diagnosis of developmental dysplasia of the hip (DDH) include measuring hip parameters and quantifying the degree of hip dislocation. However, clinical thought-based analysis of hip parameters may be a more effective way to achieve expert-like diagnoses of DDH. This study aims to develop a diagnostic strategy-based software for pediatric DDH and validate its clinical feasibility.

Methods

In total, 543 anteroposterior pelvic radiographs were retrospectively collected from January 2017 to December 2021. Two independent clinicians measured four diagnostic indices to compare the diagnoses made by the software and conventional manual method. The diagnostic accuracy was evaluated using the receiver operator characteristic (ROC) curves and confusion matrix, and the consistency of parametric measurements was assessed using Bland-Altman plots.

Results

In 543 cases (1,086 hips), the area under the curve, accuracy, sensitivity, and specificity of the software for diagnosing DDH were 0.988–0.994, 99.08%–99.72%, 98.07%–100.00%, and 99.59%, respectively. Compared with the expert panel, the Bland-Altman 95% limits of agreement for the acetabular index, as determined by the software, were −2.09°–2.91° (junior orthopedist) and −1.98°–2.72° (intermediate orthopedist). As for the lateral center-edge angle, the 95% limits were −3.68°–5.28° (junior orthopedist) and −2.94°–4.59° (intermediate orthopedist).

Conclusions

The software can provide expert-like analysis of pelvic radiographs and obtain the radiographic diagnosis of pediatric DDH with great consistency and efficiency. Its initial success lays the groundwork for developing a full-intelligent comprehensive diagnostic system of DDH.