The role of imaging parameters in the diagnosis of developmental dysplasia of the hip based on artificial intelligence: A perspective

Abstract

Developmental dysplasia of the Hip (DDH) is a common pediatric orthopedic disease, characterized primarily by abnormal development of the hip joint structure. The clinical objective is the early detection, diagnosis, and treatment. Current diagnostic strategies rely on a combination of physical examination and imaging assessment, with particular emphasis on the comprehensive assessment of multiple imaging parameters. In recent years, the integration of Artificial Intelligence (AI) with medical imaging has enhanced the accuracy and objectivity of DDH diagnosis and management. Nevertheless, current research still faces model limitations and variability in imaging acquisition protocols. This article provides a comprehensive overview of the anatomical foundations of DDH-related imaging parameters, their clinical significance, and the latest advancements in AI application. It initially details the measurement of hip joint imaging parameters, then discusses their quantitative contributions to clinical decision-making through predictive modeling, and finally explores the innovative use of AI in imaging interpretation while addressing existing technical constraints, with the aim of advancing precision medicine in the context of DDH.