Research
HIP-AI
Background
Developmental dysplasia of the hip (DDH) occurs 3-4% of infants before the age of six months. Early detection of DDH, with the first six months after birth, allows for effective treatment. In the Netherlands, early detection of DDH is integrated into the Child Health Care (CHC) disease prevention program and is performed at the CHC centers. Screening is based on identifying risk factors (physical examination, breech position, family history) and when an infant is deemed at risk, it is referred to a hospital for an ultrasound. The sensitivity of this current prevention program without ultrasound is 86%, implying that approximately one out of seven infants with DDH remains undiagnosed at an early stage. In addition, the specificity of this screening is 82%, which means that approximately 6 out of 7 referred infants do not have DDH.
Ultrasonographic examination stands as the global gold standard for diagnosing DDH. Since a well-trained sonographer is crucial for accurate ultrasound-based classification of DDH, diagnosis cannot be performed at the CHC center because it requires months of training. Within this research, artificial intelligence (AI) is used to enable a guided ultrasound acquisition of the infant hip at the CHC center to establish a universal and consistent screening system, provide appropriate care at the right place, minimize interrater variances, enhance sensitivity, and contribute to cost reduction.