Hip dysplasia (HD) leads to premature osteoarthritis. Timely detection and correction of HD has been shown to improve pain, functional status, and hip longevity. Several time-consuming radiological measurements are currently used to confirm HD. An artificial intelligence (AI) software named HIPPO automatically locates anatomical landmarks on anteroposterior pelvis radiographs and performs the needed measurements. The primary aim of this study was to assess the reliability of this tool as compared to multi-reader evaluation in clinically proven cases of adult HD. The secondary aims were to assess the time savings achieved and evaluate inter-reader assessment. A consecutive preoperative sample of 130 HD patients (256 hips) was used. This cohort included 82.3% females (n = 107) and 17.7% males (n = 23) with median patient age of 28.6 years (interquartile range (IQR) 22.5 to 37.2). Three trained readers’ measurements were compared to AI outputs of lateral centre-edge angle (LCEA), caput-collum-diaphyseal (CCD) angle, pelvic obliquity, Tönnis angle, Sharp’s angle, and femoral head coverage. Intraclass correlation coefficients (ICC) and Bland-Altman analyses were obtained.Aims
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Some patients presenting with hip pain and instability and underlying acetabular dysplasia (AD) do not experience resolution of symptoms after surgical management. Hip-spine syndrome is a possible underlying cause. We hypothesized that there is a higher frequency of radiological spine anomalies in patients with AD. We also assessed the relationship between radiological severity of AD and frequency of spine anomalies. In a retrospective analysis of registry data, 122 hips in 122 patients who presented with hip pain and and a final diagnosis of AD were studied. Two observers analyzed hip and spine variables using standard radiographs to assess AD. The frequency of lumbosacral transitional vertebra (LSTV), along with associated Castellvi grade, pars interarticularis defect, and spinal morphological measurements were recorded and correlated with radiological severity of AD.Aims
Methods