Background

Computed tomography (CT)-derived acetabular angles are commonly used in the diagnosis of hip dysplasia, but the measurements are labor-intensive, with higher inter- and intra-operator variation, necessitating an automated method.

Purpose

To develop and validate an automatic method for segmenting the acetabular lunate surface and measure diagnostic angles using CT images to improve diagnosis and preoperative planning for patients with hip dysplasia.

Material and Methods

We developed a method to segment the acetabular lunate surface, automatically identify five landmark points (center, anterior, posterior, lateral, and medial) and calculate diagnostic angles for center-edge (CE), anterior-sector (AASA), posterior-sector (PASA), acetabular anteversion (AcAV), and acetabular-index (AI). The method was validated against repeated manual measurements by three raters on a dataset of 18 patients (36 hips).

Results

No differences between raters and the automatic method for the center (P = 0.18), anterior (P = 0.55), posterior (P = 0.18), lateral (P = 0.13), and medial (P = 0.12) landmarks. No statistically significant differences were observed between raters and the automatic method for the AASA (P = 0.01) and PASA (P = 0.08) angles. Statistically significant differences were found between the automatic method and rater 3 for the CE and AI angles, and between the automatic method and rater 2 for the AcAV angle. The ICC for all angle measurements by raters and the automated method was in the range of 0.90–0.99.

Conclusion

With similar agreement between manual and automatic measurements, the automatic method provides important information that may be used for both diagnosis and surgical planning, with the potential to greatly reduce the time used for analysis per patient.

Search results

Lunate extract: fully automatic acetabular lunate segmentation and hip angle measurements