Freehand 3D ultrasound imaging of the femoral head and neck.

purposeTo evaluate the performance of a novel freehand 3D ultrasound system for assessing morphological deformities of the femoral head and neck associated with femoroacetabular impingement syndrome (FAIS).

methodsThe system integrates an off-the-shelf optical tracker with a low-cost point-of-care ultrasound probe. Bone surfaces were segmented from B-mode images using a deep learning feature pyramid network trained on a publicly available dataset and refined via transfer learning with curated, manually segmented images. Deterministic algorithms were used to generate bone surface point clouds and meshes. System accuracy was assessed by comparing reconstructed bone surfaces to computed tomography (CT) in four cadaveric hips and two patient hips. The system's feasibility for clinical imaging was evaluated in five healthy volunteers.

resultsThe ultrasound reconstructions achieved geometric agreement with CT, within-subject repeatability and within-subject reproducibility of 0.4-0.6 mm. Alpha angles derived from CT and ultrasound scan agreed to within 0.6°. Given that clinically significant bone deformities associated with FAIS are ≥ 2 mm and clinically significant differences in alpha angle are > 5°, the system's performance appears adequate for clinical morphometry. In vivo imaging demonstrated feasibility for clinical use.

conclusionThe combination of 3D optical tracking, ultrasound imaging, and deep learning-based segmentation using models trained on public datasets and enhanced by transfer learning can produce bone surface maps of the femoral head with sufficient accuracy to resolve clinically significant femoral head deformities. The system is suitable for clinical deployment.