An automated optimization pipeline for clinical-grade computer-assisted planning of high tibial osteotomies under consideration of weight-bearing.

3D preoperative planning for high tibial osteotomies (HTO) has increasingly replaced 2D planning but is complex, time-consuming and therefore expensive. Several interdependent clinical objectives and constraints have to be considered, which often requires multiple rounds of revisions between surgeons and biomedical engineers. We therefore developed an automated preoperative planning pipeline, which takes imaging data as an input to generate a ready-to-use, patient-specific planning solution. Deep-learning based segmentation and landmark localization was used to enable the fully automated 3D lower limb deformity assessment. A 2D-3D registration algorithm allowed the transformation of the 3D bone models into the weight-bearing state. Finally, an optimization framework was implemented to generate ready-to use preoperative plannings in a fully automated fashion, using a genetic algorithm to solve the multi-objective optimization (MOO) problem based on several clinical requirements and constraints. The entire pipeline was evaluated on a large clinical dataset of 53 patient cases who previously underwent a medial opening-wedge HTO. The pipeline was used to automatically generate preoperative solutions for these patients. Five experts blindly compared the automatically generated solutions to the previously generated manual plannings. The overall mean rating for the algorithm-generated solutions was better than for the manual solutions. In 90% of all comparisons, they were considered to be equally good or better than the manual solution. The combined use of deep learning approaches, registration methods and MOO can reliably produce ready-to-use preoperative solutions that significantly reduce human workload and related health costs.

Pedicle subtraction osteotomy with patient-specific instruments.

BACKGROUND: Although the utility of patient-specific instruments (PSI) has been well established for complex osteotomies in orthopedic surgery, it is yet to be comparatively analyzed for complex spinal deformity correction, such as pedicle subtraction osteotomy (PSO). METHODS: Six thoracolumbar human cadavers were used to perform nine PSOs using the free-hand (FH) technique and nine with PSI (in total 18 PSOs). Osteotomy planes were planned on the basis of preoperative computed tomography (CT). A closing-wedge angle of 30° was targeted for each PSO. Postoperative CT scans were obtained to measure segmental lordosis correction and the deviation from the planned 30° correction as well as the osseous gap of posterior elements. RESULTS: The time required to perform a PSO was 18:22 (range 10:22-26:38) min and 14:14 (range 10:13-22:16) min in the PSI and FH groups, respectively (p = 0.489). The PSI group had a significantly higher lordosis gain (29°, range 23-31° vs. 21°, range 13-34°; p = 0.015). The lordosis gain was significantly more accurate with PSI (deviation angle: 1°; range 0-7°) than with the FH technique (9°; range 4-17°; p = 0.003). PSI achieved a significantly smaller residual osseous gap of the posterior elements (5 mm; range 0-9 mm) than the FH group (11 mm; range 3-27 mm; p = 0.043).With PSI, an angular difference of 3° (range 1-12°), a translational offset of 1 (range 0-6) mm at the level of the lamina, and a vertebral body entry point deviation of 1 (range 0-4) mm was achieved in the osteotomies. CONCLUSIONS: PSI-guided PSO can be a more feasible and accurate approach in achieving a planned lordosis angle than the traditional FH technique in a cadaver model. This approach further reduced osseous gaps, potentially promoting higher fusion rates in vivo.