Prediction outcomes for anterior vertebral body growth modulation surgery from discriminant spatiotemporal manifolds.

PURPOSE: Anterior vertebral body growth modulation (AVBGM) is a minimally invasive surgical technique that gradually corrects spine deformities while preserving lumbar motion. However, identifying suitable patients for surgery is based on clinical judgment and surgical experience. This process would be facilitated by the identification of patients responding to AVBGM prior to surgery using data-driven models trained on previous instrumented cases. METHODS: We introduce a statistical framework for predicting the surgical outcomes following AVBGM in adolescents with idiopathic scoliosis. A discriminant manifold is first constructed to maximize the separation between responsive and non-responsive groups of patients treated with AVBGM for scoliosis. The model then uses subject-specific correction trajectories based on articulated transformations in order to map spine correction profiles to a group-average piecewise-geodesic path. Spine correction trajectories are described in a piecewise-geodesic fashion to account for varying times at follow-up examinations, regressing the curve via a quadratic optimization process. To predict the evolution of correction, a baseline reconstruction is projected onto the manifold, from which a spatiotemporal regression model is built from parallel transport curves inferred from neighboring exemplars. RESULTS: The model was trained on 438 reconstructions and tested on 56 subjects using 3D spine reconstructions from follow-up examinations, with the probabilistic framework yielding accurate results with differences of [Formula: see text] in main curve angulation and a classification rate of 83.2%, and generating models similar to biomechanical simulations. CONCLUSION: The proposed method achieved a higher prediction accuracy and improved the modeling of spatiotemporal morphological changes in surgical patients treated with AVBGM.

Computer-assisted pedicle screw trajectory planning using CT-inferred bone density: A demonstration against surgical outcomes.

PURPOSE: Image-guided spine surgery and preoperative computer-assisted planning provide spine surgeons with tools to improve the safety, accuracy, and reliability of pedicle screw placement. The purpose of this study is to demonstrate a computer-assisted pedicle screw placement planning tool in comparison to screws as delivered by a spine surgeon. METHODS: We describe a novel computer-assisted tool for preoperative pedicle screw placement planning in computed tomography (CT) images, designed with respect to the vertebral shape and structure, and augmented with respect to the considerations of surgical practice. The approach is based on three-dimensional (3D) modeling of the vertebral body and pedicles, and planning of the pedicle screw size and insertion trajectory by maximizing the screw fastening strength, evaluated through CT-inferred bone density maps. The approach is augmented by yielding screw plans consistent with the straight-forward surgical technique of aligning screws parallel to vertebral endplates, and the screw entry points following the spinal curvature to facilitate rod attachment. For a cohort of 25 patients, placement plans were retrospectively obtained for 204 pedicle screws with the computer-assisted tool from preoperative CT images, while reference trajectories of inserted pedicle screws were reconstructed in 3D from postoperative biplanar radiographs. RESULTS: The best performing version of the computer-assisted tool achieved clinically acceptable preoperative pedicle screw placement plans in 96.6% of the cases, while the comparison to the postoperative reconstructions resulted in 3.4 ± 2.5 mm for the screw entry point location, 2.7 ± 1.6 mm for the screw crossing point location, and 7.4 ± 5.3∘ for the screw sagittal inclination (mean absolute difference ± standard deviation). CONCLUSION: Quantitative comparison revealed that the preoperative placement plans are consistent with the postoperative results, and that the computer-assisted tool integrating bone density and surgical constraints can successfully incorporate important aspects of pedicle screw placement. The results therefore confirm the accuracy of the tool prior to being integrated in an image-guidance system.

Biomechanically driven intraoperative spine registration during navigated anterior vertebral body tethering.

The integration of pre-operative biomechanical planning with intra-operative imaging for navigated corrective spine surgery may improve surgical outcomes, as well as the accuracy and safety of manoeuvres such as pedicle screw insertion and cable tethering, as these steps are performed empirically by the surgeon. However, registration of finite element models (FEMs) of the spine remains challenging due to changes in patient positioning and imaging modalities. The purpose of this study was to develop and validate a new method registering a preoperatively constructed patient-specific FEM aimed to plan and assist anterior vertebral body tethering (AVBT) of scoliotic patients, to intraoperative cone beam computed tomography (CBCT) during navigated AVBT procedures. Prior to surgery, the 3D reconstruction of the patient's spine was obtained using biplanar radiographs, from which a patient-specific FEM was derived. The surgical plan was generated by first simulating the standing to intraoperative decubitus position change, followed by the AVBT correction techniques. Intraoperatively, a CBCT was acquired and an automatic segmentation method generated the 3D model for a series of vertebrae. Following a rigid initialization, a multi-level registration simulation using the FEM and the targeted positions of the corresponding reconstructed vertebrae from the CBCT allows for the refinement of the alignment between modalities. The method was tested with 18 scoliotic cases with a mean thoracic Cobb angle of 47° ± 7° having already undergone AVBT. The translation error of the registered FEM vertebrae to the segmented CBCT spine was 1.4 ± 1.2 mm, while the residual orientation error was 2.7° ± 2.6°, 2.8° ± 2.4° and 2.5° ± 2.8° in the coronal, sagittal, and axial planes, respectively. The average surface-to-surface distance was 1.5 ± 1.2 mm. The proposed method is a first attempt to use a patient-specific biomechanical FEM for navigated AVBT, allowing to optimize surgical strategies and screw placement during surgery.

Variability Analysis of Manual and Computer-Assisted Preoperative Thoracic Pedicle Screw Placement Planning.

STUDY DESIGN: A comparison among preoperative pedicle screw placement plans, obtained from computed tomography (CT) images manually by two spine surgeons and automatically by a computer-assisted method. OBJECTIVE: To analyze and compare the manual and computer-assisted approach to pedicle screw placement planning in terms of the inter- and intraobserver variability. SUMMARY OF BACKGROUND DATA: Several methods for computer-assisted pedicle screw placement planning have been proposed; however, a systematic variability analysis against manual planning has not been performed yet. METHODS: For 256 pedicle screws, preoperative placement plans were determined manually by two experienced spine surgeons, each independently performing two sets of measurements by using a dedicated software for surgery planning. For the same 256 pedicle screws, preoperative placement plans were also obtained automatically by a computer-assisted method that was based on modeling of the vertebral structures in 3D, which were used to determine the pedicle screw size and insertion trajectory by maximizing its fastening strength through the underlying bone mineral density. RESULTS: A total of 1024 manually (2 observers × 2 sets × 256 screws) and 256 automatically (1 computer-assisted method × 256 screws) determined preoperative pedicle screw placement plans were obtained and compared in terms of the inter- and intraobserver variability. A large difference was observed for the pedicle screw sagittal inclination that was, in terms of the mean absolute difference and the corresponding standard deviation, equal to 18.3°â€Š±â€Š7.6° and 12.3°â€Š±â€Š6.5°, respectively for the intraobserver variability of the second observer and for the interobserver variability between the first observer and the computer-assisted method. CONCLUSION: The interobserver variability among the observers and the computer-assisted method is within the intraobserver variability of each observer, which indicates on the potential use of the computer-assisted approach as a useful tool for spine surgery that can be adapted according to the preferences of the surgeon. LEVEL OF EVIDENCE: 3.

Computer-Assisted Screw Size and Insertion Trajectory Planning for Pedicle Screw Placement Surgery.

Pathological conditions that cause instability of the spine are commonly treated by vertebral fixation involving pedicle screw placement surgery. However, existing methods for preoperative planning are based only on geometrical properties of vertebral structures (i.e., shape) without taking into account their structural properties (i.e., appearance). We propose a novel automated method for computer-assisted preoperative planning of the thoracic pedicle screw size and insertion trajectory. The proposed method extracts geometrical properties of vertebral structures by parametric modeling of vertebral bodies and pedicles in three dimensions (3D), and combines them with structural properties, evaluated through underlying image intensities in computed tomography (CT) images while considering the guidelines for pedicle screw design. The method was evaluated on 81 pedicles, obtained from 3D CT images of 11 patients that were appointed for pedicle screw placement surgery. In terms of mean absolute difference (MAD) and corresponding standard deviation (SD), the resulting high modeling accuracy of 0.39±0.31 mm for 3D vertebral body models and 0.31±0.25 mm for 3D pedicle models created an adequate anatomical frame for 3D pedicle screw models. When comparing the automatically obtained and manually defined plans for pedicle screw placement, a relatively high agreement was observed, with MAD ±SD of 0.4±0.4 mm for the screw diameter, 5.8±4.2 mm for the screw length, 2.0±1.4 mm for the pedicle crossing point and 7.6±5.8(°) for screw insertion angles. However, a statistically significant increase of 48±26% in the screw fastening strength in favor of the proposed automated method was observed in 99% of the cases.