3D Spine Morphology Simulation for Faster Surgical Prediction
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Solution Overview
Problem
Current spinal surgery models fail to accurately align the spine in coronal and axial planes, lack consideration of the head-pelvis alignment, and struggle with high computational costs and resource intensity, leading to partial corrections and inaccurate post-surgical predictions.
Innovation Solution
A system and method for rapidly generating three-dimensional simulations of spinal morphology using x-ray or CT scan data, incorporating skeletal structures, allowing for customization and prediction of surgical outcomes by morphing a generic model with patient-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If comprehensive three-dimensional spinal modeling is performed including all skeletal structures, then accuracy of surgical prediction is improved, but computational resources and time required increase prohibitively
Solution Approach 1:
The system segments the skeletal system into modular components (spine, pelvis, skull, extremities) that can be independently modeled and transformed. Each bone is represented as a separate transformable element with defined joint relationships, allowing selective modeling of relevant structures rather than complete system simulation.
Solution Approach 2:
The system creates simplified virtual copies of the patient's skeletal structures from medical images (X-ray, CT, MRI). These virtual models replicate essential geometric and spatial relationships without requiring full computational complexity of the original anatomical structures, enabling rapid simulation and prediction.
2Manufacturing precision
If detailed morphological simulation of spinal curvature is performed, then accuracy of post-surgical result prediction is improved, but computation time increases significantly
Solution Approach 1:
The system performs preliminary registration and alignment of virtual skeletal models with patient-specific anatomical data before surgical simulation. Reference frames are established in advance using anatomical landmarks, and transformation parameters are pre-calculated, enabling rapid what-if analysis during surgical planning without repeated complex computations.
Solution Approach 2:
The system represents spinal morphology using key geometric parameters (curvature angles, vertebral positions, pelvic tilt) rather than full three-dimensional surface models. This parameterized approach allows efficient modification and simulation of different surgical outcomes by changing specific parameters without reprocessing entire anatomical models.
3Reliability
If alignment in all three planes (sagittal, coronal, axial) is considered, then completeness of spinal correction is improved, but model complexity and data requirements increase
Solution Approach 1:
The system extends traditional two-dimensional spinal alignment assessment into three-dimensional space by incorporating coronal and axial plane measurements with sagittal plane data. Virtual models are transformed and visualized across all three anatomical planes simultaneously, allowing comprehensive evaluation of spinal alignment and surgical outcomes in three-dimensional space.
Solution Approach 2:
The system creates a universal coordinate framework that simultaneously handles measurements and transformations in all three anatomical planes. The same virtual model and transformation algorithms work across sagittal, coronal, and axial views, providing multi-functional capability for comprehensive spinal assessment without requiring separate modeling systems for each plane.
Data Source
AI summary
Disclosed are systems and methods for rapid generation of simulations of a patient's spinal morphology that enable pre-operative viewing of a patient's condition and to assist surgeons in determining the best corrective procedure and with any of the selection, augmentation or manufacture of spinal devices based on the patient specific simulated condition. The simulation is generated by morphing a generic spine model with a three-dimensional curve representation of the patient's particular spinal morphology derived from existing images of the patient's condition. Other anatomical structures in the patient's skeletal system are likewise simulated by morphing a generic normal skeletal model, as applicable, particularly those skeletal entities that are connected directly or indirectly to the spinal column.