Patient-Specific 3D Spine Modeling for Coronal and Sagittal Balance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current spinal surgery methods fail to accurately align the spine in both the coronal and axial planes due to reliance on angular data from the sagittal plane, neglecting the alignment of the head with the pelvis, and lack of predictive accuracy, requiring costly and resource-intensive computational models.
Innovation Solution
A system and method for constructing a three-dimensional simulation of the spine using X-ray or CT scan data, incorporating sagittal and coronal alignment, and adjusting surgical devices based on patient-specific data to achieve balanced spinal alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional angular data from sagittal plane is used for spinal modeling, then the modeling process is simple, but the alignment accuracy in coronal and axial planes deteriorates
Solution Approach 1:
The patent transitions from 2D angular measurements in the sagittal plane to 3D spatial coordinates incorporating all three planes (sagittal, coronal, and axial). This dimensional expansion enables comprehensive spinal alignment assessment by capturing vertebral positions in three-dimensional space rather than relying solely on angular data from a single plane.
2Manufacturing precision
If comprehensive 3D spinal modeling is performed, then alignment accuracy improves, but computational resources required increase prohibitively
Solution Approach 1:
The patent creates a simplified 3D computational model that replicates essential spinal geometry and alignment characteristics without requiring full-scale detailed imaging data. This copied model enables predictive simulation of surgical outcomes using reduced computational resources while maintaining sufficient accuracy for clinical decision-making.
Solution Approach 2:
The patent transforms the computational approach by changing from processing complete high-resolution 3D spinal datasets to processing extracted key geometric parameters and simplified coordinate representations. This parameter reduction maintains the essential information needed for alignment prediction while dramatically reducing computational burden.
3Measurement precision
If detailed patient-specific 3D modeling is performed, then predictive accuracy of surgical outcomes improves, but the time required for model generation increases
Solution Approach 1:
The patent performs preliminary extraction and processing of critical spinal geometric parameters from imaging data before the actual surgical planning process. By pre-computing key alignment metrics and establishing the 3D coordinate framework in advance, the system enables rapid surgical outcome prediction without requiring time-consuming detailed modeling during the surgical planning phase.
Data Source
Figure 1
Figure 2
Figure 3
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.