Patient-Specific Spinal Alignment Modeling for PJK Prediction
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Solution Overview
Problem
Existing spinal fusion surgeries face challenges due to surgical complications such as proximal junctional kyphosis (PJK) and adjacent segment disease, which are difficult to predict and mitigate, despite the use of realignment criteria like Roussouly, SRS-Schwab, and GAP scores, as they are multifactorial and influenced by vertebral loading and muscle expenditure.
Innovation Solution
A computer-implemented method and system for generating patient-specific spinal alignments using pre-operative images, computing metrics of muscle expenditure and vertebral loading, simulating alignments, and predicting mechanical complications, including finite element analysis to optimize sagittal alignment and reduce risks of PJK and adjacent segment disease.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional realignment criteria (Roussouly, SRS-Schwab, GAP) are used in spinal fusion surgery, then surgical procedures can be performed with established guidelines, but mechanical complications such as proximal junctional kyphosis and adjacent segment disease occur due to inadequate prediction of vertebral loading and muscle expenditure
Solution Approach 1:
The patent replaces traditional mechanical and visual alignment assessment methods with computer-based simulations. The system uses computational models to calculate vertebral loading and muscle expenditure, substituting physical measurement techniques with digital modeling and analysis to predict mechanical complications more accurately.
Solution Approach 2:
The patent performs preliminary computer simulations and calculations of vertebral loading and muscle expenditure before surgery. By conducting these assessments preoperatively, the system allows surgeons to evaluate different alignment scenarios and predict complications before the actual surgical intervention, enabling better planning and decision-making.
2Measurement precision
If comprehensive computer simulations and finite element analysis are performed to assess vertebral loading and muscle expenditure, then prediction accuracy of mechanical complications improves, but computational complexity and processing requirements increase
Solution Approach 1:
The patent segments the complex computational task into distinct modules: image processing to extract spinal geometry, construction of computer models representing vertebral structures, finite element analysis for loading calculations, and muscle expenditure computation. This segmentation allows each component to be optimized independently and facilitates implementation on standard computing hardware.
Solution Approach 2:
The patent introduces computer models as intermediary representations between physical spinal anatomy and computational analysis. These models serve as simplified yet accurate representations that enable complex finite element analysis without requiring direct measurement of actual vertebral loading, bridging the gap between physical reality and computational prediction.
3Reliability
If patient-specific computer models and finite element analysis are used to optimize spinal alignment, then surgical outcomes improve by reducing mechanical complications, but processing time and computational resources increase
Solution Approach 1:
The patent performs all complex computational analyses, including finite element analysis and muscle expenditure calculations, in the preoperative planning phase. By completing these time-consuming computations before surgery, the system provides surgeons with optimized alignment recommendations without delaying the actual surgical procedure, thus sacrificing preoperative time to preserve intraoperative time.
Solution Approach 2:
The patent creates digital copies (computer models) of the patient's spinal anatomy from preoperative images. These virtual replicas allow for extensive simulation and analysis without affecting the actual patient, enabling repeated testing of different alignment scenarios and optimization of surgical plans before the real intervention.
Data Source
AI summary
Systems and methods for assessing and/or generating a patient-specific alignment for spinal deformity correction surgery are disclosed. A proposed alignment is received. Upon processing at least one pre-operative image of a patient: a plurality of spinopelvic parameters are obtained and at least one computer model of the patient is constructed. An assessment of the proposed alignment is generated using the at least one model. A signal based on the assessment is outputted. A new alignment may be generated based on the results of the assessment.