3D Vertebra Bone Density Modeling for Spinal Implant Planning
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Solution Overview
Problem
Current methods for spinal surgery analysis, such as DEXA scans, lack precision in measuring volumetric bone density, leading to imprecise and anecdotal surgical predictions.
Innovation Solution
Utilizing CT scans to generate a 3D volumetric model of the spine with AI segmentation, simulating surgical forces, and predicting outcomes to rank surgery options based on bone density and biomechanical responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DEXA scans are used for bone density measurement, then the measurement process is simple and quick, but the measurement precision of volumetric bone density is insufficient
Solution Approach 1:
The patent segments the vertebral body into multiple volumetric regions (e.g., superior endplate region, inferior endplate region, central region) and calculates bone density independently for each region. This segmentation enables precise volumetric bone density measurement by analyzing Hounsfield units within specific 3D regions, directly resolving the limitation of DEXA scans that cannot provide region-specific volumetric density data.
Solution Approach 2:
The patent transitions from 2D planar bone density assessment (DEXA) to 3D volumetric bone density analysis using CT imaging. By reconstructing the vertebral body as a three-dimensional model with volumetric regions, the system achieves accurate volumetric bone density measurement, directly addressing the insufficiency of traditional 2D measurement methods.
2Manufacturing precision
If 3D volumetric modeling with AI segmentation is implemented, then the accuracy of surgery planning is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs AI-based segmentation and 3D volumetric modeling of the vertebral body before surgical planning. By pre-processing the CT images to create accurate 3D models with defined volumetric regions and bone density values, the system establishes a detailed anatomical framework in advance, enabling more accurate surgical planning without increasing real-time computational complexity during the actual surgical decision-making process.
Solution Approach 2:
The patent creates a digital 3D copy of the patient's vertebral body from CT scan data, complete with volumetric region segmentation and bone density assignment. This digital twin serves as a virtual model for surgical simulation and planning, allowing complex computational analysis to be performed on the copy rather than requiring complex hardware modifications during actual surgery.
3Reliability
If multiple spine surgery options are simulated and ranked, then the reliability of surgical outcome prediction is improved, but the time required for analysis increases
Solution Approach 1:
The patent performs biomechanical simulations and outcome predictions for multiple surgery options during the pre-operative planning phase. By conducting these simulations in advance using the 3D volumetric model, the system generates reliability assessments for different surgical approaches before the actual surgery, allowing surgeons to make informed decisions without time pressure during the surgical procedure itself.
Solution Approach 2:
The patent implements a tiered approach where essential biomechanical parameters are calculated first to provide rapid initial assessments, followed by more comprehensive simulations only for the most promising surgical options. This partial action strategy maintains high prediction reliability while reducing overall analysis time by avoiding exhaustive simulation of all possible surgical variations.
Data Source
AI summary
Systems, methods, and computer-readable storage media for vertebra bone density analysis, and more specifically to identifying which portions of vertebra have sufficient density to support different types of spinal surgery. A system can segment the pre-operation medical images and generate a 3D pre-operation model having a plurality of volumetric regions based on those pre-operation medical images, wherein each volumetric region has a bone density. The system can then identify different spine surgery options and generate, for each of the plurality of spine surgery options using the 3D pre-operation model, a 3D predicted model. The system can then simulate these predicted models being exposed to various stresses and forces, and predict which of the predicted models results in the best surgery outcome.