Spinal Cord Navigation Using Augmented Anatomy Mapping
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Solution Overview
Problem
Current imaging technologies are inadequate for accurately visualizing segment-specific spinal cord structures and their orientations, limiting the precise delivery of spinal cord stimulation therapies due to the thickness of the dura and resource-intensive methods like DTI scans.
Innovation Solution
A hybrid image-guided navigation system that combines anatomical measurement data with multimodal imaging data to generate augmented spinal cord anatomy models, allowing for precise targeting and visualization of spinal cord structures relative to vertebrae.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional imaging techniques are used to visualize spinal cord structures, then the imaging process is simple and quick, but the imaging accuracy is insufficient due to the thickness of the dura
Solution Approach 1:
The patent combines multiple imaging modalities (CT, MRI, fluoroscopy) with anatomical measurement data and navigation systems to create a hybrid imaging approach. This integration allows the system to overcome the limitations of individual imaging techniques by merging their strengths while compensating for their weaknesses, particularly the inability of conventional imaging to visualize structures through the thick dura.
Solution Approach 2:
The patent introduces anatomical measurement data and augmented reality overlays as intermediary elements between the imaging system and the surgeon. These intermediaries provide additional spatial context and measurement information that bridge the gap between what conventional imaging can show and what the surgeon needs to know for precise targeting.
2Measurement precision
If DTI scans are used to image spinal cord anatomy, then detailed spinal cord structures can be visualized, but the scan time is longer and resource consumption is higher
Solution Approach 1:
The patent applies partial action by using anatomical measurement data and selective imaging approaches rather than performing complete DTI scans on all patients. The system uses pre-acquired anatomical data combined with intraoperative imaging to provide sufficient detail for surgical planning without the full resource cost of comprehensive DTI imaging.
Solution Approach 2:
The patent performs preliminary anatomical measurements and imaging assessments before surgery to establish baseline data. This preliminary action allows the surgical team to plan procedures in advance and reduces the need for time-consuming intraoperative imaging, as the anatomical framework is already established from pre-surgical assessments.
3Reliability
If conventional imaging methods are used for pre-surgical assessment, then the assessment process is quick and resource-efficient, but the ability to accurately target spinal cord structures is limited
Solution Approach 1:
The patent segments the imaging and navigation system into modular components: anatomical measurement data acquisition, medical image processing, navigation data generation, and augmented reality display. This segmentation allows each component to be optimized independently while maintaining overall system reliability, making the complex navigation system more manageable and clinically implementable.
Solution Approach 2:
The patent applies local quality by providing enhanced imaging and measurement data specifically at the surgical target site rather than uniformly enhancing the entire imaging system. The augmented reality overlay and navigation data are concentrated where they are most needed—for precise spinal cord structure targeting—rather than improving overall system complexity uniformly throughout.
Data Source
AI summary
Image-guided navigation for spinal cord treatments and therapies are described. The image-guided navigation is augmented with anatomical measurement data related to spinal cord and vertebral anatomy. From these data and medical image data, an augmented model of spinal cord anatomy is generated and/or navigation data can be generated for localizing spinal cord structures, such as by mapping the anatomical measurement data to the medical image data. The augmented model data and/or navigation data can be used for surgical navigation, stimulation parameter setting, electrode configuration selection, pre-surgical planning, surgical visualization, and so on.