Volumetric Vector Map for Lung Nodule Characterization
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Solution Overview
Problem
Current methods for radiographically evaluating lung cancer nodules are inadequate due to their heterogenous nature, leading to inaccurate characterization and requiring multiple biopsy passes to determine disease presence.
Innovation Solution
A system and method that utilize 3D image data to generate a volumetric vector map by calculating gradients based on maximum and minimum attenuation values, assisting clinicians in identifying the most aggressive components of tumors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple biopsy passes are performed to assess heterogeneous lung cancer nodules, then the accuracy of disease characterization is improved, but the complexity of the medical procedure and time consumption increase
Solution Approach 1:
The system performs preliminary 3D imaging and volumetric analysis before the biopsy procedure to identify the most aggressive components of the nodule. This preliminary characterization guides the biopsy needle placement, allowing for a single targeted pass rather than multiple exploratory passes, thereby maintaining diagnostic accuracy while reducing procedural complexity
Solution Approach 2:
The system applies local quality analysis by generating volumetric vector maps that highlight specific regions within the nodule with different aggression levels. Instead of treating the entire nodule uniformly, the system identifies and targets specific high-aggression zones for biopsy, improving characterization accuracy while minimizing the number of biopsy passes required
2Ease of operation
If maximum cross-sectional length is measured in two planes, then the assessment is simplified, but the characterization accuracy of heterogeneous nodules deteriorates
Solution Approach 1:
The system transitions from 2D planar measurement to 3D volumetric analysis by generating voxel maps and volumetric vector maps. This dimensional upgrade allows the system to maintain ease of operation through automated processing while dramatically improving characterization accuracy by capturing the heterogeneous nature of nodules in three dimensions, including internal structure and spatial distribution of aggressive components
3Measurement precision
If 3D volumetric analysis with gradient calculation is performed, then the characterization accuracy is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system segments the complex 3D analysis into distinct computational steps: first generating a voxel map from 3D image data, then calculating attenuation values, followed by gradient computation, and finally generating volumetric vector maps. This segmentation of the processing pipeline manages computational complexity by breaking down the intensive 3D analysis into manageable stages while maintaining high characterization accuracy
Data Source
AI summary
Systems and methods of guiding a clinician in a medical procedure for a nodule involve receiving three-dimensional (3D) image data, generating a volumetric vector map based on the 3D image data, and displaying the volumetric vector map in a way, e.g., via a heat map, that assists a clinician in performing a medical procedure. The systems and methods involve identifying volumetric parameters of the nodule in the 3D image data, generating a voxel map based on the volumetric parameters, identifying a maximum attenuation value in the 3D space of the voxel map, applying a differential equation, e.g., a gradient, to the 3D space of the voxel map from a voxel with the maximum attenuation value to other voxels within the voxel map, and generating a volumetric vector map based on the result of applying the differential equation.