Lung Analysis System for Bronchoscopy Guided Lung Volume Reduction
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Solution Overview
Problem
Current methods for analyzing high-resolution computed tomography (HRCT) and quantitative computed tomography (QCT) data lack efficient tools for quickly and accurately identifying lung lobe candidacy for bronchoscopy guided lung volume reduction (BLVR) procedures, which is crucial for successful patient outcomes.
Innovation Solution
The system and method involve receiving three-dimensional image data of the lung, categorizing voxels into lung lobe, airway, and fissure voxels, generating fissure integrity scores, and creating perspective views of these voxels to provide a comprehensive report that aids healthcare professionals in determining lung lobe candidacy for BLVR procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis of HRCT and QCT data is performed, then detailed examination is possible, but the process is time-consuming and lacks efficiency
Solution Approach 1:
The patent replaces manual mechanical analysis with an automated computer-based system that processes HRCT and QCT data. The system automatically generates three-dimensional visualizations, calculates emphysema scores, assesses fissure integrity, and identifies target lobes, eliminating the time-consuming manual review process while maintaining diagnostic accuracy.
Solution Approach 2:
The patent creates three-dimensional visual copies and models of the lung anatomy from two-dimensional CT scan data. These 3D visualizations include transparent views of lung lobes, airways, and fissures, allowing physicians to quickly assess structural integrity and emphysema distribution without manually analyzing multiple 2D slices.
2Measurement precision
If comprehensive analysis of emphysema severity, fissure integrity, and heterogeneity is performed, then accurate target lobe identification is achieved, but the complexity of analysis increases
Solution Approach 1:
The patent segments the lung anatomy into distinct components: lung lobes, airways, and fissures. Each component is analyzed separately with specific metrics (emphysema scores for lobes, integrity scores for fissures), allowing comprehensive assessment without overwhelming complexity. The segmentation enables targeted analysis of only the relevant structures for BLVR candidacy.
Solution Approach 2:
The patent introduces an intermediary automated processing system that bridges the raw CT data and the physician's decision-making. This intermediary automatically performs complex calculations including emphysema severity scoring, fissure integrity assessment, and heterogeneity analysis, presenting the results in an easily interpretable format that reduces the cognitive burden on physicians.
3Reliability
If detailed visual representation of fissure integrity is provided, then confidence in target lobe selection increases, but the amount of data to process increases
Solution Approach 1:
The patent applies local quality assessment by providing detailed visual representation of fissure integrity specifically at critical locations rather than uniformly across the entire lung. The system highlights areas of fissural thickening or discontinuity in the context of the specific target lobe being evaluated, allowing physicians to focus on locally relevant information that directly impacts BLVR candidacy determination.
Solution Approach 2:
The patent transforms two-dimensional CT slice data into three-dimensional visual representations with transparency effects. This dimensional transformation allows simultaneous visualization of multiple structures (lung parenchyma, airways, fissures) in their spatial context, enabling comprehensive assessment in a single view rather than requiring review of numerous 2D slices.
Data Source
AI summary
Systems, methods, and executable programs for providing lung candidacy information to health care professionals. A method includes receiving three-dimensional image data categorized as lung lobe voxels, airway voxels, or lung fissure voxels. A fissure integrity score is generated for the lung fissure voxels. First perspective transparent views of the categorized lung lobe voxels, the categorized airway voxels, and the categorized lung fissure voxels are generated based on a first point of view. The first perspective view of the lung fissure voxels includes a visual representation of fissure integrity based on the generated fissure integrity scores for the corresponding voxels. A report is generated that includes the generated views. The report is outputted.