Lung Candidacy Report for Bronchoscopy 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 systems to reliably assess emphysema severity, fissure integrity, and heterogeneity, making it difficult for physicians to identify suitable lung lobes for bronchoscopy-guided lung volume reduction (BLVR) procedures.
Innovation Solution
A system and method that receives three-dimensional lung scan data, delineates lung lobes and fissures, generates emphysema scores, fissure integrity scores, and heterogeneity scores, and outputs a visual report indicating lung lobe candidacy for BLVR procedures using unique colors or patterns to represent meeting predefined inclusion criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated analysis systems are implemented to assess emphysema severity, fissure integrity, and heterogeneity, then productivity and reliability of lung candidacy assessment are improved, but device complexity increases
Solution Approach 1:
The system segments the complex analysis task into distinct components: emphysema severity assessment, fissure integrity evaluation, and heterogeneity analysis. Each component is processed independently and then integrated into a comprehensive lung candidacy report, making the overall complex system manageable and reliable
Solution Approach 2:
The patent introduces an automated image processing system as an intermediary between the raw HRCT/QCT images and the physician's decision-making process. This intermediary automatically performs measurements, generates scores, and creates visual reports, reducing the complexity burden on the physician while maintaining high productivity
2Measurement precision
If multiple scoring metrics (emphysema severity, fissure integrity, heterogeneity) are generated for each lobe, then measurement precision and reliability are improved, but the quantity of information to be processed increases
Solution Approach 1:
The system applies different scoring metrics and visualization methods to different lung lobes based on their specific characteristics. Each lobe receives individualized assessment with tailored visual representations, allowing physicians to quickly identify relevant information for each specific lobe without being overwhelmed by uniform detailed data across all lobes
Solution Approach 2:
The patent uses color-coded visual representations to encode multiple scoring metrics. Different colors indicate different levels of emphysema severity, fissure integrity, and heterogeneity, allowing physicians to rapidly interpret multiple quantitative measures through intuitive visual cues rather than processing raw numerical data
3Ease of operation
If visual reports with color-coded candidacy icons are provided for each lobe, then ease of operation and decision-making speed are improved, but loss of detailed information may occur through simplification
Solution Approach 1:
The system transforms detailed quantitative scoring data into a visual dimension through color-coded icons and graphical representations. This dimensional transformation allows physicians to perceive complex multi-parameter information spatially and intuitively, improving ease of operation while preserving the underlying detailed data through interactive access options
Data Source
AI summary
A system and method for analyzing scan data of a lung and presenting a lung candidacy report. The lung candidacy report includes determinations represented visually of whether lung lobes are suitable candidates for a bronchoscopy guided lung volume reduction procedure. The lung candidacy report includes emphysema values and fissure integrity determined from the scan data.