Lung Imaging Analysis for Collateral Ventilation Assessment
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Solution Overview
Problem
Current methods for treating pulmonary diseases like COPD are hindered by collateral ventilation, which complicates the effectiveness of lung volume reduction procedures due to air passing between lung compartments, and there is a need for accurate analysis of lung imaging data to identify suitable treatment sites and devices for lung volume reduction.
Innovation Solution
A method and system for analyzing CT data by segmenting the lung, calculating emphysema and fissure defect scores, determining collateral ventilation, and identifying potential treatment sites for implantable devices or therapeutic agents to reduce lung hyperinflation, while also addressing collateral ventilation between lung compartments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If implantable devices are placed in airways feeding diseased lung regions to regulate fluid flow, then lung volume reduction is achieved, but collateral ventilation through fissure defects prevents effective isolation of the diseased region
Solution Approach 1:
The system performs preliminary analysis of CT imaging data to identify fissure defects and assess collateral ventilation risk before device placement. This allows clinicians to evaluate whether a target lung region can be effectively isolated from collateral airflow, ensuring that implantable devices are placed only in regions where complete isolation is achievable
Solution Approach 2:
The patent replaces physical measurement of collateral ventilation with computational analysis of CT imaging data. By using image processing algorithms to detect fissure defects and calculate collateral ventilation scores, the system substitutes mechanical assessment methods with non-invasive digital analysis
2Measurement precision
If CT imaging data is analyzed in detail to identify fissure defects and assess collateral ventilation, then treatment site selection accuracy is improved, but analysis complexity and time increase
Solution Approach 1:
The analysis system processes CT imaging data by segmenting the lung into distinct regions and identifying specific fissure defects separately. By dividing the complex analysis into modular components (fissure detection, defect characterization, collateral ventilation scoring), the system achieves high measurement precision while maintaining manageable complexity through structured data organization
Solution Approach 2:
The system creates digital representations (models) of lung anatomy and fissure defects from CT imaging data. These computational models serve as simplified copies that capture the essential geometric and topological features needed for collateral ventilation assessment, enabling accurate analysis without requiring direct manipulation of the full-complexity raw imaging data
Data Source
AI summary
Devices, methods, and systems are provided for analyzing lung imaging data. Lung imaging data maybe analyzed to segment the lung, identify fissure locations, calculate fissure defect scores, identify adjacent lung compartments, calculate emphysema scores, calculate volumes, and calculate proximities. Collateral ventilation within a lung compartment may be determined based on the analyzed lung imaging data.