Contrast-Free Lung Imaging for Ventilation/Perfusion Ratio Calculation
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Solution Overview
Problem
Current imaging techniques for detecting pulmonary embolism and other vascular irregularities rely heavily on contrast agents, which can cause adverse reactions and are not suitable for rapid diagnosis, especially in cases where contrast agents are contraindicated.
Innovation Solution
A method for calculating a ventilation/perfusion ratio from three-dimensional in vivo lung images without contrast agents using multi-scale filters to extract vasculature trees, segment and analyze lung motion, and quantify vessel geometry to detect irregularities such as pulmonary embolism.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contrast agents are used to enhance vascular visibility, then measurement precision of vascular irregularities is improved, but object-affected harmful factors increase due to adverse reactions
Solution Approach 1:
The invention extracts and removes the contrast agent component from the imaging system, achieving vascular imaging through pure anatomical and functional analysis of existing tissue properties. The method segments pulmonary arteries and veins by analyzing inherent density differences and flow characteristics without any contrast enhancement, thereby eliminating harmful contrast agent exposure while maintaining diagnostic capability.
Solution Approach 2:
The invention introduces computational image processing algorithms as an intermediary between the X-ray imaging system and the final diagnostic output. These algorithms automatically segment vasculature, calculate perfusion metrics, and detect abnormalities through software-based analysis rather than chemical contrast agents, mediating the detection process through intelligent image analysis.
2Productivity
If contrast agents are administered for rapid diagnosis, then productivity of diagnostic process is improved, but object-affected harmful factors increase due to contraindications
Solution Approach 1:
The imaging system performs self-service by automatically acquiring, processing, and analyzing vascular images without requiring external contrast agents. The system uses built-in computational algorithms to segment vessels, calculate perfusion ratios, and detect emboli directly from standard CT images, making the diagnostic process self-sufficient and eliminating dependence on contrast agent administration.
Solution Approach 2:
The invention replaces the chemical mechanism of contrast agent enhancement with a computational mechanism for vascular visualization. Instead of using iodine-based chemicals to alter tissue density, the system uses digital image processing techniques including thresholding, region growing, and perfusion calculation algorithms to achieve the same diagnostic goal without chemical intervention.
3Ease of operation
If multi-scale filters and automated analysis are applied to extract vasculature, then device complexity increases, but ease of operation improves by enabling automated detection
Solution Approach 1:
The invention applies segmentation by dividing the complex image processing task into distinct functional modules: initial image acquisition, multi-scale filter application for enhancement, automated thresholding for binary segmentation, region growing for vessel extraction, and perfusion ratio calculation. Each module handles a specific aspect of the analysis, making the overall complex process manageable and automated.
Solution Approach 2:
The system automatically adjusts processing parameters such as filter scales, threshold values, and region growing criteria based on the specific characteristics of each image dataset. The multi-scale filters operate across multiple parameter levels to capture vessels of different diameters, and the algorithm adapts thresholding parameters dynamically to optimize segmentation for each patient's anatomy.
Data Source
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AI summary
The invention provides a method of calculating a ventilation / perfusion ratio from at least one in vivo lung image acquired in the absence of contrast agent and a time series of lung images, the method including steps of: applying a multi-scale filter to the in vivo lung image to provide a probability field and a scale field; performing vessel segmentation on the probability field to extract a vasculature tree from the probability field; mapping the scale field to the segmented vasculature tree to quantify a geometry of the vasculature tree; measuring three-dimensional motion of a portion of the lung from the time series of lung images; and comparing the motion of the potion of the lung to the scale of the vasculature in the region of the portion of the lung to obtain a ventilation / perfusion measure.