Vascular Tree Segmentation for Intestinal Perfusion Analysis
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Solution Overview
Problem
Current methods for evaluating angiographic three-dimensional computed tomography datasets of hollow organs, such as the intestine, are inadequate for precise localization of pathologies and perfusion analysis, leading to inefficient identification and treatment of intestinal issues.
Innovation Solution
A computer-implemented method that segments the vascular tree from the computed tomography dataset, constructs a two-dimensional tree structure, assigns perfusion information to each blood vessel segment, and analyzes this information to determine hemodynamic parameters for precise localization and visualization of intestinal pathologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional axial, coronary and sagittal computed tomography methods are used for visualizing vascular anatomy and hollow organ segments, then the imaging coverage is comprehensive, but the localization precision of pathologies is only rough and insufficient
Solution Approach 1:
The method segments the vascular tree into individual blood vessel segments and assigns each segment a unique identifier. This segmentation enables precise localization of pathologies to specific vascular segments, transforming the rough localization from traditional methods into precise segment-based identification.
Solution Approach 2:
The invention introduces a hierarchical tree structure dimension to the traditional three-dimensional CT data. By organizing blood vessels into a tree structure with branches, nodes, and segments, the system adds a topological dimension that enables precise localization beyond spatial coordinates alone.
2Reliability
If perfusion parameters are assessed visually by a person making a diagnosis, then the evaluation is comprehensive, but a second manual and visual exploration needs to be performed intraoperatively which is time-consuming and less reliable
Solution Approach 1:
The system performs automated segmentation, tree structure construction, and perfusion parameter assessment during the preoperative CT evaluation phase. This preliminary action provides reliable blood vessel identification and perfusion analysis before surgery, eliminating the need for time-consuming intraoperative manual exploration.
Solution Approach 2:
The invention replaces manual visual exploration with an automated computer-implemented method. The system automatically segments vessels, constructs tree structures, calculates perfusion parameters, and generates reports, substituting the mechanical manual exploration process with an automated digital system that is both faster and more reliable.
3Measurement precision
If the entire hollow organ is manually explored intraoperatively, then all regions can be examined, but smaller blood vessel segments cannot be identified sufficiently clearly and thromboses can only be detected manually in a less reliable way
Solution Approach 1:
The system segments the vascular tree into discrete blood vessel segments with unique identifiers, enabling precise identification of even small vessels. This segmentation allows the system to track and evaluate individual vessel segments throughout the hierarchy, making small vessels as identifiable as large ones.
Solution Approach 2:
The invention introduces a computer-based evaluation system as an intermediary between the CT data and the surgeon. This intermediary automatically processes the data, identifies blood vessel segments, assesses perfusion parameters, and presents the information in an easily interpretable format, making complex vascular information accessible during surgery.
4Productivity
If automated evaluation is implemented, then productivity and accuracy are improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system segments the complex CT data into manageable components: blood vessel segmentation, tree structure construction, and perfusion parameter calculation. This segmentation of the processing task enables automated evaluation while organizing the complexity into modular, manageable steps.
Solution Approach 2:
The evaluation system is designed to handle multiple functions within a unified framework: segmentation, tree construction, perfusion analysis, and report generation. This multi-functionality consolidates what would otherwise require multiple separate systems into a single integrated solution, managing complexity through consolidation.
Data Source
AI summary
At least one vascular tree supplying at least a part of the hollow organ in the computed tomography dataset is segmented, and a tree structure up to an order possible based on the blood vessel segmentation result is determined from a blood vessel segmentation result. Perfusion information for each edge in the tree structure is assigned as at least one of the computed tomography data assigned to the blood vessel segment or at least one value derived therefrom. Adjacent hollow organ segments of the hollow organ are defined based on supply by adjacent blood vessels in the tree structure, and the tree structure and the perfusion information are analyzed to determine hemodynamic information to assign to hollow organ segments. At least a part of the hemodynamic information in at least one of the computed tomography dataset or a visualization dataset derived therefrom is then visualized.