Imaging Analysis Apparatus for Cerebrovascular Compartment Identification
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Solution Overview
Problem
Current methods for assessing cerebrovascular status in intensive care unit patients are limited, and there is a need for more effective techniques to analyze blood flow and brain barrier permeability, particularly in conditions like stroke and epilepsy where neurovascular coupling is impaired.
Innovation Solution
A method and apparatus for analyzing imaging data from a living subject's vasculature using a grid of picture-elements, where each element is associated with a vector of features indicative of temporal intensity variation, allowing for clustering and identification of different compartments, including extravascular areas, to evaluate brain or retinal functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (intracranial pressure measurements, thermal diffusion flowmetry, transcranial Doppler velocimetry) are used to assess cerebrovascular status, then cerebral perfusion pressure and blood flow can be measured, but the assessment is limited and cannot provide comprehensive real-time analysis of blood flow dynamics and barrier permeability
Solution Approach 1:
The imaging data is divided into a grid of picture-elements (pixels), with each element representing a specific region of interest in the vasculature. This segmentation allows independent analysis of temporal intensity variations in each region, enabling comprehensive mapping of blood flow dynamics across different vascular compartments (arterial, venous, capillary) and tissue regions simultaneously
Solution Approach 2:
The patent transitions from conventional single-parameter measurements to multi-dimensional analysis by extracting multiple features (temporal intensity variation, rise time, peak time, area under curve) from imaging data. This dimensional expansion enables simultaneous assessment of blood flow velocity, volume, and barrier permeability properties that were previously requiring multiple separate measurement techniques
2Loss of information
If detailed analysis of blood flow and barrier permeability is performed using conventional techniques, then specific parameters can be measured, but real-time comprehensive analysis and detailed mapping capabilities are lacking
Solution Approach 1:
The system performs preliminary processing by pre-defining a grid of picture-elements and pre-identifying regions of interest before actual imaging data acquisition. This allows the analysis algorithm to be pre-configured and optimized, enabling real-time processing of incoming imaging streams without compromising comprehensive data extraction
Solution Approach 2:
The patent creates multiple virtual copies of the imaging data through the picture-element grid, where each element generates its own intensity-time curve and feature set. This copying approach enables parallel processing of multiple regions simultaneously, maintaining real-time analysis capability while extracting detailed information from each vascular compartment independently
3Measurement precision
If comprehensive features are extracted from each picture-element to identify different vascular compartments, then detailed vascular mapping can be achieved, but computational complexity increases
Solution Approach 1:
The patent identifies and extracts specific critical parameters (rise time, peak time, area under curve, temporal intensity variation) from the intensity-time curves of picture-elements. By focusing on these key parameters rather than analyzing entire raw curves, the system achieves accurate vascular compartment classification (arterial vs. venous vs. capillary) while managing computational complexity through parameter reduction and feature selection
Data Source
AI summary
A method of analyzing a stream of imaging data is disclosed. The method comprises: for each picture-element of the data, associating a vector of features indicative of temporal intensity variation relative to baseline intensity, thereby providing a plurality of vectors. The method further comprises clustering the picture-elements according to the vectors, thereby providing a plurality of clusters, and identifying different compartments in the vasculature based on the clusters.