4D DSA Framework for Vascular Blood Flow Analysis
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Solution Overview
Problem
Current clinical practices in angiography are limited by the inability to effectively interpret time-resolved information in three dimensions from two-dimensional projection images, leading to potential missed image information and incorrect diagnoses due to vessel overlap and obscuration.
Innovation Solution
A framework for quantitative evaluation of four-dimensional Digital Subtraction Angiography (DSA) datasets, which delineates a volume of interest, extracts a centerline, determines blood dynamics measures at user-selected points, and generates visualizations based on these measures, enabling more accurate assessment of blood flow and vascular anatomy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If 2D projection images are used for angiography, then the imaging process is simple and quick, but vessel overlap and obscuration occur leading to loss of information and reduced diagnostic accuracy
Solution Approach 1:
The patent transitions from 2D projection images to 3D volumetric reconstruction of vascular structures. By acquiring projection images at multiple angles during rotational scanning and reconstructing them into a 3D volume, the system eliminates vessel overlap and obscuration problems inherent in 2D imaging, providing complete spatial information about vascular anatomy without increasing fundamental system complexity.
Solution Approach 2:
The patent introduces time-resolved 4D DSA that captures contrast dynamics throughout the cardiac cycle. By performing rotational scanning at multiple phases of the cardiac cycle and reconstructing time-resolved 3D volumes, the system dynamically tracks blood flow and vascular changes over time, providing quantitative blood dynamics measures that are impossible to obtain from static 2D images.
2Measurement precision
If 3D reconstruction techniques are applied to eliminate vessel overlap, then diagnostic accuracy improves, but the complexity of data processing and reconstruction increases
Solution Approach 1:
The patent applies 3D volumetric reconstruction from multiple 2D projection images acquired during rotational scanning. This dimensionality transformation provides complete spatial information about vascular structures, eliminating overlap and obscuration while enabling precise measurement of vascular anatomy, lumen diameter, and vessel morphology that cannot be obtained from 2D projections alone.
Solution Approach 2:
The patent creates a universal 3D volumetric dataset that serves multiple diagnostic functions simultaneously. The same 3D volume can be used for anatomical assessment, functional blood flow analysis, quantitative measurements, and guidance of interventional procedures, reducing the need for multiple separate imaging acquisitions and processing pipelines.
3Loss of information
If time-resolved 3D datasets are generated, then blood flow dynamics can be analyzed, but the quantity of data and processing requirements increase significantly
Solution Approach 1:
The patent implements 4D DSA that captures time-resolved 3D volumetric data throughout the cardiac cycle. By performing rotational scanning at multiple cardiac phases and reconstructing time-resolved volumes, the system captures dynamic blood flow information including contrast bolus propagation, vascular filling patterns, and flow velocity changes. This dynamic approach preserves complete blood flow information while using efficient temporal sampling strategies.
Solution Approach 2:
The patent performs preliminary 3D reconstruction of the vascular anatomy before conducting time-resolved blood flow analysis. By first establishing the 3D vascular geometry and then tracking contrast dynamics within this pre-defined vascular framework, the system reduces the complexity of processing time-resolved data compared to analyzing raw 4D projection images directly.
Data Source
AI summary
A framework for quantitative evaluation of time-varying data. In accordance with one aspect, the framework delineates a volume of interest in a four-dimensional (4D) Digital Subtraction Angiography (DSA) dataset (204). The framework then extracts a centerline of the volume of interest (206). In response to receiving one or more user-selected points along the centerline (208), the framework determines at least one blood dynamics measure associated with the one or more user-selected points (210), and generates a visualization based on the blood dynamics measure (212).