Time-Resolved 3D Angiography via 2D Temporal Projection
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Solution Overview
Problem
Current angiography techniques face limitations in temporal resolution, making it difficult to accurately image and distinguish between arterial and venous structures, especially in complex intracranial vasculature, which hinders the visualization of vascular anatomy and flow patterns necessary for minimally invasive procedures.
Innovation Solution
A system and method that generate time-resolved, three-dimensional medical images by combining temporal information from a series of 2D images with a static 3D image, allowing for high temporal and spatial resolution, enabling the differentiation of arterial from venous vasculature and providing dynamic visualization of vascular structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If rotational acquisitions are obtained over a minimum time of about 5 seconds to achieve 3D reconstruction, then spatial resolution is improved, but temporal resolution deteriorates causing venous structures to be filled and mixed with arterial structures
Solution Approach 1:
The patent segments the 3D reconstruction process by acquiring data from multiple 2D projection views at different time points during the rotation. Each 2D view captures arterial structures at a specific temporal moment, and these segmented temporal data sets are then integrated to form a time-resolved 3D representation, resolving the conflict between spatial and temporal resolution.
Solution Approach 2:
The patent adds the time dimension to the traditional 3D reconstruction by acquiring multiple 2D projection data sets at different time points during the rotational acquisition. This transforms the problem from a static 3D reconstruction into a dynamic 4D (3D + time) reconstruction, allowing temporal resolution to be preserved while maintaining spatial accuracy.
2Loss of information
If thresholding is applied to display pure arterial anatomy by suppressing venous structures, then arterial visualization is improved, but measurement accuracy of vascular dimensions deteriorates
Solution Approach 1:
The patent performs preliminary temporal segmentation by acquiring multiple 2D projection views at different time points before reconstruction. This preliminary temporal mapping allows the system to identify and isolate arterial structures in their native temporal context, eliminating the need for post-reconstruction thresholding that compromises measurement accuracy.
Solution Approach 2:
The patent introduces time as an intermediary parameter that mediates between arterial and venous structures. By using temporal information from multiple 2D views acquired at different time points, the system can selectively reconstruct arterial structures without applying lossy thresholding, thereby preserving measurement accuracy while achieving pure arterial visualization.
3Measurement precision
If repeated contrast injections are performed to reduce vessel overlap and improve viewing angles, then vascular structure differentiation is improved, but contrast medium consumption increases and complications arise
Solution Approach 1:
The patent employs periodic action by acquiring multiple 2D projection views at systematically spaced time points during a single contrast injection. This periodic sampling of temporal data allows comprehensive vascular structure differentiation throughout the contrast bolus passage, eliminating the need for repeated injections while maintaining diagnostic quality.
Solution Approach 2:
The patent maintains continuity of useful action by performing the entire 3D data acquisition from multiple 2D views during a single continuous contrast injection and rotational sweep. This continuous acquisition process captures the complete temporal evolution of contrast distribution, maximizing information extraction from a single contrast dose and avoiding the need for additional injections.
Data Source
AI summary
A method for generating time-resolved 3D medical images of a subject by imparting temporal information from a time-series of 2D medical images into 3D images of the subject. Generally speaking, this is achieved by acquired image data using a medical imaging system, generating a time-series of 2D images of a ROI from at least a portion of the acquired image data, reconstructing a 3D image substantially without temporal resolution from the acquired image data, and selectively combining the time series of 2D images with the 3D image. Selective combination typically involves registering frames of the time-series of 2D images with the 3D image, projecting pixel values from the 2D image frames “into” the 3D image, and weighting the 3D image with the projected pixel values for each frame of the time-series of 2D images. This method is particularly useful for generating 4D-DSA images, that is, time-resolved 3D-DSA images, from a time-series of 2D-DSA images acquired via single plane or biplane x-ray acquisitions with 3D images acquired via a rotational DSA acquisition. 4D-DSA images can also be generated by selectively combining a time-series of 2D-DSA images generated from individual projections from a rotational x-ray acquisition with a 3D image reconstructed from substantially all of the projection views acquired during the rotational x-ray acquisition. These DSA images may have a spatial resolution on the order of 5123 pixels and a temporal resolution of about 30 frames per second, which represents an increase over traditional 3D-DSA frame rates by a factor between 150 and 600.