Dynamic MRI Acquisition Plane for Cardiac Valve Tracking
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Solution Overview
Problem
Phase-contrast flow acquisition in MRI is challenging when analyzing blood flow through vessels and valves subject to cardiac motion, as the valves move in and out of the fixed image plane, leading to inaccurate flow measurements.
Innovation Solution
A dynamic acquisition plane is automatically tracked by detecting and propagating key anatomical landmarks, such as cardiac valves, using deformation fields computed by an inverse-consistent deformable registration algorithm, and fitting a geometric plane to these landmarks to accurately measure flow velocities across the cardiac cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed image plane is used for phase-contrast flow acquisition, then the imaging setup is simple and stable, but the flow measurements become inaccurate when valves move in and out of the plane during cardiac motion
Solution Approach 1:
The patent applies the dynamics principle by transforming the fixed image plane into a dynamic acquisition plane that automatically tracks and adapts to the moving cardiac valves throughout the cardiac cycle. The system detects valve positions in multiple frames and propagates these positions to define a time-varying acquisition plane, ensuring the measurement plane remains aligned with the moving valves rather than remaining static.
Solution Approach 2:
The system implements feedback by using detected valve positions from image analysis to continuously adjust and redefine the acquisition plane. The detected landmark positions feed back into the system to update the plane definition, creating a closed-loop control mechanism that maintains measurement accuracy despite valve motion.
2Measurement precision
If anatomical landmarks are manually tracked to follow valve motion, then flow measurement accuracy improves, but the operation becomes time-consuming and labor-intensive
Solution Approach 1:
The system applies the self-service principle by enabling automatic landmark detection and tracking without requiring manual user intervention. The algorithm autonomously detects anatomical landmarks in image frames, propagates their positions through the cardiac cycle, and defines the acquisition plane automatically, allowing the system to serve itself rather than requiring operator input.
Solution Approach 2:
The patent replaces the manual mechanical tracking process with an automated computational image processing system. Instead of operators manually tracking valve positions frame-by-frame, the system uses deformable registration algorithms and landmark detection software to automatically compute and track valve positions, substituting human labor with automated computational mechanics.
3Reliability
If the image acquisition plane remains static, then the scanning process is simple and fast, but it fails to capture accurate flow data when valves move during the cardiac cycle
Solution Approach 1:
The system transforms the static acquisition plane into a dynamic one that adapts its position and orientation throughout the cardiac cycle. By detecting valve positions in multiple frames and propagating these positions, the system creates a time-varying acquisition plane that maintains alignment with moving valves, ensuring reliable diagnostic data without requiring repeated static acquisitions.
Data Source
AI summary
A method for clinical parameter derivation and adaptive flow acquisition within a sequence of magnetic resonance images includes commencing an acquisition of a sequence of images. One or more landmarks are automatically detected from within one or more images of the sequence of images. The detected one or more landmarks are propagated across subsequent images of the sequence of images. A plane is fitted to the propagation of landmarks. The positions of landmarks or alternatively the position of the fitted plane within the sequence of images is used for derivation of clinical parameters such as tissue velocities and/or performing adaptive flow acquisitions to measure blood flow properties.