Cardiac MRI Self-Gating for Arrhythmia Reconstruction
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Solution Overview
Problem
Current cardiovascular magnetic resonance imaging (MRI) techniques face challenges in imaging patients with severe arrhythmias, as existing methods either produce corrupt data or require prolonged scan times due to ectopic beats, leading to compromised image quality and inefficiencies.
Innovation Solution
A retrospective reconstruction method using cardiac self-gating to determine myocardial systolic and diastolic motion from low-spatial, high-temporal resolution images, allowing for the accurate combination of data from normal and interrupted beats, improving sampling density and image quality, employing techniques like the golden angle radial trajectory for undersampled k-space data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ECG-based retrospective reconstruction is used, then cardiac motion can be synthesized from multiple heartbeats, but image quality is compromised in patients with severe arrhythmias due to ectopic beats causing corrupt data or requiring prolonged scan times
Solution Approach 1:
The patent changes the gating parameter from ECG-triggered to self-gated using image-derived cardiac motion signals. This allows the system to adapt to arrhythmic patterns by using actual observed cardiac motion rather than assuming regular intervals, thereby maintaining image quality without requiring prolonged scan times for arrhythmic patients
Solution Approach 2:
The system performs self-gating by deriving cardiac phase information directly from the imaging data itself rather than relying on external ECG triggers. The cardiac motion signal is extracted from the image data through techniques like feature tracking or intensity variation analysis, enabling the system to autonomously handle arrhythmic patterns without external guidance
2Reliability
If arrhythmia rejection is enabled to handle ectopic beats, then corrupt imaging data is avoided, but scan times are prolonged and breath holds become unachievable
Solution Approach 1:
The patent changes the temporal sampling approach from fixed ECG-gated intervals to variable self-gated intervals based on actual cardiac motion. This allows the system to capture adequate data within the available breath-hold duration by adapting to the patient's actual heart rate and rhythm patterns rather than relying on predetermined timing
Solution Approach 2:
The system acquires more k-space lines than the minimum required during the breath-hold window, using the additional sampling opportunities created by the flexible self-gating approach to improve image quality without extending the breath-hold duration
3Measurement precision
If low-spatial and high-temporal resolution images are used for self-gating, then cardiac phase can be determined accurately, but sampling density in k-space is reduced
Solution Approach 1:
The patent segments the k-space sampling into two distinct patterns: a low-spatial-resolution high-temporal-resolution pattern used for extracting cardiac phase information (self-gating), and a complete high-spatial-resolution pattern used for final image reconstruction. This segmentation allows the system to use different sampling strategies for different purposes without compromising either cardiac phase accuracy or final image quality
Solution Approach 2:
The patent uses an intermediary low-resolution image reconstruction as a mediator to extract cardiac phase information. This intermediary reconstruction serves as a bridge, providing sufficient temporal resolution for gating signal extraction while preserving the option to reconstruct high-resolution images from the complete k-space data
Data Source
AI summary
A retrospective reconstruction method uses cardiac self-gating for patients with severe arrhythmias. Self-gated myocardial systolic and diastolic motion is determined from low-spatial and high-temporal resolution images and then the MRI-dataset is retrospectively reconstructed to obtain high quality images. The method uses undersampled image reconstruction to obtain the low-spatial and high-temporal resolution images, including those of different beat morphologies. Processing of these images is utilized to generate a cardiac phase signal. This signal allows for arrhythmia detection and cardiac phase sorting. The cardiac phase signal allows for detection of end-systolic and diastolic events which allows for improved sampling efficiency. In the case of frequent and severe arrhythmia, the method utilizes data from the normal and interrupted beats to improve sampling and image quality.