MyoFold: rapid Myocardial tissue and movement quantification via a highly Folded sequence
Rui Guo, Yingwei Fan, Bowei Liu, Xiaofeng Qian, Jiahuan Dai, Dongyue, Si, Yuanyuan Wang, Ancong Wang, Xiaoying Tang, Haiyan Ding

TL;DR
MyoFold is a rapid MRI sequence that simultaneously quantifies myocardial tissue properties and movement within a single breath-hold, using a neural network for T1/T2 mapping, achieving accuracy comparable to existing methods.
Contribution
The paper introduces MyoFold, a novel MRI sequence that combines T1/T2 mapping and cine imaging in a single rapid acquisition with neural network-based analysis.
Findings
MyoFold achieves accurate T1 and T2 measurements comparable to existing methods.
It reduces scan time by three-fold compared to separate sequences.
MyoFold maintains measurement accuracy for myocardial thickness.
Abstract
Purpose: To develop and evaluate a cardiovascular magnetic resonance sequence (MyoFold) for rapid myocardial tissue and movement characterization. Method: MyoFold sequentially performs joint T1/T2 mapping and cine for one left-ventricle slice within a breathing-holding of 12 heartbeats. MyoFold uses balanced Steady-State-Free-Precession (bSSFP) with 2-fold acceleration for data readout and adopts an electrocardiogram (ECG) to synchronize the cardiac cycle. MyoFold first acquires six single-shot inversion-recovery images at the diastole of the first six heartbeats. For joint T1/T2 mapping, T2 preparation (T2-prep) adds different T2 weightings to the last three images. On the remaining six heartbeats, segmented bSSFP is continuously performed for each cardiac phase for cine. We build a neural network and trained it using the numerical simulation of MyoFold for T1 and T2 calculations.…
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Taxonomy
TopicsAdvanced MRI Techniques and Applications · Cardiac Imaging and Diagnostics · Cardiovascular Function and Risk Factors
