Motion-resolved real-time 4D flow MRI with low-rank and subspace modeling
Aiqi Sun
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Search for more papers by this authorBo Zhao
Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
Search for more papers by this authorYuliang Long
Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
Search for more papers by this authorBei Wang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Search for more papers by this authorRui Li
Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
Search for more papers by this authorCorresponding Author
He Wang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
Correspondence
He Wang, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Email: [email protected]
Search for more papers by this authorAiqi Sun
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Search for more papers by this authorBo Zhao
Department of Biomedical Engineering, University of Texas at Austin, Austin, Texas, USA
Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, Texas, USA
Search for more papers by this authorYuliang Long
Department of Cardiology, Zhongshan Hospital, Fudan University, Shanghai, China
Search for more papers by this authorBei Wang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Search for more papers by this authorRui Li
Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
Search for more papers by this authorCorresponding Author
He Wang
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, China
Correspondence
He Wang, Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
Email: [email protected]
Search for more papers by this authorClick here for author-reader discussions
Funding information: China Postdoctoral Science Foundation, Grant/Award Number: 2022M710795; Start-up funds from the University of Texas at Austin, National Natural Science Foundation of China, Grant/Award Numbers: 82271956; 81971583; National Key R&D Program of China, Grant/Award Number: 2018YFC1312900; Natural Science Foundation of Shanghai, Grant/Award Number: 20ZR1406400
Abstract
Purpose
To develop a new motion-resolved real-time four-dimensional (4D) flow MRI method, which enables the quantification and visualization of blood flow velocities with three-directional flow encodings and volumetric coverage without electrocardiogram (ECG) synchronization and respiration control.
Methods
An integrated imaging method is presented for real-time 4D flow MRI, which encompasses data acquisition, image reconstruction, and postprocessing. The proposed method features a specialized continuous -space acquisition scheme, which collects two sets of data (i.e., training data and imaging data) in an interleaved manner. By exploiting strong spatiotemporal correlation of 4D flow data, it reconstructs time-series images from highly-undersampled -space measurements with a low-rank and subspace model. Through data-binning-based postprocessing, it constructs a five-dimensional dataset (i.e., x-y-z-cardiac-respiratory), from which respiration-dependent flow information is further analyzed. The proposed method was evaluated in aortic flow imaging experiments with ten healthy subjects and two patients with atrial fibrillation.
Results
The proposed method achieves 2.4 mm isotropic spatial resolution and 34.4 ms temporal resolution for measuring the blood flow of the aorta. For the healthy subjects, it provides flow measurements in good agreement with those from the conventional 4D flow MRI technique. For the patients with atrial fibrillation, it is able to resolve beat-by-beat pathological flow variations, which cannot be obtained from the conventional technique. The postprocessing further provides respiration-dependent flow information.
Conclusion
The proposed method enables high-resolution motion-resolved real-time 4D flow imaging without ECG gating and respiration control. It is able to resolve beat-by-beat blood flow variations as well as respiration-dependent flow information.
CONFLICT OF INTEREST
Yichen Zheng is an employee of Beijing PINS Medical Co. Ltd. Peng Wu is an employee of Philips Healthcare.
Supporting Information
| Filename | Description |
|---|---|
| mrm29557-sup-0001-FigureS1.pdfapplication/unknown, 160.1 KB | Figure S1. Bland–Altman plots of the differences in SNR and VNR between the conventional cine 4D flow imaging and the proposed real-time 4D flow imaging. Here the central dotted horizontal line refers to the mean of the differences for the two methods, while the outer dotted horizontal lines refer to the lower/upper limits of agreement. |
| mrm29557-sup-0001-VideoS1.gifapplication/unknown, 18.1 MB | Video S1. Real-time 4D flow MRI of a healthy subject. This video clip contains the reconstructed magnitude images and velocity maps over ten cardiac cycles from the proposed real-time 4D flow imaging method for a healthy subject. The synchronized respiratory and cardiac motion signals are also shown. |
| mrm29557-sup-0001-VideoS2.gifapplication/unknown, 19.8 MB | Video S2. Real-time 4D flow MRI of a healthy subject. This video clip contains the streamline visualization of the blood flow over ten cardiac cycles from the proposed real-time 4D flow imaging method for a healthy subject. The synchronized respiratory and cardiac motion signals and the flow curve associated with ascending aorta are also shown. |
| mrm29557-sup-0001-VideoS3.gifapplication/unknown, 13.5 MB | Video S3. Real-time 4D flow MRI of a patient with atrial fibrillation. This video clip contains the reconstructed magnitude images and velocity maps over ten cardiac cycles from the proposed real-time 4D flow imaging method for a patient with atrial fibrillation. The synchronized respiratory and cardiac motion signals are also shown. |
| mrm29557-sup-0001-VideoS4.gifapplication/unknown, 12.7 MB | Video S4. Real-time 4D flow MRI of a patient with atrial fibrillation. This video clip contains the streamline visualization of the blood flow over ten cardiac cycles from the proposed real-time 4D flow imaging method for a patient with atrial fibrillation. The synchronized respiratory and cardiac motion signals and the flow curve associated with ascending aorta are also shown. |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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