MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation

Zhehao Hu; Jiayu Xiao; Xianglun Mao; Yibin Xie; Alan C Kwan; Shlee S Song; Michael W Fong; Alison G Wilcox; Debiao Li; Anthony G Christodoulou; Zhaoyang Fan

doi:10.1002/mrm.29522

MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation

Magn Reson Med. 2023 Apr;89(4):1496-1505. doi: 10.1002/mrm.29522. Epub 2022 Nov 6.

Authors

Zhehao Hu^{1

2

3}, Jiayu Xiao¹, Xianglun Mao², Yibin Xie², Alan C Kwan^{2

4}, Shlee S Song⁵, Michael W Fong^{6

7}, Alison G Wilcox¹, Debiao Li^{2

3}, Anthony G Christodoulou^{2

3}, Zhaoyang Fan^{1

2

8

9}

Affiliations

¹ Department of Radiology, University of Southern California, Los Angeles, California, USA.
² Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
³ Department of Bioengineering, University of California, Los Angeles, California, USA.
⁴ Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
⁵ Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, California, USA.
⁶ Division of Cardiovascular Medicine, University of Southern California, Los Angeles, California, USA.
⁷ Cardiovascular Thoracic Institute, University of Southern California, Los Angeles, California, USA.
⁸ Department of Radiation Oncology, University of Southern California, Los Angeles, California, USA.
⁹ Department of Biomedical Engineering, University of Southern California, Los Angeles, California, USA.

Abstract

Purpose: To extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment.

Methods: MT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated.

Results: MT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects.

Conclusion: The refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted.

Keywords: MR Multitasking; multi-contrast imaging; multi-dimensional imaging; phase-resolved imaging; water-fat separation; whole-heart MR.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Heart Ventricles
Humans
Imaging, Three-Dimensional* / methods
Magnetic Resonance Imaging
Reproducibility of Results
Stroke Volume
Ventricular Function, Left
Water*

Substances

Water

Abstract

Publication types

MeSH terms

Substances

Grants and funding