Synthetic contrast: technical aspect and recent advancement

Fuyixue Wang^1,2
¹Athinoula A. Martinos Center for Biomedical Imaging, MGH, Charlestown, MA, United States, ²Department of Radiology, Harvard Medical School, Charlestown, MA, United States

Synopsis

Keywords: Image acquisition: Multiparametric, Image acquisition: Image processing, Image acquisition: Fast imaging

Synthetic images with flexibly adjustable contrasts can be generated from quantitative multi-parametric MRI. With the advancement of fast multi-parametric imaging, synthetic imaging provides a more efficient MR exam paradigm to obtain clinically useful contrasts. This talk will cover the technical aspect of synthetic imaging. It will present the i) basics of contrast synthesis; 2) fast quantitative multi-parametric acquisition and their recent advancement, including multidynamic multiecho (MDME), MR Fingerprinting (MRF), MR Multitasking, and Echo-Planar Time-resolved Imaging (EPTI); and 3) recent advancement of imaging synthesis methods including machine learning based approaches. We will also discuss the future directions of synthetic imaging.

Abstract

Synthetic images^1-5 with different and flexibly adjustable contrasts can be generated from quantitative multi-parametric MRI data. With the advancement of fast MRI methods and significantly reduced scan time of multi-parametric imaging, synthetic imaging has become much more practical and provides a more efficient MR exam paradigm to obtain clinically useful contrasts. This talk will cover the technical aspect of synthetic imaging. It will present the i) basics of image contrast synthesis from multi-parametric data; 2) fast quantitative multi-parametric acquisition and their recent advancement, including multidynamic multiecho (MDME)^4-5, MR Fingerprinting (MRF)^6-7, MR Multitasking^8-9, and Echo Planar Time-resolved Imaging (EPTI)^10-12; and 3) recent advancement of imaging synthesis methods including machine learning based approaches^13-14. We will also discuss future directions of synthetic MRI toward better image quality and accuracy for clinical applications.

Acknowledgements

No acknowledgement found.

References

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Figures

Example synthetic images using quantitative multi-parametric images acquired by EPTI.

Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)