Fingerprinting: Concept & State-of-the Art Techniques
Yong Chen1
1Radiology, Case Western Reserve University, Cleveland, OH, United States

Synopsis

Magnetic Resonance Fingerprinting is a novel imaging method for rapid quantitative imaging. This presentation will first cover the basic concepts of Magnetic Resonance Fingerprinting and then introduce its extension for cardiac imaging. We will further discuss recent advances in cardiac Magnetic Resonance Fingerprinting and the future directions in clinical applications.

Target Audience

Basic scientists and clinicians who are interested in quantitative imaging and magnetic resonance fingerprinting in cardiac MRI.

Objectives

  • Provide an overview of magnetic resonance fingerprinting for rapid quantitative mapping ·
  • Understand the basic concepts of cardiac magnetic resonance fingerprinting ·
  • Discuss recent advances in cardiac magnetic resonance fingerprinting and potential applications in cardiac imaging

Overview of Magnetic Resonance Fingerprinting

Many studies have demonstrated that quantitative tissue mapping can provide improved tissue characterization and disease monitoring as compared to conventional contrast-weighted imaging. However, quantitative tissue mapping is extremely challenging using traditional imaging approaches. Magnetic Resonance Fingerprinting (MRF) is a novel imaging acquisition and post-processing approach which can provide simultaneous quantification of multiple tissue properties in a single examination [1,2]. Compared to conventional quantitative MR imaging approaches, MRF has demonstrated superior performance in both accuracy and efficiency [1]. In this section, we will first review the basic concepts of MRF and its application in quantitative tissue mapping in multiple human organs [3–6].

Technical Development of Cardiac Magnetic Resonance Fingerprinting

Development of MRF methods for cardiac imaging faces special challenges due to cardiac motions. In this section, we will first briefly review conventional T1 and T2 relaxation time measurement techniques in cardiac imaging [7,8]. We will then introduce the technical aspects of the cardiac MRF method developed by Hamilton et al. including pulse sequence design, MRF dictionary generation, and pattern matching [5]. The performance of cardiac MRF for myocardial T1 and T2 mapping as compared to traditional methods will be discussed. The confounding factors that could influence the accuracy and precision of this cardiac MRF technique will be reviewed [9].

Recent Advances in Cardiac Magnetic Resonance Fingerprinting and Future Directions

This section will review recent technical developments in cardiac MRF, including acceleration of data acquisition and post-processing, and expansion of tissue properties quantified by cardiac MRF [10–13]. We will also review some preliminary clinical studies using cardiac MRF and potential applications in future studies.

Acknowledgements

No acknowledgement found.

References

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[3] Chen Y, Jiang Y, Pahwa S, Ma D, Lu L, Twieg MD, et al. MR fingerprinting for rapid quantitative abdominal imaging. Radiology 2016;279:278–86.

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[9] Hamilton JI, Jiang Y, Ma D, Lo WC, Gulani V, Griswold M, et al. Investigating and reducing the effects of confounding factors for robust T1and T2mapping with cardiac MR fingerprinting. Magn Reson Imaging 2018;53:40–51.

[10] Jaubert O, Cruz G, Bustin A, Schneider T, Lavin B, Koken P, et al. Water–fat Dixon cardiac magnetic resonance fingerprinting. Magn Reson Med 2019:mrm.28070. https://doi.org/10.1002/mrm.28070.

[11] Fang Z, Chen Y, Liu M, Xiang L, Zhang Q, Wang Q, et al. Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Accelerated Data in Magnetic Resonance Fingerprinting. IEEE Trans Med Imaging 2019;38:2364–74.

[12] Hamilton JI, Jiang Y, Ma D, Chen | Yong, Lo W-C, Griswold | Mark, et al. Simultaneous multislice cardiac magnetic resonance fingerprinting using low rank reconstruction. NMR Biomed 2019;32:e4041.

[13] Hamilton JI, Seiberlich N. Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification. Proc IEEE 2019:1–17.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)