Time efficient whole-brain coverage with MR Fingerprinting using slice-interleaved echo-planar-imaging
Open accessAbstract
Magnetic resonance fingerprinting (MRF) is a promising method for fast simultaneous quantification of multiple tissue parameters. The objective of this study is to improve the coverage of MRF based on echo-planar imaging (MRF-EPI) by using a slice-interleaved acquisition scheme. For this, the MRF-EPI is modified to acquire several slices in a randomized interleaved manner, increasing the effective repetition time of the spoiled gradient echo readout acquisition in each slice. Per-slice matching of the signal-trace to a precomputed dictionary allows the generation of T 1 and T 2* maps with integrated B 1+ correction. Subsequent compensation for the coil sensitivity profile and normalization to the cerebrospinal fluid additionally allows for quantitative proton density (PD) mapping. Numerical simulations are performed to optimize the number of interleaved slices. Quantification accuracy is validated in phantom scans and feasibility is demonstrated in-vivo. Numerical simulations suggest the acquisition of four slices as a trade-off between quantification precision and scan-time. Phantom results indicate good agreement with reference measurements (Difference T 1: −2.4 ± 1.1%, T 2*: −0.5 ± 2.5%, PD: −0.5 ± 7.2%). In-vivo whole-brain coverage of T 1, T 2* and PD with 32 slices was acquired within 3:36 minutes, resulting in parameter maps of high visual quality and comparable performance with single-slice MRF-EPI at 4-fold scan-time reduction.
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The tremendous amounts of high-impact publications in top journals dealing with deep learning in medical imaging illustrate the value of the methods.
“This is illustrated by the tremendous amounts of high-impact publications in top-journals dealing with deep learning in medical imaging (for example [17, 21, 30, 32, 40, 90, 162, 137, 140, 273, 285], all published in 2018).”
From An overview of deep learning in medical imaging focusing on MRI (2019) · cites this paper as [162]
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Magnetic resonance fingerprinting
Ma, D., Gulani, V., Seiberlich, N., Liu, K., Sunshine, J. L., Duerk, J. L., & Griswold, M. A. (2013) · Nature · doi:10.1038/nature11971 · Cited by 1,577 · see citing works
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An overview of deep learning in medical imaging focusing on MRI
Lundervold, A. S., & Lundervold, A. (2019) · Zeitschrift für Medizinische Physik · doi:10.1016/j.zemedi.2018.11.002 · Cited by 2,058 · see citing works
- Authors
- Rieger, B., Akçakaya, M., Pariente, J. C., Llufriu, S., Martinez-Heras, E., Weingärtner, S., & Schad, L. R.
- Affiliations
- Heidelberg University (DE)
- University of Minnesota (US)
- Corresponding author
- Weingärtner, Sebastian
- Venue
- Scientific Reports
- Published
- 2018-04-27
- Volume
- 8
- Issue
- 1
- Pages
- 6667-6667
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5923901
- OpenAlex
- W2806139191
- Cited by
- 39
- References
- 1
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 3 · 2023: 5 · 2022: 3 · 2021: 10 · 2020: 6 · 2019: 5 · 2018: 2
- FWCI
- 3.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- National Science Foundation (1651825)
- Deutsche Forschungsgemeinschaft
- Universität Heidelberg
- Red Española de Esclerosis Múltiple (RD12/0060/01‐02, RD16/0015/0002,, RD16/0015/0003, RD16/0015/0002, RD16/0015/0003, RD12/0032/0002, RD12/0060/01-02, RD12/0032, RD12/0032/0002)
- National Institutes of Health
- Instituto de Salud Carlos III (JR14/00015, PI15/00587, RD12/0032/0002, RD16/0015/0002, RD12/0060/01-02, RD16/0015/0003, RD12/0032)
- European Regional Development Fund
- National Heart, Lung, and Blood Institute (R00HL111410)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › NMR spectroscopy and applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- magnetic resonance fingerprinting, echo planar imaging, whole-brain coverage, T1 mapping, T2 mapping, proton density mapping, B1 correction, spoiled gradient echo, scan time reduction
- MeSH terms
- Brain, Humans, Image Processing, Computer-Assisted, Sensitivity and Specificity, Echo-Planar Imaging, Healthy Volunteers
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