0812 ISMRM Abstract

MIMOSA: Multi-parametric Imaging using Multiple-echoes with Optimized Simultaneous Acquisition for highly-efficient quantitative MRI

0812 · Quantitative Imaging · Wednesday, 14 May, 8:15 AM–10:15 AM · 323AB

Keywords: Quantitative Imaging Multi-parametric mapping

Accepted

Yuting Chen ^1,2,3, Yohan Jun^2,3, Amir Heydari⁴, Xingwang Yong^2,3, Huafeng Liu¹, Huihui Ye⁵, Borjan Gagoski^3,6, Berkin Bilgic^2,3,7, Shohei Fujita^2,3

¹State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, Hangzhou, China

²Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, United States of America

³Department of Radiology, Harvard Medical School, Boston, United States of America

⁴Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran (Islamic Republic of)

⁵School of Communication Engineering, Hangzhou Dianzi University, Hangzhou, China

⁶Fetal-Neonatal Neuroimaging & Developmental Science Center, Boston Children's Hospital, Boston, United States of America

⁷Harvard/MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, United States of America

Presenting Author: Yuting Chen

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References

1. Cao T, Ma S, Wang N, et al. Three-dimensional simultaneous brain mapping of T1, T2, and magnetic susceptibility with MR Multitasking. Magnetic Resonance in Medicine . 2022;87(3):1375-1389. doi:10.1002/mrm.29059 2. Zhang J, Nguyen TD, Solomon E, et al. mcLARO : Multi ‐ contrast learned acquisition and reconstruction optimization for simultaneous quantitative multi ‐ parametric mapping. Magnetic Resonance in Med . September 2023:mrm.29854. doi:10.1002/mrm.29854 3. Kvernby S, Warntjes MJB, Haraldsson H, Carlhäll CJ, Engvall J, Ebbers T. Simultaneous three-dimensional myocardial T1 and T2 mapping in one breath hold with 3D-QALAS. J Cardiovasc Magn Reson . 2014;16(1):102. doi:10.1186/s12968-014-0102-0 4. Cho J, Gagoski B, Kim TH, et al. Time ‐ efficient, high ‐ resolution 3T whole ‐ brain relaxometry using 3D ‐ QALAS with wave ‐ CAIPI readouts. Magnetic Resonance in Med . September 2023:mrm.29865. doi:10.1002/mrm.29865 5. Jun Y, Arefeen Y, Cho J, et al. Zero-DeepSub: Zero-shot deep subspace reconstruction for rapid multiparametric quantitative MRI using 3D-QALAS. Magnetic Resonance in Medicine . 2024;91(6):2459-2482. doi:10.1002/mrm.30018 6. Fujita S, Gagoski B, Hwang KP, et al. Cross-vendor multiparametric mapping of the human brain using 3D-QALAS: A multicenter and multivendor study. Magnetic Resonance in Medicine . 2024;91(5):1863-1875. doi:10.1002/mrm.29939 7. Layton KJ, Kroboth S, Jia F, et al. Pulseq: A rapid and hardware-independent pulse sequence prototyping framework. Magnetic Resonance in Medicine . 2017;77(4):1544-1552. doi:10.1002/mrm.26235 8. Cheng JY, Zhang T, Ruangwattanapaisarn N, et al. Free ‐ breathing pediatric MRI with nonrigid motion correction and acceleration. Journal of Magnetic Resonance Imaging . 2015;42(2). [doi]

2. Haldar JP. Low-Rank Modeling of Local -Space Neighborhoods (LORAKS) for Constrained MRI. IEEE TRANSACTIONS ON MEDICAL IMAGING . 2014;33(3).

3. Kim TH, Setsompop K, Haldar JP. LORAKS makes better SENSE: Phase ‐ constrained partial fourier SENSE reconstruction without phase calibration. Magnetic Resonance in Med . 2017;77(3):1021-1035. doi:10.1002/mrm.26182 11. Golub G, Pereyra V. Separable nonlinear least squares: the variable projection method and its applications. Inverse Problems . 2003;19(2):R1. doi:10.1088/0266-5611/19/2/201 12. Shin HG, Lee J, Yun YH, et al. χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain. NeuroImage . 2021;240:118371. doi:10.1016/j.neuroimage.2021.118371 13. Kim M, Shin H-G, Oh C, et al. Chi-sepnet: Susceptibility source separation using deep neural network. Proceedings of the 30th Annual ISMRM Meeting, London, 2022; 2464. [doi]

4. Collins DL, Zijdenbos AP, Kollokian V, et al. Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging . 1998;17(3):463-468. doi:10.1109/42.712135 15. Chung S, Kim D, Breton E, Axel L. Rapid B1+ mapping using a preconditioning RF pulse with TurboFLASH readout. Magnetic Resonance in Medicine . 2010;64(2):439-446. doi:10.1002/mrm.22423 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2025/0812