Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
366-05-003 ISMRM Abstract

3D T1/T2/T2*/PDFF rosette MRF for renal mass characterization

Primary: Acquisition & Reconstruction - Quantitative Imaging: relaxometry, multi-parametric, MR Fingerprinting, and synthetic MRI
Secondary: Body - Kidney
366-05-003 · Quantitative Applications in Body MRI: Make the Numbers Count · Monday, 11 May, 4:10 PM–5:05 PM · Digital Posters Row G
Keywords: MR Fingerprinting Motion Correction Kidney cancer Low rank
Accepted
Gastao Cruz1, Evan Cummings1,2, Jacob Richardson1, Tom Griesler 1,2, Jesse Hamilton1,2,3, Hero K Hussain1, Vikas Gulani1,3, Matthew Davenport1,3,4, Nicole Seiberlich1,2,3
1Department of Radiology, University of Michigan, Ann Arbor, United States of America
2Department of Biomedical Engineering, University of Michigan, Ann Arbor, United States of America
3University of Michigan, Ann Arbor, United States of America
4Department of Urology, University of Michigan, Ann Arbor, United States of America
Presenting Author: Tom Griesler

Synopsis

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References

1. Schieda, N., et al., Multicenter Evaluation of Multiparametric MRI Clear Cell Likelihood Scores in Solid Indeterminate Small Renal Masses. Radiology, 2022. 303(3): p. 590-599
2. Adams, L.C., et al., Native T1 Mapping as an In Vivo Biomarker for the Identification of Higher-Grade Renal Cell Carcinoma: Correlation With Histopathological Findings. Invest Radiol, 2019. 54(2): p. 118-128.
3. Adams, L.C., et al., Use of quantitative T2 mapping for the assessment of renal cell carcinomas: first results. Cancer Imaging, 2019. 19(1): p. 35.
4. Zhang, Y.D., et al., Comparison of Utility of Histogram Apparent Diffusion Coefficient and R2* for Differentiation of Low-Grade From High-Grade Clear Cell Renal Cell Carcinoma. AJR Am J Roentgenol, 2015. 205(2): p. W193-201.
5. Jomoto, W., et al., Differentiation of Angiomyolipoma With Minimal Fat from Clear Cell Renal Cell Carcinoma Using Non-contrast Multiparametric Magnetic Resonance Imaging. In Vivo, 2022. 36(6): p. 2790-2799.
6. Ma D, Gulani V, Seiberlich N, Liu K, Sunshine JL, Duerk JL, Griswold MA. Magnetic resonance fingerprinting. Nature. 2013 Mar;495(7440):187-92.McGivney DF, Pierre E, Ma D, et al. SVD compression for magnetic resonance fingerprinting in the time domain. IEEE Trans. Med. Imaging 2014;33:2311–2322 doi: 10.1109/TMI.2014.2337321. [doi]
7. Jaubert O, Arrieta C, Cruz G, Bustin A, Schneider T, Georgiopoulos G, Masci PG, Sing‐Long C, Botnar RM, Prieto C. Multi‐parametric liver tissue characterization using MR fingerprinting: simultaneous T1, T2, T2*, and fat fraction mapping. Magnetic resonance in medicine. 2020 Nov;84(5):2625-35.
8. Chen Y, MacAskill CJ, Huang S, Dell KM, Tirumani SH, Griswold MA, Flask CA. MR Fingerprinting for Quantitative Kidney Imaging. In Advanced Clinical MRI of the Kidney: Methods and Protocols 2023 Nov 18 (pp. 163-180). Cham: Springer International Publishing.
9. Cruz G, Qi H, Jaubert O, Kuestner T, Schneider T, Botnar RM, Prieto C. Generalized low‐rank nonrigid motion‐corrected reconstruction for MR fingerprinting. Magnetic Resonance in Medicine. 2022 Feb;87(2):746-63.
10. Cruz G, Cummings E, Griesler T, Hamilton J, Vikas Gulani, Davenport M, et al. 3D Free-breathing T1, T2, T2* and PDFF mapping in the kidneys with Dictionary-Patch regularized Low Rank Motion Corrected Rosette MRF. Proceedings on International Society for Magnetic Resonance in Medicine Scientific Meeting, 2025, program number 2733.
11. Vahle T, Bacher M, Rigie D, Fenchel M, Speier P, Bollenbeck J, Schäfers KP, Kiefer B, Boada FE. Respiratory motion detection and correction for MR using the pilot tone: applications for MR and simultaneous PET/MR examinations. Investigative radiology. 2020 Mar 1;55(3):153-9.
12. Solomon E, Rigie DS, Vahle T, Paška J, Bollenbeck J, Sodickson DK, Boada FE, Block KT, Chandarana H. Free‐breathing radial imaging using a pilot‐tone radiofrequency transmitter for detection of respiratory motion. Magnetic resonance in medicine. 2021 May;85(5):2672-85.
13. Pruessmann KP, Weiger M, Börnert P, Boesiger P. Advances in sensitivity encoding with arbitrary k‐space trajectories. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine. 2001 Oct;46(4):638-51.
14. Rueckert D, Sonoda LI, Hayes C, Hill DL, Leach MO, Hawkes DJ. Nonrigid registration using free-form deformations: application to breast MR images. IEEE transactions on medical imaging. 1999 Aug;18(8):712-21.
15. Modat M, Ridgway GR, Taylor ZA, Lehmann M, Barnes J, Hawkes DJ, Fox NC, Ourselin S. Fast free-form deformation using graphics processing units. Computer methods and programs in biomedicine. 2010 Jun 1;98(3):278-84.
16. Adams LC, Ralla B, Jurmeister P, Bressem KK, Fahlenkamp UL, Hamm B, Busch J, Makowski MR. Native T1 mapping as an in vivo biomarker for the identification of higher-grade renal cell carcinoma: correlation with histopathological findings. Investigative radiology. 2019 Feb 1;54(2):118-28.
17. Zhang, Y., et al., Addressing metabolic heterogeneity in clear cell renal cell carcinoma with quantitative Dixon MRI. JCI Insight, 2017. 2(15).

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/366-05-003