PURPOSE: The aim of this study was to develop a simple, robust, and easy-to-use calibration procedure for correcting misalignments in rosette MRI k-space sampling, with the objective of producing images with minimal artifacts. METHODS: Quick automatic calibration scans were proposed for the beginning of the measurement to collect information on the time course of the rosette acquisition trajectory. A two-parameter model was devised to match the measured time-varying readout gradient delays and approximate the actual rosette sampling trajectory. The proposed calibration approach was implemented, and performance assessment was conducted on both phantoms and human subjects. RESULTS: The fidelity of phantom and in vivo images exhibited significant improvement compared with uncorrected rosette data. The two-parameter calibration approach also demonstrated enhanced precision and reliability, as evidenced by quantitative T 2 * $$ {\mathrm{T}}_2^{\ast } $$ relaxometry analyses. CONCLUSION: Adequate correction of data sampling is a crucial step in rosette MRI. The presented experimental results underscore the robustness, ease of implementation, and suitability for routine experimental use of the proposed two-parameter rosette trajectory calibration approach.

Central European Institute of Technology Masaryk University Brno Czech Republic

Department of Radiology Masaryk Memorial Cancer Institute Brno Czech Republic

Institute of Scientific Instruments of the Czech Academy of Sciences Brno Czech Republic

See more in PubMed

Noll DC. Multishot rosette trajectories for spectrally selective MR imaging. IEEE Trans Med Imaging. 1997;16:372‐377. doi:10.1109/42.611345 PubMed DOI

Schirda CV, Zhao T, Andronesi OC, et al. In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels. Magn Reson Med. 2016;76:380‐390. doi:10.1002/mrm.25896 PubMed DOI PMC

Schirda CV, Zhao T, Yushmanov VE, et al. Fast 3D rosette spectroscopic imaging of neocortical abnormalities at 3 T: assessment of spectral quality. Magn Reson Med. 2018;79:2470‐2480. doi:10.1002/mrm.26901 PubMed DOI PMC

Liu Y, Hamilton J, Eck B, Griswold M, Seiberlich N. Myocardial T1 and T2 quantification and water–fat separation using cardiac MR fingerprinting with rosette trajectories at 3T and 1.5T. Magn Reson Med. 2021;85:103‐119. doi:10.1002/mrm.28404 PubMed DOI PMC

Liu Y, Hamilton J, Jiang Y, Seiberlich N. Cardiac MRF using rosette trajectories for simultaneous myocardial T1, T2, and proton density fat fraction mapping. Front Cardiovasc Med. 2022;9:977603. PubMed PMC

Shen X, Özen AC, Sunjar A, et al. Ultra‐short T2 components imaging of the whole brain using 3D dual‐echo UTE MRI with rosette k‐space pattern. Magn Reson Med. 2023;89:508‐521. doi:10.1002/mrm.29451 PubMed DOI PMC

Li Y, Yang R, Zhang C, Zhang J, Jia S, Zhou Z. Analysis of generalized rosette trajectory for compressed sensing MRI. Med Phys. 2015;42:5530‐5544. doi:10.1118/1.4928152 PubMed DOI

Xu W, Yang X, Liu K, Tian Q, Xu J. Rosette trajectories for fast MRI based on an adaptive reconstruction method. IEEE Access. 2021;9:35164‐35177. doi:10.1109/ACCESS.2021.3062020 DOI

Dietrich BE, Brunner DO, Wilm BJ, et al. A field camera for MR sequence monitoring and system analysis. Magn Reson Med. 2015;75:1831‐1840. doi:10.1002/mrm.25770 PubMed DOI

Gilbert KM, Dubovan PI, Gati JS, Menon RS, Baron CA. Integration of an RF coil and commercial field camera for ultrahigh‐field MRI. Magn Reson Med. 2022;87:2551‐2565. doi:10.1002/mrm.29130 PubMed DOI

Rahmer J, Schmale I, Mazurkewitz P, Lips O, Börnert P. Non‐Cartesian k‐space trajectory calculation based on concurrent reading of the gradient amplifiers' output currents. Magn Reson Med. 2021;85:3060‐3070. doi:10.1002/mrm.28725 PubMed DOI

Duyn JH, Yang Y, Frank JA, van der Veen JW. Simple correction method fork‐space trajectory deviations in MRI. J Magn Reson. 1998;132:150‐153. doi:10.1006/jmre.1998.1396 PubMed DOI

Rosenzweig S, Holme HCM, Uecker M. Simple auto‐calibrated gradient delay estimation from few spokes using radial intersections (RING). Magn Reson Med. 2019;81:1898‐1906. doi:10.1002/mrm.27506 PubMed DOI

Moussavi A, Untenberger M, Uecker M, Frahm J. Correction of gradient‐induced phase errors in radial MRI. Magn Reson Med. 2013;71:308‐312. doi:10.1002/mrm.24643 PubMed DOI

Goora FG, Colpitts BG, Balcom BJ. Arbitrary magnetic field gradient waveform correction using an impulse response based pre‐equalization technique. J Magn Reson. 2014;238:70‐76. doi:10.1016/j.jmr.2013.11.003 PubMed DOI

Fabich HT, Benning M, Sederman AJ, Holland DJ. Ultrashort echo time (UTE) imaging using gradient pre‐equalization and compressed sensing. J Magn Reson. 2014;245:116‐124. doi:10.1016/j.jmr.2014.06.015 PubMed DOI

Addy NO, Wu HH, Nishimura DG. Simple method for MR gradient system characterization and k‐space trajectory estimation. Magn Reson Med. 2012;68:120‐129. doi:10.1002/mrm.23217 PubMed DOI PMC

Bush AM, Sandino CM, Ramachandran S, et al. Rosette trajectories enable ungated, motion‐robust, simultaneous cardiac and liver PubMed DOI PMC

Roeloffs V, Bush AM, Anand S, Lustig M. Correcting gradient delays in multi‐Echo rosette trajectories with RING. In: Proceedings of the 28th Annual Meeting of ISMRM. ISMRM; 2020:3393.

Dimov AV, Boyd NA, Kawaji K, Carroll TJ. Retrospective gradient delay correction in multi‐shot multi‐echo rosette acquisition. Proceedings of the 27th Annual Meeting of ISMRM. ISMRM; 2019:4.

Robison RK, Devaraj A, Pipe JG. Fast, simple gradient delay estimation for spiral MRI. Magn Reson Med. 2010;63:1683‐1690. doi:10.1002/mrm.22327 PubMed DOI

Mahmud SZ, Denney TS, Bashir A. Feasibility of spinal cord imaging at 7 T using rosette trajectory with magnetization transfer preparation and compressed sensing. Sci Rep. 2023;13:8777. doi:10.1038/s41598-023-35853-7 PubMed DOI PMC

Stich M, Wech T, Slawig A, et al. Gradient waveform pre‐emphasis based on the gradient system transfer function. Magn Reson Med. 2018;80:1521‐1532. doi:10.1002/mrm.27147 PubMed DOI

Peters DC, Derbyshire JA, McVeigh ER. Centering the projection reconstruction trajectory: reducing gradient delay errors. Magn Reson Med. 2003;50:1‐6. doi:10.1002/mrm.10501 PubMed DOI PMC

Tan H, Meyer CH. Estimation of k‐space trajectories in spiral MRI. Magn Reson Med. 2009;61:1396‐1404. doi:10.1002/mrm.21813 PubMed DOI PMC

Bucholz EK, Song J, Johnson GA, Hancu I. Multispectral imaging with three‐dimensional rosette trajectories. Magn Reson Med. 2008;59:581‐589. doi:10.1002/mrm.21551 PubMed DOI PMC

Feng L. Golden‐angle radial MRI: basics, advances, and applications. J Magn Reson Imaging. 2022;56:45‐62. doi:10.1002/jmri.28187 PubMed DOI PMC

Noll DC, Meyer CH, Pauly JM, Nishimura DG, Macovski A. A homogeneity correction method for magnetic resonance imaging with time‐varying gradients. IEEE Trans Med Imaging. 1991;10:629‐637. doi:10.1109/42.108599 PubMed DOI

Turkbey B, Rosenkrantz AB, Haider MA, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol. 2019;76:340‐351. doi:10.1016/j.eururo.2019.02.033 PubMed DOI

Liebert A, Das BK, Kapsner LA, et al. Smart forecasting of artifacts in contrast‐enhanced breast MRI before contrast agent administration. Eur Radiol. 2023;34:4752‐4763. doi:10.1007/s00330-023-10469-7 PubMed DOI PMC

Brodsky EK, Klaers JL, Samsonov AA, Kijowski R, Block WF. Rapid measurement and correction of phase errors from B0 eddy currents: impact on image quality for non‐Cartesian imaging. Magn Reson Med. 2012;69:509‐515. doi:10.1002/mrm.24264 PubMed DOI PMC

Bernstein MA, King KF, Zhou XJ. Handbook of MRI Pulse Sequences. Elsevier; 2004.

Fu Z, Johnson K, Altbach MI, Bilgin A. Cancellation of streak artifacts in radial abdominal imaging using interference null space projection. Magn Reson Med. 2022;88:1355‐1369. doi:10.1002/mrm.29285 PubMed DOI PMC

Langlois S, Desvignes M, Constans J. M, Revenu M. MRI geometric distortion: a simple approach to correcting the effects of non‐linear gradient fields. J Magn Reson Imaging. 1999;9:821‐831. doi:10.1002/(SICI)1522-2586(199906)9:6<821::AID-JMRI9>3.0.CO;2-2 PubMed DOI