Hybrid-state free precession in nuclear magnetic resonance

The dynamics of large spin-1/2 ensembles are commonly described by the Bloch equation, which is characterized by the magnetization’s non-linear response to the driving magnetic field. Consequently, most magnetic field variations result in non-intuitive spin dynamics, which are sensitive to small calibration errors. Although simplistic field variations result in robust spin dynamics, they do not explore the richness of the system’s phase space. Here, we identify adiabaticity conditions that span a large experiment design space with tractable dynamics. All dynamics are trapped in a one-dimensional subspace, namely in the magnetization’s absolute value, which is in a transient state, while its direction adiabatically follows the steady state. In this hybrid state, the polar angle is the effective drive of the spin dynamics. As an example, we optimize this drive for robust and efficient quantification of spin relaxation times and utilize it for magnetic resonance imaging of the human brain.Nuclear magnetic resonance is a technique ubiquitous in a diverse range of scientific and clinical fields. However, it can be sensitive to small deviations in the driving magnetic fields, which can easily disrupt measurement accuracy. Here, the authors develop a hybrid-state free precession approach which demonstrates greater robustness against deviations in the magnetic fields and exhibits an improved signal-to-noise ratio.

[1]  V. Fock,et al.  Beweis des Adiabatensatzes , 1928 .

[2]  I. Rabi,et al.  A New Method of Measuring Nuclear Magnetic Moment , 1938 .

[3]  E. Purcell,et al.  Relaxation Effects in Nuclear Magnetic Resonance Absorption , 1948 .

[4]  H. C. Torrey Bloch Equations with Diffusion Terms , 1956 .

[5]  H. Mcconnell Reaction Rates by Nuclear Magnetic Resonance , 1958 .

[6]  H. Carr STEADY-STATE FREE PRECESSION IN NUCLEAR MAGNETIC RESONANCE , 1958 .

[7]  J. H. Wilkinson The algebraic eigenvalue problem , 1966 .

[8]  R. Freeman,et al.  Phase and intensity anomalies in fourier transform NMR , 1971 .

[9]  P. Lauterbur,et al.  Image Formation by Induced Local Interactions: Examples Employing Nuclear Magnetic Resonance , 1973, Nature.

[10]  D. Hoult The solution of the bloch equations in the presence of a varying B1 field—An approach to selective pulse analysis , 1979 .

[11]  D. Hoult,et al.  Selective population inversion in NMR , 1984, Nature.

[12]  A. Macovski,et al.  Optimal Control Solutions to the Magnetic Resonance Selective Excitation Problem , 1986, IEEE Transactions on Medical Imaging.

[13]  J Hennig,et al.  RARE imaging: A fast imaging method for clinical MR , 1986, Magnetic resonance in medicine.

[14]  R. Balaban,et al.  Magnetization transfer contrast (MTC) and tissue water proton relaxation in vivo , 1989, Magnetic resonance in medicine.

[15]  J. Mugler,et al.  Three‐dimensional magnetization‐prepared rapid gradient‐echo imaging (3D MP RAGE) , 1990, Magnetic resonance in medicine.

[16]  Jürgen Hennig,et al.  Echoes—how to generate, recognize, use or avoid them in MR‐imaging sequences. Part II: Echoes in imaging sequences , 1991 .

[17]  J. Hennig Echoes—how to generate, recognize, use or avoid them in MR‐imaging sequences. Part I: Fundamental and not so fundamental properties of spin echoes , 1991 .

[18]  C. R. Rao,et al.  Information and the Accuracy Attainable in the Estimation of Statistical Parameters , 1992 .

[19]  Jonathan A. Jones,et al.  Optimal Sampling Strategies for the Measurement of Spin–Spin Relaxation Times , 1996 .

[20]  W. Manning,et al.  Simultaneous acquisition of spatial harmonics (SMASH): Fast imaging with radiofrequency coil arrays , 1997, Magnetic resonance in medicine.

[21]  N. Gershenfeld,et al.  Bulk Spin-Resonance Quantum Computation , 1997, Science.

[22]  Jonathan A. Jones Optimal Sampling Strategies for the Measurement of Relaxation Times in Proteins , 1997 .

[23]  G. Castagnoli,et al.  Geometric quantum computation with NMR , 1999, quant-ph/9910052.

[24]  Jonathan A. Jones,et al.  Geometric quantum computation using nuclear magnetic resonance , 2000, Nature.

[25]  P. Boesiger,et al.  Advances in sensitivity encoding with arbitrary k‐space trajectories , 2001, Magnetic resonance in medicine.

[26]  J. Pauly,et al.  Characterization and reduction of the transient response in steady‐state MR imaging , 2001, Magnetic resonance in medicine.

[27]  K. Scheffler,et al.  Optimization of signal behavior in the transition to driven equilibrium in steady‐state free precession sequences , 2002, Magnetic resonance in medicine.

[28]  B. Rutt,et al.  Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state , 2003, Magnetic resonance in medicine.

[29]  K. Scheffler,et al.  Is TrueFISP a gradient‐echo or a spin‐echo sequence? , 2003, Magnetic resonance in medicine.

[30]  Timo O. Reiss,et al.  Application of optimal control theory to the design of broadband excitation pulses for high-resolution NMR. , 2003, Journal of magnetic resonance.

[31]  M. Griswold,et al.  Inversion recovery TrueFISP: Quantification of T1, T2, and spin density , 2004, Magnetic resonance in medicine.

[32]  C. Ganter Off‐resonance effects in the transient response of SSFP sequences , 2004, Magnetic resonance in medicine.

[33]  A. Haase,et al.  Rapid NMR Imaging Using Low Flip-Angle Pulses , 2004 .

[34]  C. Ganter Static susceptibility effects in balanced SSFP sequences , 2006, Magnetic resonance in medicine.

[35]  K. Scheffler,et al.  On the origin of apparent low tissue signals in balanced SSFP , 2006, Magnetic resonance in medicine.

[36]  Olaf Dössel,et al.  An Optimal Radial Profile Order Based on the Golden Ratio for Time-Resolved MRI , 2007, IEEE Transactions on Medical Imaging.

[37]  Fred W. Glover,et al.  Scatter Search and Local Nlp Solvers: A Multistart Framework for Global Optimization , 2006, INFORMS J. Comput..

[38]  Yu Li,et al.  A software channel compression technique for faster reconstruction with many channels. , 2008, Magnetic resonance imaging.

[39]  Iven Mareels,et al.  Novel insight into magnetic resonance through a spherical coordinate framework for the Bloch equation , 2009, Medical Imaging.

[40]  L. Axel,et al.  Rapid B1+ mapping using a preconditioning RF pulse with TurboFLASH readout , 2010, Magnetic resonance in medicine.

[41]  E. Hahn,et al.  Spin Echoes , 2011 .

[42]  Danny C. Kim,et al.  Free-Breathing Radial 3D Fat-Suppressed T1-Weighted Gradient Echo Sequence: A Viable Alternative for Contrast-Enhanced Liver Imaging in Patients Unable to Suspend Respiration , 2011, Investigative radiology.

[43]  A. Haase,et al.  FLASH imaging: rapid NMR imaging using low flip-angle pulses. 1986. , 1986, Journal of magnetic resonance.

[44]  S. Glaser,et al.  Second order gradient ascent pulse engineering. , 2011, Journal of magnetic resonance.

[45]  W. W. Hansen,et al.  Nuclear Induction , 2011 .

[46]  M. Griswold,et al.  IR TrueFISP with a golden‐ratio‐based radial readout: Fast quantification of T1, T2, and proton density , 2013, Magnetic resonance in medicine.

[47]  S. Glaser,et al.  Understanding the global structure of two-level quantum systems with relaxation: Vector fields organized through the magic plane and the steady-state ellipsoid , 2013 .

[48]  J. Duerk,et al.  Magnetic Resonance Fingerprinting , 2013, Nature.

[49]  Michael Elad,et al.  ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: Where SENSE meets GRAPPA , 2014, Magnetic resonance in medicine.

[50]  Yun Jiang,et al.  SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain , 2014, IEEE Transactions on Medical Imaging.

[51]  M. Griswold,et al.  MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout , 2015, Magnetic resonance in medicine.

[52]  M. Dupuis,et al.  Prospective study on microscopic potential with Gogny interaction , 2015, 1504.05817.

[53]  Matthias Weigel,et al.  Extended phase graphs: Dephasing, RF pulses, and echoes ‐ pure and simple , 2015, Journal of magnetic resonance imaging : JMRI.

[54]  M. Schluchter,et al.  Music‐based magnetic resonance fingerprinting to improve patient comfort during MRI examinations , 2016, Magnetic resonance in medicine.

[55]  F. Knoll,et al.  Multiparametric imaging with heterogeneous radiofrequency fields , 2016, Nature Communications.

[56]  Justin P. Haldar,et al.  Optimal experiment design for magnetic resonance fingerprinting , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[57]  Debra F. McGivney,et al.  Slice profile and B1 corrections in 2D magnetic resonance fingerprinting , 2017, Magnetic resonance in medicine.

[58]  J. Duerk,et al.  MR fingerprinting using the quick echo splitting NMR imaging technique , 2017, Magnetic resonance in medicine.

[59]  J. Hennig,et al.  Pseudo Steady‐State Free Precession for MR‐Fingerprinting , 2017, Magnetic resonance in medicine.

[60]  Dmitry S. Novikov,et al.  Transverse NMR relaxation in biological tissues , 2018, NeuroImage.

[61]  F. Knoll,et al.  Low rank alternating direction method of multipliers reconstruction for MR fingerprinting , 2016, Magnetic resonance in medicine.

[62]  Shaihan J Malik,et al.  Joint system relaxometry (JSR) and Crámer‐Rao lower bound optimization of sequence parameters: A framework for enhanced precision of DESPOT T1 and T2 estimation , 2018, Magnetic resonance in medicine.

[63]  Justin P. Haldar,et al.  Optimal Experiment Design for Magnetic Resonance Fingerprinting: Cramér-Rao Bound Meets Spin Dynamics , 2017, IEEE Transactions on Medical Imaging.

[64]  Robert Brown,et al.  Parameter map error due to normal noise and aliasing artifacts in MR fingerprinting , 2019, Magnetic resonance in medicine.

[65]  Alessandro Sbrizzi,et al.  Understanding the Combined Effect of ${k}$ -Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions , 2018, IEEE Transactions on Medical Imaging.