Rotary excitation of non-sinusoidal pulsed magnetic fields: Towards non-invasive direct detection of cardiac conduction.

PURPOSE: There is a need for high resolution non-invasive imaging methods of physiologic magnetic fields. The purpose of this work is to develop a MRI detection approach for non-sinusoidal magnetic fields based on the rotary excitation (REX) mechanism which was previously successfully applied for the detection of oscillating magnetic fields in the sub-nT range. METHODS: The new detection concept was examined by means of Bloch simulations, evaluating the interaction effect of spin-locked magnetization and low-frequency pulsed magnetic fields. The REX detection approach was validated under controlled conditions in phantom experiments at 3 T. Gaussian and sinc-shaped stimuli were investigated. In addition, the detection of artificial fields resembling a cardiac QRS complex, which is the most prominent peak visible on a magnetocardiogram, was tested. RESULTS: Bloch simulations demonstrated that the REX method has a high sensitivity to pulsed fields in the resonance case, which is met when the spin-lock frequency coincides with a non-zero Fourier component of the stimulus field. In the experiments, we found that magnetic stimuli of different durations and waveforms can be distinguished by their characteristic REX response spectrum. The detected REX amplitude was proportional to the stimulus peak amplitude (R2 > 0.98) and the lowest field detection was 1 nT. Furthermore, the detection of QRS-like fields with varying QRS durations yielded significant results in a phantom setup (p < 0.001). CONCLUSION: REX detection can be transferred to non-sinusoidal pulsed magnetic fields and could provide a non-invasive, quantitative tool for spatially resolved assessment of cardiac biomagnetism. Potential applications include the direct detection and characterization of cardiac conduction.

Quantification of the rotating frame relaxation time T2ρ: Comparison of balanced spin-lock and continuous-wave Malcolm-Levitt preparations.

For the quantification of rotating frame relaxation times, the T2ρ relaxation pathway plays an essential role. Nevertheless, T2ρ imaging has been studied only to a small extent compared with T1ρ, and preparation techniques for T2ρ have so far been adapted from T1ρ methods. In this work, two different preparation concepts are compared specifically for the use of T2ρ mapping. The first approach involves transferring the balanced spin-locking (B-SL) concept of T1ρ imaging. The second and newly proposed approach is a continuous-wave Malcolm-Levitt (CW-MLEV) pulse train with zero echo times and was motivated from T2 preparation strategies. The modules are tested in Bloch simulations for their intrinsic sensitivity to field inhomogeneities and validated in phantom experiments. In addition, myocardial T2ρ mapping was performed in mice as an exemplary application. Our results demonstrate that the CW-MLEV approach provides superior robustness and thus suggest that established methods of T1ρ imaging are not best suited for T2ρ experiments. In the presence of field inhomogeneities, the simulations indicated an increased banding compensation by a factor of 4.1 compared with B-SL. Quantification of left ventricular T2ρ time in mice yielded more consistent results, and values in the range of 59.2-61.1 ms (R2 = 0.986-0.992) were observed at 7 T.

Quantification correction for free-breathing myocardial T1ρ mapping in mice using a recursively derived description of a T1ρ* relaxation pathway.

BACKGROUND: Fast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T1ρ relaxation pathway. In this study, we present an improved quantification method for T1ρ using a newly derived formalism of a T1ρ* relaxation pathway. METHODS: The new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T1ρ mapping in mice. Here, the impact of the breath dependent spin recovery time Trec on the quantification results was examined in detail. RESULTS: Simulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from - 7.4% to - 0.97%. In vivo, a correlation of uncorrected T1ρ with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T1ρ values in different animals was reduced by at least 39%. CONCLUSION: The suggested quantification formalism enables fast and precise myocardial T1ρ quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.