Purpose Accurate and artifact‐free T1ρ quantification is still a major challenge due to a susceptibility of the spin‐locking module to B0 and/or B1 field inhomogeneities. In this study, we present a novel spin‐lock preparation module (B‐SL) that enables an almost full compensation of both types of inhomogeneities. Methods The new B‐SL module contains a second 180° refocusing pulse to compensate each pulse in the preparation block by a corresponding pulse with opposite phase. For evaluation and validation of B‐SL, extensive simulations as well as phantom measurements were performed. Furthermore, the new module was compared to three common established compensation methods. Results Both simulations and measurements demonstrate a much lower susceptibility to artifacts for the B‐SL module, therefore providing an improved accuracy in T1ρ quantification. In the presence of field inhomogeneities, measurements revealed an increased banding compensation by 79% compared with the frequently used composite module. The goodness of the mono‐exponential T1ρ fitting procedure was improved by 58%. Conclusion The B‐SL preparation enables the generation of accurate relaxation maps with significantly reduced artifacts, even in the case of large field imperfections. Therefore, the B‐SL module is suggested to be highly beneficial for in vivo T1ρ quantification.
Purpose T1ρ dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T1ρ mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T1ρ mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals. Methods A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T1ρ quantification accuracy. The in vivo validation of T1ρ mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal. Results The Bloch simulation-based sampling shows considerably higher image quality as well as improved T1ρ quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of − 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T1ρ mapping. The mean T1ρ in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T1ρ dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz. Conclusion This new and fast T1ρ quantification technique enables high-resolution myocardial T1ρ mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.
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.
Introduction Over the past decade, CMRI has become the method of choice for characterizing fibrotic scars. Native T1ρ mapping offers an alternative to conventional T1 and T2 quantification techniques due to its high sensitivity to low-frequency processes. In addition, there is the possibility of T1ρ dispersion imaging, which could be used as a sensitive biomarker for assessing myocardial fibrosis [1]. However, due to a very long measurement time, T1ρ dispersion quantification in myocardium can hardly be done in the limited time of a small animal study. In this work we present a concept for rapid T1ρ dispersion quantification based on the new approach of synthetic dispersion reconstruction (SynDR). Theory A T1ρ map is calculated by measuring Nt T1ρ weighted images using different spin lock (SL) times. T1ρ dispersion quantification requires Nf T1ρ maps with different SL amplitudes. Hence the measurement time is very time consuming, because it requires the acquisition of Nt*Nf images (full mapping). With our new approach (SynDR), only a single T1ρ reference map and a series of dispersion weighted images need to be acquired. The T1ρ dispersion can be reconstructed by synthetically generated maps, whereby each map is calculated from the reference map and the dispersion weighted images, only requiring Nt+Nf images. Methods All measurements were performed on a 7T small animal scanner. The method was based on an optional cartesian/radial gradient echo sequence using large flip angles (45°) and an optimized readout sorting. The quantification accuracy of SynDR was compared with full mapping measurements in a phantom experiment and validated in vivo on mice. The synthetic T1ρ maps were used to perform a dispersion analysis in myocardium. Results The comparison between SynDR and the full mapping reference in phantoms showed a very high quantification accuracy with a mean/maximum deviation of 1.1% and 1.7%. Fig. 1 shows synthetic T1ρ maps (a) in healthy mice and the obtained dispersion map (b) using SynDR. In the dispersion analysis (c) a T1ρ slope of 5.6±1.5ms/kHz was obtained for myocardium. Here an acceleration factor of 4 could be realized in comparison to full mapping. In further measurements, an acceleration of 7.4 could be reached using a radial readout with KWIC filter view sharing. Discussion In this work, a novel T1ρ dispersion imaging method was presented that far exceeds the speed of conventional full mapping methods. The acceleration is based on avoiding unnecessary measurements of T1ρ weighted images through more efficient mathematical modeling. Further acceleration could be achieved using an optimized radial data acquisition. The method shows good image quality and high quantification accuracy both in phantom and in vivo. Based on the promising results, further studies in mice are planned to investigate the dispersion character of healthy and diseased tissues. Reference [1] Yin Q et al. Magn Reson Imaging. 2017 Oct; 42:69–73. SynDR method and T1ρ dispersion analysis Funding Acknowledgement Type of funding source: Public grant(s) – National budget only. Main funding source(s): BRD, Bundesministerium für Bildung und Forschung
Contrary to the basic principle of CEST, the RACETE technique allows for the direct detection of positive chemical exchange contrast. This method, which was previously demonstrated only under ultra-high field conditions at 7T-17.5T, has now successfully been implemented on a clinical 3T scanner in initial phantom experiments. Furthermore, we present a novel dual-contrast RACETE-technique for simultaneous imaging of the positive RACETE and the negative CEST contrast.
Spin-lock based absorption of magnetic oscillations offers potential for direct detection of electrical neuronal activity. We propose a novel versatile validation and calibration technique which paves the way for emulation and quantification of biomagnetic fields. Using ultra-weak gradient waveforms, the method mimics brain activity and thus projects artificial fields onto the tissue under investigation. The method applicable for sequence validation or signal calibration was tested in phantom and in vivo experiments with the built-in gradient system providing sinusoidal field modulations down to 1 nT. It proved to be reliable and reproducible and hence can potentially enable quantification of biomagnetic fields.
Spin-lock based functional magnetic resonance imaging (fMRI) has the potential for direct spatially-resolved detection of neuronal activity and thus may represent an important step for basic research in neuroscience. In this work, the corresponding fundamental effect of Rotary EXcitation (REX) is investigated both in simulations as well as in phantom and in vivo experiments. An empirical law for predicting optimal spin-lock pulse durations for maximum magnetic field sensitivity was found. Experimental conditions were established that allow robust detection of ultra-weak magnetic field oscillations with simultaneous compensation of static field inhomogeneities. Furthermore, this work presents a novel concept for the emulation of brain activity utilizing the built-in MRI gradient system, which allows REX sequences to be validated in vivo under controlled and reproducible conditions. Via transmission of Rotary EXcitation (tREX), we successfully detected magnetic field oscillations in the lower nano-Tesla range in brain tissue. Moreover, tREX paves the way for the quantification of biomagnetic fields.
Resonant absorption during spin-lock preparation can be used to measure tiny oscillating magnetic fields acting as direct evidence of electrical neuronal activity. Different spin-locking techniques were compared with respect to their sensitivity in magnetic field detection. As a specialty, the oscillating magnetic fields were generated by the built-in gradient system in an offcenter slice. The spin-lock time was identified as the crucial parameter for the performance of NEMO (neuro-electro-magnetic-oscillations) detection, since minima and maxima in the signal amplitude emerged in phantom and in vivo experiments. Affirmative, the experimental results show an excellent agreement with simulation results.
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