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Register a new userEnhanced Hyperpolarized Chemical Shift Imaging Based on a priori Segmented Information
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Purpose: To develop an approach for improving the resolution and sensitivity of hyperpolarized 13C MRSI based on a priori anatomical information derived from featured, water-based 1H images. Methods: A reconstruction algorithm exploiting 1H MRI for the redefinition of the 13C MRSI anatomies was developed, based on a modification of the Spectroscopy with Linear Algebraic Modeling (SLAM) principle. To enhance 13C spatial resolution and reduce spillover effects without compromising SNR, this model was extended by endowing it with a search allowing smooth variations in the 13C MR intensity within the targeted regions of interest. Results: Experiments were performed in vitro on enzymatic solutions and in vivo on rodents, based on the administration of 13C-enriched hyperpolarized pyruvate and urea. The spectral images reconstructed for these substrates and from metabolic products based on predefined 1H anatomical compartments using the new algorithm, compared favorably with those arising from conventional Fourier-based analyses of the same data. The new approach also delivered reliable kinetic 13C results, for the kind of processes and timescales usually targeted by hyperpolarized MRSI. Conclusions: A simple yet flexible strategy is introduced to boost the sensitivity and resolution provided by hyperpolarized 13C MRSI, based on readily available 1H MR information.
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Purpose: Hyperpolarized imaging experiments have conflicting requirements of high spatial, temporal, and spectral resolution. Spectral-Spatial RF excitation has been shown to form an attractive magnetization-efficient method for hyperpolarized imaging, but the optimum readout strategy is not yet known. Methods: In this work we propose a novel 3D hybrid-shot spiral sequence which features two constant density regions that permit the retrospective reconstruction of either high spatial or high temporal resolution images post hoc, (adaptive spatiotemporal imaging) allowing greater flexibility in acquisition and reconstruction. Results: We have implemented this sequence, both via simulation and on a pre-clinical scanner, to demonstrate its feasibility, in both a 1H phantom and with hyperpolarized 13C pyruvate in vivo. Conclusion: This sequence forms an attractive method for acquiring hyperpolarized imaging datasets, providing adaptive spatiotemporal imaging to ameliorate the conflict of spatial and temporal resolution, with significant potential for clinical translation.
Nuclear magnetic resonance (NMR) diffusion measurements are widely used to derive parameters indirectly related to the microstructure of biological tissues and porous media. However, a direct imaging of cell or pore shapes and sizes would be of high interest. For a long time, determining pore shapes by NMR diffusion acquisitions seemed impossible, because the necessary phase information could not be preserved. Here we demonstrate experimentally using the measurement technique which we have recently proposed theoretically that the shape of arbitrary closed pores can be imaged by diffusion acquisitions, which yield the phase information. For this purpose, we use hyperpolarized xenon gas in well-defined geometries. The signal can be collected from the whole sample which mainly eliminates the problem of vanishing signal at increasing resolution of conventional NMR imaging. This could be used to non-invasively gain structural information inaccessible so far such as pore or cell shapes, cell density or axon integrity.
Purpose: Investigation of the feasibility of the R2* mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio. Theory and Methods: The improvement of the performance of state of the art MRI relaxometry algorithms is challenging because of a non-negligible bias and still unresolved numerical instabilities. Here, R2* mapping reconstructions, including complex-fitting with multi-spectral fat-correction by using single-decay (1D) and double-decay (2D) formulation, are studied in order to identify optimal configuration parameters and minimize numerical artifacts. The effects of echo number, echo spacing, and fat/water relaxation model are evaluated through simulated and in-vivo data. We also explore the stability of such models by analyzing the impact of high percentage of fat infiltrations and local transverse relaxation differences among biological species. Results: The main limits of the MRI relaxometry are the presence of bias and the occurrence of artifacts which affect its accuracy. Chemical-shift complex reconstructions R2*-corrected with 1D formulation exhibit a large bias in presence of a significant difference in the relaxation rates of fat and water and with fat concentration larger than 30%. We find that for fat-dominated tissues or in patients affected by iron overload, MRI reconstructions accounting for multi-exponential relaxation time provide accurate R2* measurements and are less prone to numerical artifacts. Conclusions: Complex fitting 2D formulation outperforms the conventional 1D approximation in various diagnostic scenarios. Although it still lacks of numerical stability which requires model enhancement and support from spectroscopy, it offers promising perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of neuromuscular disorders.
Purpose: The balanced steady-state free precession sequence has been previously explored to improve the efficient use of non-recoverable hyperpolarized $^{13}$C magnetization, but suffers from poor spectral selectivity and long acquisition time. The purpose of this study was to develop a novel metabolite-specific 3D bSSFP (MS-3DSSFP) sequence with stack-of-spiral readouts for improved lactate imaging in hyperpolarized [1-$^{13}$C]pyruvate studies on a clinical 3T scanner. Methods: Simulations were performed to evaluate the spectral response of the MS-3DSSFP sequence. Thermal $^{13}$C phantom experiments were performed to validate the MS-3DSSFP sequence. In vivo hyperpolarized [1-$^{13}$C]pyruvate studies were performed to compare the MS-3DSSFP sequence with metabolite specific gradient echo (MS-GRE) sequences for lactate imaging. Results: Simulations, phantom and in vivo studies demonstrate that the MS-3DSSFP sequence achieved spectrally selective excitation on lactate while minimally perturbing other metabolites. Compared with MS-GRE sequences, the MS-3DSSFP sequence showed approximately a 2.5-fold SNR improvement for lactate imaging in rat kidneys, prostate tumors in a mouse model and human kidneys. Conclusions: Improved lactate imaging using the MS-3DSSFP sequence in hyperpolarized [1-$^{13}$C]pyruvate studies was demonstrated in animals and humans. The MS-3DSSFP sequence could be applied for other clinical applications such as in the brain or adapted for imaging other metabolites such as pyruvate and bicarbonate.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to quantify perfusion and vascular permeability. In most cases a bolus arrival time (BAT) delay exists between the arterial input function (AIF) and the contrast agent arrival in the tissue of interest which needs to be estimated. Existing methods for BAT estimation are tailored to tissue concentration curves which have a fast upslope to the peak as frequently observed in patient data. However, they may give poor results for curves that do not have this characteristic shape such as tissue concentration curves of small animals. In this paper, we propose a novel method for BAT estimation of signals that do not have a fast upslope to their peak. The model is based on splines which are able to adapt to a large variety of concentration curves. Furthermore, the method estimates BATs on a continuous time scale. All relevant model parameters are automatically determined by generalized cross validation. We use simulated concentration curves of small animal and patient settings to assess the accuracy and robustness of our approach. The proposed method outperforms a state-of-the-art method for small animal data and it gives competitive results for patient data. Finally, it is tested on in vivo acquired rat data where accuracy of BAT estimation was also improved upon the state-of-the-art method. The results indicate that the proposed method is suitable for accurate BAT estimation of DCE-MRI data, especially for small animals.
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