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Register a new userUltrashort Echo Time Magnetic Resonance Fingerprinting (UTE-MRF) for Simultaneous Quantification of Long and Ultrashort T2 Tissues
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Purpose: To demonstrate an ultrashort echo time magnetic resonance fingerprinting (UTE-MRF) method that can simultaneously quantify tissue relaxometries for muscle and bone in musculoskeletal systems and tissue components in brain and therefore can synthesize pseudo-CT images. Methods: A FISP-MRF sequence with half pulse excitation and half spoke radial acquisition was designed to sample fast T2 decay signals. Sinusoidal echo time (TE) pattern was applied to enhance MRF sensitivity for tissues with short and ultrashort T2 values. The performance of UTE-MRF was evaluated via simulations, phantoms, and in vivo experiments. Results: A minimal TE of 0.05 ms was achieved in UTE-MRF. Simulations indicated that extension of TE sampling increased T2 quantification accuracy in cortical bone and tendon, and had little impact on long T2 muscle quantifications. For a rubber phantom, an average T1/T2 of 162/1.07 ms from UTE-MRF were compared well with gold standard T2 of 190 ms from IR-UTE and T2* of 1.03 ms from UTE sequence. For a long T2 agarose phantom, the linear regression slope between UTE-MRF and gold standard was 1.07 (R2=0.991) for T1 and 1.04 (R2=0.994) for T2. In vivo experiments showed the detection of cortical bone and Achilles tendon, where the averaged T2 was respectively 1.0 ms and 15 ms. Scalp images were in good agreement with CT. Conclusion: UTE-MRF with sinusoidal TE variations shows its capability to produce pseudo-CT images and simultaneously output T1, T2, proton density, and B0 maps for tissues with long T2 and short/ultrashort T2 in the brain and musculoskeletal system.
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Purpose: To develop a clinical chemical exchange saturation transfer magnetic resonance fingerprinting (CEST-MRF) pulse sequence and reconstruction method. Methods: The CEST-MRF pulse sequence was modified to conform to hardware limits on clinical scanners while keeping scan time $leqslant$ 2 minutes. The measured data was reconstructed using a deep reconstruction network (DRONE) to yield the water relaxation and chemical exchange parameters. The feasibility of the 6 parameter DRONE reconstruction was tested in simulations in a digital brain phantom. A healthy subject was scanned with the CEST-MRF sequence and a conventional MRF sequence for comparison. The reproducibility was assessed via test-retest experiments and the concordance correlation coefficient (CCC) calculated for white matter (WM) and grey matter (GM). The clinical utility of CEST-MRF was demonstrated in a brain metastasis patient in comparison to standard clinical imaging sequences. The tumor was segmented into edema, solid core and necrotic core regions and the CEST-MRF values compared to the contra-lateral side. Results: The 6 parameter DRONE reconstruction of the digital phantom yielded a mean absolute error of $leqslant$ 6% for all parameters. The CEST-MRF parameters were in good agreement with those from a conventional MRF sequence and previous studies in the literature. The mean CCC for all 6 parameters was 0.79$pm$0.02 in WM and 0.63$pm$0.03 in GM. The CEST-MRF values in nearly all tumor regions were significantly different (p=0.001) from each other and the contra-lateral side. Conclusion: The clinical CEST-MRF sequence provides a method for fast simultaneous quantification of multiple tissue parameters in pathologies.
Purpose: To develop a fast magnetic resonance fingerprinting (MRF) method for quantitative chemical exchange saturation transfer (CEST) imaging. Methods: We implemented a CEST-MRF method to quantify the chemical exchange rate and volume fraction of the N${alpha}$-amine protons of L-arginine (L-Arg) phantoms and the amide and semi-solid exchangeable protons of in vivo rat brain tissue. L-Arg phantoms were made with different concentrations (25-100 mM) and pH (pH 4-6). The MRF acquisition schedule varied the saturation power randomly for 30 iterations (phantom: 0-6 ${mu}$T; in vivo: 0-4 ${mu}$T) with a total acquisition time of <=2 minutes. The signal trajectories were pattern-matched to a large dictionary of signal trajectories simulated using the Bloch-McConnell equations for different combinations of exchange rate, exchangeable proton volume fraction, and water T1 and T2* relaxation times. Results: The chemical exchange rates of the N${alpha}$-amine protons of L-Arg were significantly (p<0.0001) correlated with the rates measured with the Quantitation of Exchange using Saturation Power method. Similarly, the L-Arg concentrations determined using MRF were significantly (p<0.0001) correlated with the known concentrations. The pH dependence of the exchange rate was well fit (R2=0.9186) by a base catalyzed exchange model. The amide proton exchange rate measured in rat brain cortex (36.3+-12.9 Hz) was in good agreement with that measured previously with the Water Exchange spectroscopy method (28.6+-7.4 Hz). The semi-solid proton volume fraction was elevated in white (11.2+-1.7%) compared to gray (7.6+-1.8%) matter brain regions in agreement with previous magnetization transfer studies. Conclusion: CEST-MRF provides a method for fast, quantitative CEST imaging.
Magnetic resonance fingerprinting (MRF) is one novel fast quantitative imaging framework for simultaneous quantification of multiple parameters with pseudo-randomized acquisition patterns. The accuracy of the resulting multi-parameters is very important for clinical applications. In this paper, we derived signal evolutions from the anomalous relaxation using a fractional calculus. More specifically, we utilized time-fractional order extension of the Bloch equations to generate dictionary to provide more complex system descriptions for MRF applications. The representative results of phantom experiments demonstrated the good accuracy performance when applying the time-fractional order Bloch equations to generate dictionary entries in the MRF framework. The utility of the proposed method is also validated by in-vivo study.
Magnetic Resonance Imaging (MRI) of hard biological tissues is challenging due to the fleeting lifetime and low strength of their response to resonant stimuli, especially at low magnetic fields. Consequently, the impact of MRI on some medical applications, such as dentistry, continues to be limited. Here, we present three-dimensional reconstructions of ex-vivo human teeth, as well as a rabbit head and part of a cow femur, all obtained at a field strength of only 260 mT. These images are the first featuring soft and hard tissues simultaneously at sub-Tesla fields, and they have been acquired in a home-made, special-purpose, pre-medical MRI scanner designed with the goal of demonstrating dental imaging at low field settings. We encode spatial information with two variations of zero-echo time (ZTE) pulse sequences: Pointwise-Encoding Time reduction with Radial Acquisition (PETRA) and a new sequence we have called Double Radial Non-Stop Spin Echo (DRaNSSE), which we find to perform better than the former. For image reconstruction we employ Algebraic Reconstruction Techniques (ART) as well as standard Fourier methods. A noise analysis of the resulting images shows that ART reconstructions exhibit a higher signal to noise ratio with a more homogeneous noise distribution.
Spin-echo functional MRI (SE-fMRI) has the potential to improve spatial specificity when compared to gradient-echo fMRI. However, high spatiotemporal resolution SE-fMRI with large slice-coverage is challenging as SE-fMRI requires a long echo time (TE) to generate blood oxygenation level-dependent (BOLD) contrast, leading to long repetition times (TR). The aim of this work is to develop an acquisition method that enhances the slice-coverage of SE-fMRI at high spatiotemporal resolution. An acquisition scheme was developed entitled Multisection Excitation by Simultaneous Spin-echo Interleaving (MESSI) with complex-encoded generalized SLIce Dithered Enhanced Resolution (cgSlider). MESSI utilizes the dead-time during the long TE by interleaving the excitation and readout of two slices to enable 2x slice-acceleration, while cgSlider utilizes the stable temporal background phase in SE-fMRI to encode and decode two adjacent slices simultaneously with a phase-constrained reconstruction method. The proposed cgSlider-MESSI was also combined with Simultaneous Multi-Slice (SMS) to achieve further slice-acceleration. This combined approach was used to achieve 1.5mm isotropic whole-brain SE-fMRI with a temporal resolution of 1.5s and was evaluated using sensory stimulation and breath-hold tasks at 3T. Compared to conventional SE-SMS, cgSlider-MESSI-SMS provides four-fold increase in slice-coverage for the same TR, with comparable temporal signal-to-noise ratio. Corresponding fMRI activation from cgSlider-MESSI-SMS for both fMRI tasks were consistent with those from conventional SE-SMS. Overall, cgSlider-MESSI-SMS achieved a 32x encoding-acceleration by combining RinplanexMBxcgSliderxMESSI=4x2x2x2. High-quality, high-resolution whole-brain SE-fMRI was acquired at a short TR using cgSlider-MESSI-SMS.
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