Low-rank reconstruction for simultaneous double half-echo 23Na and undersampled 23Na multi-quantum coherences MRI.

PURPOSE: To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low-rank reconstruction frameworks. THEORY AND METHODS: The Double Half-Echo technique enables short echo time Cartesian 23Na MRI and acquires two k-space halves, reconstructed by a low-rank coupling constraint. Additionally, three-dimensional (3D) 23Na Multi-Quantum Coherences (MQC) MRI requires multi-echo sampling paired with phase-cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k-Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five-dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal-to-noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. RESULTS: The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from 8 × 8 × 15 $$ 8\times 8\times 15 $$ mm3 to 8 × 8 × 8 $$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from 2 × 31 $$ 2\times 31 $$ min to 2 × 23 $$ 2\times 23 $$ min. CONCLUSION: The proposed sequence, coupled with low-rank reconstructions, provides an efficient framework for comprehensive whole-brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low-rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution.

Feasibility of undersampled spiral trajectories in MREPT for fast conductivity imaging.

PURPOSE: To investigate spiral-based imaging including trajectories with undersampling as a fast and robust alternative for phase-based magnetic resonance electrical properties tomography (MREPT) techniques. METHODS: Spiral trajectories with various undersampling ratios were prescribed to acquire images from an experimental phantom and a healthy volunteer at 3T. The non-Cartesian acquisitions were reconstructed using SPIRiT, and conductivity maps were derived using phase-based cr-MREPT. The resulting maps were compared between different sampling trajectories. Additionally, a conductivity map was obtained using a Cartesian balanced SSFP acquisition from the volunteer to comparatively demonstrate the robustness of the proposed method. RESULTS: The phantom and volunteer results illustrate the benefits of the spiral acquisitions. Specifically, undersampled spiral acquisitions display improved robustness against field inhomogeneity artifacts and lowered SD values with shortened readout times. Furthermore, average of conductivity values measured for the cerebrospinal fluid with the spiral acquisitions were 1.703 S/m, indicating a close agreement with the theoretical values of 1.794 S/m. CONCLUSION: A spiral-based acquisition framework for conductivity imaging with and without undersampling is presented. Overall, spiral-based acquisitions improved robustness against field inhomogeneity artifacts, while achieving whole head coverage with multiple averages in less than a minute.

Functional lung imaging of 2-year-old children after congenital diaphragmatic hernia repair using dynamic mode decomposition MRI.

OBJECTIVES: To investigate the feasibility of non-contrast-enhanced functional lung imaging in 2-year-old children after congenital diaphragmatic hernia (CDH) repair. METHODS: Fifteen patients after CDH repair were examined using non-contrast-enhanced dynamic magnetic resonance imaging (MRI). For imaging two protocols were used during free-breathing: Protocol A with high temporal resolution and Protocol B with high spatial resolution. The dynamic images were then analysed through a recently developed post-processing method called dynamic mode decomposition (DMD) to obtain ventilation and perfusion maps. The ventilation ratios (VRatio) and perfusion ratios (QRatio) of ipsilateral to contralateral lung were compared to evaluate functional differences. Lastly, DMD MRI-based perfusion results were compared with perfusion parameters obtained using dynamic contrast-enhanced (DCE) MRI to assess agreement between methods. RESULTS: Both imaging protocols successfully generated pulmonary ventilation (V) and perfusion (Q) maps in all patients. Overall, the VRatio and QRatio values were 0.84 ± 0.19 and 0.70 ± 0.24 for Protocol A, and 0.88 ± 0.18 and 0.72 ± 0.23 for Protocol B, indicating reduced ventilation ([Formula: see text]) and perfusion ([Formula: see text]) on the ipsilateral side. Moreover, there is a very strong positive correlation ([Formula: see text]) and close agreement between DMD MRI-based perfusion values and DCE MRI-based perfusion parameters. CONCLUSIONS: DMD MRI can obtain pulmonary functional information in 2-year-old CDH patients. The results obtained with DMD MRI correlate with DCE MRI, without the need for ionising radiation or exposure to contrast agents. While further studies with larger cohorts are warranted, DMD MRI is a promising option for functional lung imaging in CDH patients. CLINICAL RELEVANCE STATEMENT: We demonstrate that pulmonary ventilation and perfusion information can be obtained in 2-year-old patients after CDH repair, without the need for ionising radiation or contrast agents by utilising non-contrast-enhanced MRI acquisitions together with dynamic mode decomposition analysis. KEY POINTS: • Non-contrast-enhanced functional MR imaging is a promising option for functional lung imaging in 2-year-old children after congenital diaphragmatic hernia. • DMD MRI can generate pulmonary ventilation and perfusion maps from free-breathing dynamic acquisitions without the need for ionising radiation or contrast agents. • Lung perfusion parameters obtained with DMD MRI correlate with perfusion parameters obtained using dynamic contrast-enhanced MRI.

Dynamic mode decomposition of dynamic MRI for assessment of pulmonary ventilation and perfusion.

PURPOSE: To introduce dynamic mode decomposition (DMD) as a robust alternative for the assessment of pulmonary functional information from dynamic non-contrast-enhanced acquisitions. METHODS: Pulmonary fractional ventilation and normalized perfusion maps were obtained using DMD from simulated phantoms as well as in vivo dynamic acquisitions of healthy volunteers at 1.5T. The performance of DMD was compared with conventional Fourier decomposition (FD) and matrix pencil (MP) methods in estimating functional map values. The proposed method was evaluated based on estimated signal amplitude in functional maps across varying number of measurements. RESULTS: Quantitative assessments performed on phantoms and in vivo measurements indicate that DMD is capable of successfully obtaining pulmonary functional maps. Specifically, compared to FD and MP methods, DMD is able to reduce variations in estimated amplitudes across different number of measurements. This improvement is evident in the fractional ventilation and normalized perfusion maps obtain from phantom simulations with frequency variations and noise, as well as in the maps obtained from in vivo measurements. CONCLUSIONS: A robust method for accurately estimating pulmonary ventilation and perfusion related signal changes in dynamic acquisitions is presented. The proposed method uses DMD to obtain functional maps reliably, while reducing amplitude variations caused by differences in number of measurements.

Phase-cycled balanced SSFP imaging for non-contrast-enhanced functional lung imaging.

PURPOSE: To introduce phase-cycled balanced SSFP (bSSFP) acquisition as an alternative in Fourier decomposition MRI for improved robustness against field inhomogeneities. METHODS: Series 2D dynamic lung images were acquired in 5 healthy volunteers at 1.5 T and 3 T using bSSFP sequence with multiple RF phase increments and compared with conventional single RF phase increment acquisitions. The approach was evaluated based on functional map homogeneity analysis, while ensuring image and functional map quality by means of SNR and contrast-to-noise ratio analyses. RESULTS: At both field strengths, functional maps obtained with phase-cycled acquisitions displayed improved robustness against local signal losses compared with single-phase acquisitions. The coefficient of variation (mean ± SD, across volunteers) measured in the ventilation maps resulted in 29.7 ± 2.6 at 1.5 T and 37.5 ± 3.1 at 3 T for phase-cycled acquisitions, compared with 39.9 ± 5.2 at 1.5 T and 49.5 ± 3.7 at 3 T for single-phase acquisitions, indicating a significant improvement ( p<0.05$$ p<0.05 $$ ) in ventilation map homogeneity. CONCLUSIONS: Phase-cycled bSSFP acquisitions improve robustness against field inhomogeneity artifacts and significantly improve ventilation map homogeneity at both field strengths. As such, phase-cycled bSSFP may serve as a robust alternative in lung function assessments.

Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study.

PURPOSE: The oxygen extraction fraction (OEF) is an important biomarker for tissue-viability. MRI enables noninvasive estimation of the OEF based on the blood-oxygenation-level-dependent (BOLD) effect. Quantitative OEF-mapping is commonly applied using least-squares regression (LSR) to an analytical tissue model. However, the LSR method has not yet become clinically established due to the necessity for long acquisition times. Artificial neural networks (ANNs) recently have received increasing interest for robust curve-fitting and might pose an alternative to the conventional LSR method for reduced acquisition times. This study presents in vivo OEF mapping results using the conventional LSR and the proposed ANN method. METHODS: In vivo data of five healthy volunteers and one patient with a primary brain tumor were acquired at 3T using a gradient-echo sampled spin-echo (GESSE) sequence. The ANN was trained with simulated BOLD data. RESULTS: In healthy subjects, the mean OEF was 36 ± 2% (LSR) and 40 ± 1% (ANN). The OEF variance within subjects was reduced from 8% to 6% using the ANN method. In the patient, both methods revealed a distinct OEF hotspot in the tumor area, whereas ANN showed less apparent artifacts in surrounding tissue. CONCLUSION: In clinical scan times, the ANN analysis enables OEF mapping with reduced variance, which could facilitate its integration into clinical protocols. Magn Reson Med 79:890-899, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Diffusion parameter mapping with the combined intravoxel incoherent motion and kurtosis model using artificial neural networks at 3 T.

Artificial neural networks (ANNs) were used for voxel-wise parameter estimation with the combined intravoxel incoherent motion (IVIM) and kurtosis model facilitating robust diffusion parameter mapping in the human brain. The proposed ANN approach was compared with conventional least-squares regression (LSR) and state-of-the-art multi-step fitting (LSR-MS) in Monte-Carlo simulations and in vivo in terms of estimation accuracy and precision, number of outliers and sensitivity in the distinction between grey (GM) and white (WM) matter. Both the proposed ANN approach and LSR-MS yielded visually increased parameter map quality. Estimations of all parameters (perfusion fraction f, diffusion coefficient D, pseudo-diffusion coefficient D*, kurtosis K) were in good agreement with the literature using ANN, whereas LSR-MS resulted in D* overestimation and LSR yielded increased values for f and D*, as well as decreased values for K. Using ANN, outliers were reduced for the parameters f (ANN, 1%; LSR-MS, 19%; LSR, 8%), D* (ANN, 21%; LSR-MS, 25%; LSR, 23%) and K (ANN, 0%; LSR-MS, 0%; LSR, 15%). Moreover, ANN enabled significant distinction between GM and WM based on all parameters, whereas LSR facilitated this distinction only based on D and LSR-MS on f, D and K. Overall, the proposed ANN approach was found to be superior to conventional LSR, posing a powerful alternative to the state-of-the-art method LSR-MS with several advantages in the estimation of IVIM-kurtosis parameters, which might facilitate increased applicability of enhanced diffusion models at clinical scan times.

Gaussian signal relaxation around spin echoes: Implications for precise reversible transverse relaxation quantification of pulmonary tissue at 1.5 and 3 Tesla.

PURPOSE: To characterize the reversible transverse relaxation in pulmonary tissue and to study the benefit of a quadratic exponential (Gaussian) model over the commonly used linear exponential model for increased quantification precision. METHODS: A point-resolved spectroscopy sequence was used for comprehensive sampling of the relaxation around spin echoes. Measurements were performed in an ex vivo tissue sample and in healthy volunteers at 1.5 Tesla (T) and 3 T. The goodness of fit using χred2 and the precision of the fitted relaxation time by means of its confidence interval were compared between the two relaxation models. RESULTS: The Gaussian model provides enhanced descriptions of pulmonary relaxation with lower χred2 by average factors of 4 ex vivo and 3 in volunteers. The Gaussian model indicates higher sensitivity to tissue structure alteration with increased precision of reversible transverse relaxation time measurements also by average factors of 4 ex vivo and 3 in volunteers. The mean relaxation times of the Gaussian model in volunteers are T2,G' = (1.97 ± 0.27) msec at 1.5 T and T2,G' = (0.83 ± 0.21) msec at 3 T. CONCLUSION: Pulmonary signal relaxation was found to be accurately modeled as Gaussian, providing a potential biomarker T2,G' with high sensitivity. Magn Reson Med 77:1938-1945, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Magnetic resonance fingerprinting using echo-planar imaging: Joint quantification of T1 and T2∗ relaxation times.

PURPOSE: To develop an implementation of the magnetic resonance fingerprinting (MRF) paradigm for quantitative imaging using echo-planar imaging (EPI) for simultaneous assessment of T1 and T2∗. METHODS: The proposed MRF method (MRF-EPI) is based on the acquisition of 160 gradient-spoiled EPI images with rapid, parallel-imaging accelerated, Cartesian readout and a measurement time of 10 s per slice. Contrast variation is induced using an initial inversion pulse, and varying the flip angles, echo times, and repetition times throughout the sequence. Joint quantification of T1 and T2∗ is performed using dictionary matching with integrated B1+ correction. The quantification accuracy of the method was validated in phantom scans and in vivo in 6 healthy subjects. RESULTS: Joint T1 and T2∗ parameter maps acquired with MRF-EPI in phantoms are in good agreement with reference measurements, showing deviations under 5% and 4% for T1 and T2∗, respectively. In vivo baseline images were visually free of artifacts. In vivo relaxation times are in good agreement with gold-standard techniques (deviation T1 : 4 ± 2%, T2∗: 4 ± 5%). The visual quality was comparable to the in vivo gold standard, despite substantially shortened scan times. CONCLUSION: The proposed MRF-EPI method provides fast and accurate T1 and T2∗ quantification. This approach offers a rapid supplement to the non-Cartesian MRF portfolio, with potentially increased usability and robustness. Magn Reson Med 78:1724-1733, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Optimized protocol for high resolution functional magnetic resonance imaging at 3T using single-shot echo planar imaging.

BACKGROUND: To translate highly accelerated EPI-fMRI protocols as commonly used at ultra-high field strengths to clinical 3T settings. NEW METHOD: EPI protocols with increasing matrix sizes and parallel imaging (PI) factors were tested in two separate fMRI studies, a simple motor-task and a complex motivation-task experiment with focus on the sensorimotor cortex (SMC) and the nucleus accumbens (NAcc), respectively. RESULTS: By increasing the matrix size and the PI-factor simultaneously, BOLD-sensitivity in terms of maximal t-values and numbers of activated clusters was uncompromised in single individuals in both fMRI experiments. In the SMC, the multi-subject analysis revealed an increase of 66% of the maximal t-value whereby the number of activated clusters was increased by a factor of 3.3 when the matrix size (PI-factor) was increased from 96×96 (R=2) to 192×192 (R=4). In the NAcc, the number of activated clusters increased from 5 to 7 whereby the maximal t-value remained unaffected when the matrix size (PI-factor) was increased from 96×96 (R=2) to 160×160 (R=3). COMPARISON WITH EXISTING METHOD: Using the proposed high-resolution EPI protocol, spatial blurring was clearly reduced. Further, BOLD sensitivity was clearly improved in multi-subject analyses and remained unaffected in single individuals compared to using the standard protocols. CONCLUSIONS: Conventionally used matrix sizes (PI-factors) might be non-optimal for some applications sacrificing BOLD spatial specificity. We recommend using the proposed high-resolution protocols applicable in detecting robust BOLD activation in fMRI.

Memory stabilization with targeted reactivation during human slow-wave sleep.

It is believed that neural representations of recent experiences become reactivated during sleep, and that this process serves to stabilize associated memories in long-term memory. Here, we initiated this reactivation process for specific memories during slow-wave sleep. Participants studied 50 object-location associations with object-related sounds presented concurrently. For half of the associations, the related sounds were re-presented during subsequent slow-wave sleep while participants underwent functional MRI. Compared with control sounds, related sounds were associated with increased activation of right parahippocampal cortex. Postsleep memory accuracy was positively correlated with sound-related activation during sleep in various brain regions, including the thalamus, bilateral medial temporal lobe, and cerebellum. In addition, postsleep memory accuracy was also positively correlated with pre- to postsleep changes in parahippocampal-medial prefrontal connectivity during retrieval of reactivated associations. Our results suggest that the brain is differentially activated by studied and unstudied sounds during deep sleep and that the thalamus and medial temporal lobe are involved in establishing the mnemonic consequences of externally triggered reactivation of associative memories.

Sinusoidal echo-planar imaging with parallel acquisition technique for reduced acoustic noise in auditory fMRI.

PURPOSE: To extend the parameter restrictions of a silent echo-planar imaging (sEPI) sequence using sinusoidal readout (RO) gradients, in particular with increased spatial resolution. The sound pressure level (SPL) of the most feasible configurations is compared to conventional EPI having trapezoidal RO gradients. MATERIALS AND METHODS: We enhanced the sEPI sequence by integrating a parallel acquisition technique (PAT) on a 3 T magnetic resonance imaging (MRI) system. The SPL was measured for matrix sizes of 64 × 64 and 128 × 128 pixels, without and with PAT (R = 2). The signal-to-noise ratio (SNR) was examined for both sinusoidal and trapezoidal RO gradients. RESULTS: Compared to EPI PAT, the SPL could be reduced by up to 11.1 dB and 5.1 dB for matrix sizes of 64 × 64 and 128 × 128 pixels, respectively. The SNR of sinusoidal RO gradients is lower by a factor of 0.96 on average compared to trapezoidal RO gradients. CONCLUSION: The sEPI PAT sequence allows for 1) increased resolution, 2) expanded RO frequency range toward lower frequencies, which is in general beneficial for SPL, or 3) shortened TE, TR, and RO train length. At the same time, it generates lower SPL compared to conventional EPI for a wide range of RO frequencies while having the same imaging parameters.