Highly accelerated EPI with wave encoding and multi-shot simultaneous multislice imaging

PURPOSE

To introduce wave-encoded acquisition and reconstruction techniques for highly accelerated EPI with reduced g-factor penalty and image artifacts.

THEORY AND METHODS

Wave-EPI involves application of sinusoidal gradients during the EPI readout, which spreads the aliasing in all spatial directions, thereby taking better advantage of 3D coil sensitivity profiles. The amount of voxel spreading that can be achieved by the wave gradients during the short EPI readout period is constrained by the slew rate of the gradient coils and peripheral nerve stimulation monitor. We propose to use a "half-cycle" sinusoidal gradient to increase the amount of voxel spreading that can be achieved while respecting the slew and stimulation constraints. Extending wave-EPI to multi-shot acquisition minimizes geometric distortion and voxel blurring at high in-plane resolutions, while structured low-rank regularization mitigates shot-to-shot phase variations. To address gradient imperfections, we propose to use different point spread functions for the k-space lines with positive and negative polarities, which are calibrated with a FLEET-based reference scan.

RESULTS

Wave-EPI enabled whole-brain single-shot gradient-echo (GE) and multi-shot spin-echo (SE) EPI acquisitions at high acceleration factors at 3T and was combined with g-Slider encoding to boost the SNR level in 1 mm isotropic diffusion imaging. Relative to blipped-CAIPI, wave-EPI reduced average and maximum g-factors by up to 1.21- and 1.37-fold at R_in  × R_sms  = 3 × 3, respectively.

CONCLUSION

Wave-EPI allows highly accelerated single- and multi-shot EPI with reduced g-factor and artifacts and may facilitate clinical and neuroscientific applications of EPI by improving the spatial and temporal resolution in functional and diffusion imaging.

Free-breathing motion-informed locally low-rank quantitative 3D myocardial perfusion imaging

Purpose

To propose respiratory motion‐informed locally low‐rank reconstruction (MI‐LLR) for robust free‐breathing single‐bolus quantitative 3D myocardial perfusion CMR imaging. Simulation and in‐vivo results are compared to locally low‐rank (LLR) and compressed sensing reconstructions (CS) for reference.

Methods

Data were acquired using a 3D Cartesian pseudo‐spiral in‐out k‐t undersampling scheme (R = 10) and reconstructed using MI‐LLR, which encompasses two stages. In the first stage, approximate displacement fields are derived from an initial LLR reconstruction to feed a motion‐compensated reference system to a second reconstruction stage, which reduces the rank of the inverse problem. For comparison, data were also reconstructed with LLR and frame‐by‐frame CS using wavelets as sparsifying transform (ℓ1‐wavelet).

Reconstruction accuracy relative to ground truth was assessed using synthetic data for realistic ranges of breathing motion, heart rates, and SNRs. In‐vivo experiments were conducted in healthy subjects at rest and during adenosine stress. Myocardial blood flow (MBF) maps were derived using a Fermi model.

Results

Improved uniformity of MBF maps with reduced local variations was achieved with MI‐LLR. For rest and stress, intra‐volunteer variation of absolute and relative MBF was lower in MI‐LLR (±0.17 mL/g/min [26%] and ±1.07 mL/g/min [33%]) versus LLR (±0.19 mL/g/min [28%] and ±1.22 mL/g/min [36%]) and versus ℓ1‐wavelet (±1.17 mL/g/min [113%] and ±6.87 mL/g/min [115%]). At rest, intra‐subject MBF variation was reduced significantly with MI‐LLR.

Conclusion

The combination of pseudo‐spiral Cartesian undersampling and dual‐stage MI‐LLR reconstruction improves free‐breathing quantitative 3D myocardial perfusion CMR imaging under rest and stress condition.

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Fully self-gated free-running 3D Cartesian cardiac CINE with isotropic whole-heart coverage in less than 2 min

PURPOSE

To develop a novel fast water-selective free-breathing 3D Cartesian cardiac CINE scan with full self-navigation and isotropic whole-heart (WH) coverage.

METHODS

A free-breathing 3D Cartesian cardiac CINE scan with a water-selective balanced steady-state free precession and a continuous (non-ECG-gated) variable-density Cartesian sampling with spiral profile ordering, out-inward sampling and acquisition-adaptive alternating tiny golden and golden angle increment between spiral arms is proposed. Data is retrospectively binned based on respiratory and cardiac self-navigation signals. A translational respiratory-motion-corrected and cardiac-motion-resolved image is reconstructed with a multi-bin patch-based low-rank reconstruction (MB-PROST) within about 15 min. A respiratory-motion-resolved approach is also investigated. The proposed 3D Cartesian cardiac CINE is acquired in sagittal orientation in 1 min 50 s for 1.9 mm³ isotropic WH coverage. Left ventricular (LV) function parameters and image quality derived from a blinded reading of the proposed 3D CINE framework are compared against conventional multi-slice 2D CINE imaging in 10 healthy subjects and 10 patients with suspected cardiovascular disease.

RESULTS

The proposed framework provides free-breathing 3D cardiac CINE images with 1.9 mm³ spatial and about 45 ms temporal resolution in a short acquisition time (<2 min). LV function parameters derived from 3D CINE were in good agreement with 2D CINE (10 healthy subjects and 10 patients). Bias and confidence intervals were obtained for end-systolic volume, end-diastolic volume and ejection fraction of 0.1 ± 3.5 mL, -0.6 ± 8.2 mL and -0.1 ± 2.2%, respectively.

CONCLUSION

The proposed framework enables isotropic 3D Cartesian cardiac CINE under free breathing for fast assessment of cardiac anatomy and function.

High-Resolution Oscillating Steady-State fMRI Using Patch-Tensor Low-Rank Reconstruction

The goals of fMRI acquisition include high spatial and temporal resolutions with a high signal to noise ratio (SNR). Oscillating Steady-State Imaging (OSSI) is a new fMRI acquisition method that provides large oscillating signals with the potential for high SNR, but does so at the expense of spatial and temporal resolutions. The unique oscillation pattern of OSSI images makes it well suited for high-dimensional modeling. We propose a patch-tensor low-rank model to exploit the local spatial-temporal low-rankness of OSSI images. We also develop a practical sparse sampling scheme with improved sampling incoherence for OSSI. With an alternating direction method of multipliers (ADMM) based algorithm, we improve OSSI spatial and temporal resolutions with a factor of 12 acquisition acceleration and 1.3 mm isotropic spatial resolution in prospectively undersampled experiments. The proposed model yields high temporal SNR with more activation than other low-rank methods. Compared to the standard grad- ient echo (GRE) imaging with the same spatial-temporal resolution, 3D OSSI tensor model reconstruction demonstrates 2 times higher temporal SNR with 2 times more functional activation.

Isotropic 3D Cartesian single breath-hold CINE MRI with multi-bin patch-based low-rank reconstruction

PURPOSE

To develop a novel acquisition and reconstruction framework for isotropic 3D Cartesian cardiac CINE within a single breath-hold for left ventricle (LV) and whole-heart coverage.

METHODS

A variable-density Cartesian acquisition with spiral profile ordering, out-inward sampling, and acquisition-adaptive alternating tiny golden/golden angle increment between spiral arms is proposed to provide incoherent and nonredundant sampling within and among cardiac phases. A novel multi-bin patch-based low-rank reconstruction, named MB-PROST, is proposed to exploit redundant information on a local (within a patch), nonlocal (similar patches within a spatial neighborhood), and temporal (among all cardiac phases) scale with an implicit motion alignment among patches. The proposed multi-bin patch-based low-rank reconstruction reconstruction is compared against compressed sensing reconstruction, whereas LV function parameters derived from the proposed 3D CINE framework are compared against those estimated from conventional multislice 2D CINE imaging in 10 healthy subjects and 15 patients.

RESULTS

The proposed framework provides 3D cardiac CINE images with high spatial (1.9 mm³ ) and temporal resolution (˜50 ms) in a single breath-hold of ˜20 s for LV and ˜26 s for whole-heart coverage in healthy subjects. Shorter breath-hold durations of ˜13 to 15 s are feasible for LV coverage with slightly anisotropic resolution (1.9 × 1.9 × 2.5 mm) in patients. LV function parameters derived from 3D CINE were in good agreement with 2D CINE, with a bias of -0.1 mL/0.1 mL, -0.9 mL/-1.0 mL, -0.1%/-0.8%; and confidence intervals of ±1.7 mL/±3.7 mL, ±1.2 mL/±2.6 mL, and ±1.2%/±3.6% (10 healthy subjects/15 patients) for end-systolic volume, end-diastolic volume, and ejection fraction, respectively.

CONCLUSION

The proposed framework enables 3D isotropic cardiac CINE in a single breath-hold scan of ˜20 s/˜26 s for LV/whole-heart coverage, showing good agreement with clinical 2D CINE scans in terms of LV functional assessment.

Sensitivity enhancement of (Hyper-)CEST image series by exploiting redundancies in the spectral domain

CEST has proven to be a valuable technique for the detection of hyperpolarized xenon-based functionalized contrast agents. Additional information can be encoded in the spectral dimension, allowing the simultaneous detection of multiple different biosensors. However, owing to the low concentration of dissolved xenon in biological tissue, the signal-to-noise ratio (SNR) of Hyper-CEST data is still a critical issue. In this work, we present two techniques aiming to increase SNR by exploiting the typically high redundancy in spectral CEST image series: PCA-based post-processing and sub-sampled acquisition with low-rank reconstruction. Each of them yields a significant SNR enhancement, demonstrating the feasibility of the two approaches. While the first method is directly applicable to proton CEST experiments as well, the second one is particularly beneficial when dealing with hyperpolarized nuclei, since it distributes the non-renewable initial polarization more efficiently over the sampling points. The results obtained are a further step towards the detection of xenon biosensors with spectral Hyper-CEST imaging in vivo.