Implementation and Application of PSF-Based EPI Distortion Correction to High Field Animal Imaging

The purpose of this work is to demonstrate the functionality and performance of a PSF-based geometric distortion correction for high-field functional animal EPI. The EPI method was extended to measure the PSF and a postprocessing chain was implemented in Matlab for offline distortion correction. The correction procedure was applied to phantom and in vivo imaging of mice and rats at 9.4T using different SE-EPI and DWI-EPI protocols. Results show the significant improvement in image quality for single- and multishot EPI. Using a reduced FOV in the PSF encoding direction clearly reduced the acquisition time for PSF data by an acceleration factor of 2 or 4, without affecting the correction quality

MRI with phaseless encoding

Purpose Fourier encoded MRI signal is complex and, therefore, sensitive to uncontrolled phase variations caused, e.g., by object motion. An alternative encoding is proposed which leads to phaseless (positive real) signals and allows the phase fluctuations to be removed by simple magnitude calculation before the Fourier transform. Theory and Methods Phaseless encoding uses harmonic modulation of the longitudinal magnetization with different frequencies and phases before excitation. It can be combined with Fourier encoding of complementary dimensions to produce, e.g., a 3D version of echo planar imaging insensitive to intershot phase variations. It can also be mixed with Fourier encoding of the same dimension allowing a high‐resolution image to be obtained from magnitude‐reconstructed low‐resolution components. The latter is a generalization of the super‐resolution MRI with microscopic tagging proposed recently. Improved reconstruction for this technique was adopted from its optical analogue, harmonic excitation light microscopy (HELM). Results Artifact free images were obtained despite phase fluctuations caused by random receiver reference and object motion during diffusion weighting. Proposed reconstruction of mixed‐encoded data reaches higher resolution than the original super‐resolution method

Low-distortion diffusion tensor MRI with improved phaseless encoding

Due to the motion-related instability of the signal phase, diffusion MRI is usually performed with single-shot techniques such as the echo-planar imaging (EPI), which are resolution-limited and suffer from distortions caused by resonance offsets. Multi-shot methods may improve the images but require time-consuming navigators or a trade-off of the sensitivity encoding to measure shot-dependent phase errors. We have recently introduced an alternative approach to multi-shot MRI called phaseless encoding, which, by analogy to optical super-resolution methods, relies on the magnitude value of images taken in different shots thus discarding the phase error without navigators, and demonstrated its capability to perform diffusion MRI at sub-millimeter scale on a standard 3T scanner. In this work, we apply phaseless encoding in a routine diffusion tensor imaging (DTI) protocol with a moderately high resolution that is still within reach of single-shot EPI with the same hardware, and compare both techniques with respect to image distortions. A qualitative comparison of the phaseless encoding with the established navigator-based readout-segmented EPI is also presented. Several technical improvements are proposed to make phaseless encoding compatible with the routine scanning mode. The tagging radiofrequency pulses used in the encoding sequence are made slice-selective to avoid artefacts caused by saturation effects in multi-slice scans and their flip angle is optimized to reduce the intrinsic SNR loss. The super-resolution reconstruction algorithm is also improved to better suppress Gibbs ringing and to correct for possible signal amplitude fluctuations. Our study shows that the phaseless encoding is a promising approach to diffusion weighted imaging. It can easily be implemented in multi-slice sequences and produces less distorted images than the single-shot EPI at the same resolution and hardware parameters. It provides similar results to readout-segmented EPI but without the need of navigators

Diffusion-weighted imaging and diffusion tensor imaging of the heart in vivo: major developments

Diffusion-weighted magnetic resonance imaging (DWI) is a powerful diagnostic tool. Contrast in DWI images is dictated by the differences in diffusion of water in tissues, which depends on the tissue type, hydration and fluid composition. Therefore DWI can differentiate between hard and soft tissues, as well as visualize their condition, such as edema, necrosis or fibrosis. Diffusion tensor imaging (DTI) is a DWI technique which additionally delivers information about the microstructure. In cardiovascular applications DWI/DTI can non-invasively characterize the acute to chronic phase of the area at risk and microstructural dynamics without the need to use contrast agents. However, cardiac DWI/DTI differs from other applications due to serious anatomic and technologic challenges. Over the years, scientists have stepped up overcoming more and more advanced obstacles associated with complex 3D myocardial motions, breathing, blood flow and perfusion. The aim of this article is to review milestone technologic advances in DWI/ DTI of the heart in vivo. The discussed development begins with the adjustment of the diffusion imaging block to the electrocardiogram-based most quiescent phase, next considers different pulse sequence designs for first-, second- and higher-order motion compensation and SNR improvement, and ends up with prospects for further developments. Reviewed papers show great progress in this research area, but the gap between the scientific development and common clinical practice is tremendous. Cardiac DWI/ DTI has promising clinical relevance and its addition to routine imaging techniques of patients with heart disease may empower clinical diagnosis.ISSN:1734-9338ISSN:1897-429

Evaluating diffusion dispersion across an extended range of b-values and frequencies: Exploiting gap-filled OGSE shapes, strong gradients, and spiral readouts

Purpose: To address the long echo times and relatively weak diffusionsensitiza-tion that typically limit oscillating gradient spin- echo (OGSE) experiments, an OGSE implementation combining spiral readouts, gap- filled oscillating gradient shapes providing stronger diffusion encoding, and a high- performance gradient system is developed here and utilized to investigate the tradeoff between b- value and maximum OGSE frequency in measurements of diffusion dispersion (i.e., the frequency dependence of diffusivity) in the in vivo human brain. In addition, to assess the effects of the marginal flow sensitivity introduced by these OGSE waveforms, flow- compensated variants are devised for experimental comparison. Methods: Using DTI sequences, OGSE acquisitions were performed on three volunteers at b- values of 300, 500, and 1000 s/mm2and frequencies up to 125, 100, and 75 Hz, respectively; scans were performed for gap- filled oscillating gradient shapes with and without flow sensitivity. Pulsed gradient spin- echo DTI acquisi-tions were also performed at each b- value. Upon reconstruction, mean diffusivity (MD) maps and maps of the diffusion dispersion rate were computed. Results: The power law diffusion dispersion model was found to fit best to MD measurements acquired at b= 1000 s/mm2despite the associated reduction of the spectral range; this observation was consistent with Monte Carlo simulations. Furthermore, diffusion dispersion rates without flow sensitivity were slightly higher than flow- sensitive measurements. Conclusion: The presented OGSE implementation provided an improved de-piction of diffusion dispersion and demonstrated the advantages of measuring dispersion at higher b- values rather than higher frequencies within the regimes employed in this study.ISSN:0740-3194ISSN:1522-259

Motion-compensated diffusion encoding in multi-shot human brain acquisitions: Insights using high-performance gradients

Purpose: To evaluate the utility of up to second-order motion-compensated diffusion encoding in multi-shot human brain acquisitions. Methods: Experiments were performed with high-performance gradients using three forms of diffusion encoding motion-compensated through different orders: conventional zeroth-order–compensated pulsed gradients (PG), first-order–compensated gradients (MC1), and second-order–compensated gradients (MC2). Single-shot acquisitions were conducted to correlate the order of motion compensation with resultant phase variability. Then, multi-shot acquisitions were performed at varying interleaving factors. Multi-shot images were reconstructed using three levels of shot-to-shot phase correction: no correction, channel-wise phase correction based on FID navigation, and correction based on explicit phase mapping (MUSE). Results: In single-shot acquisitions, MC2 diffusion encoding most effectively suppressed phase variability and sensitivity to brain pulsation, yielding residual variations of about 10° and of low spatial order. Consequently, multi-shot MC2 images were largely satisfactory without phase correction and consistently improved with the navigator correction, which yielded repeatable high-quality images; contrarily, PG and MC1 images were inadequately corrected using the navigator approach. With respect to MUSE reconstructions, the MC2 navigator-corrected images were in close agreement for a standard interleaving factor and considerably more reliable for higher interleaving factors, for which MUSE images were corrupted. Finally, owing to the advanced gradient hardware, the relative SNR penalty of motion-compensated diffusion sensitization was substantially more tolerable than that faced previously. Conclusion: Second-order motion-compensated diffusion encoding mitigates and simplifies shot-to-shot phase variability in the human brain, rendering the multi-shot acquisition strategy an effective means to circumvent limitations of retrospective phase correction methods.ISSN:0740-3194ISSN:1522-259

Fourier transform temporal diffusion spectroscopy

Temporal diffusion spectroscopy (TDS) currently uses the oscillating gradient spin echo (OGSE) experiment to measure the spectral density of translational velocity autocorrelation at single frequencies. Due to timing restrictions imposed by the transverse relaxation, the frequency selectivity and the sampling density of OGSE are limited, especially at low frequencies. We propose to overcome this problem by adopting the principles of Fourier transform spectroscopy. The new method of Fourier transform TDS (FTDS) uses two broadband gradient waveforms with different relative delays to make the spin echo attenuation sensitive to a broad range of diffusion frequencies with different harmonic modulations and calculates the spectrum by discrete Fourier transform. The method was validated by a measurement of diffusion spectra in highly restrictive tissues of a celery stalk and provided results consistent with OGSE, however, on a denser frequency grid.ISSN:1090-780