A new approach to accelerate readout segmented EPI with compressed sensing.

PURPOSE: High resolution diffusion-weighted imaging is limited by susceptibility-induced distortions and relaxation-induced blurring. Segmented acquisition techniques can address these limitations at the expense of a prolonged scan time. If segmentation is performed along the readout direction, e.g., in RESOLVE (readout segmentation of long and variable echo-trains), scan time can be reduced by readout (RO) partial Fourier methods, or simultaneous multi-slice (SMS) methods. In this paper, we present a new approach to additionally accelerate the image acquisition called variable segment (VASE) RESOLVE. METHODS: To avoid discontinuities at the boundaries of the segments, the phase evolution and therefore the effective echo-spacing needs to be adjusted. To achieve this, we use higher undersampling factors in the outer parts of k-space. Simultaneously we increase the width of the outer segments resulting in an increase of the echo-spacing. Because of this variation, we introduce a kind of randomization to the sampling scheme. This enables the use of compressed sensing reconstruction techniques, which results in improved image quality compared to standard parallel imaging methods. RESULTS: The RMS errors for the VASE RESOLVE acquisitions were lower compared to the standard reconstructions. The VASE RESOLVE in vivo images show a higher apparent signal to noise ratio. CONCLUSION: VASE RESOLVE is a new approach to further decrease the acquisition time of RO segmented acquisitions. Compared to RESOLVE with SMS, VASE RESOLVE additionally reduces the acquisition time by a factor of 2.

Prospective motion correction in functional MRI using simultaneous multislice imaging and multislice-to-volume image registration.

The sensitivity to subject motion is one of the major challenges in functional MRI (fMRI) studies in which a precise alignment of images from different time points is required to allow reliable quantification of brain activation throughout the scan. Especially the long measurement times and laborious fMRI tasks add to the amount of subject motion found in typical fMRI measurements, even when head restraints are used. In case of moving subjects, prospective motion correction can maintain the relationship between spatial image information and subject anatomy by constantly adapting the image slice positioning to follow the subject in real time. Image-based prospective motion correction is well-established in fMRI studies and typically computes the motion estimates based on a volume-to-volume image registration, resulting in low temporal resolution. This study combines fMRI using simultaneous multislice imaging with multislice-to-volume-based image registration to allow sub-TR motion detection with subsequent real-time adaption of the imaging system. Simultaneous multislice imaging is widely used in fMRI studies and, together with multislice-to-volume-based image registration algorithms, enables computing suitable motion states after only a single readout by registering the simultaneously excited slices to a reference volume acquired at the start of the measurement. The technique is evaluated in three human BOLD fMRI studies (n = 1, 5, and 1) to explore different aspects of the method. It is compared to conventional, volume-to-volume-based prospective motion correction as well as retrospective motion correction methods. Results show a strong reduction in retrospectively computed residual motion parameters of up to 50% when comparing the two prospective motion correction techniques. An analysis of temporal signal-to-noise ratio as well as brain activation results shows high consistency between the results before and after additional retrospective motion correction when using the proposed technique, indicating successful prospective motion correction. The comparison of absolute tSNR values does not show an improvement compared to using retrospective motion correction alone. However, the improved temporal resolution may provide improved tSNR in the presence of more exaggerated intra-volume motion.

Simultaneous multislice acquisition with multi-contrast segmented EPI for separation of signal contributions in dynamic contrast-enhanced imaging.

We present a method to efficiently separate signal in magnetic resonance imaging (MRI) into a base signal S0, representing the mainly T1-weighted component without T2*-relaxation, and its T2*-weighted counterpart by the rapid acquisition of multiple contrasts for advanced pharmacokinetic modelling. This is achieved by incorporating simultaneous multislice (SMS) imaging into a multi-contrast, segmented echo planar imaging (EPI) sequence to allow extended spatial coverage, which covers larger body regions without time penalty. Simultaneous acquisition of four slices was combined with segmented EPI for fast imaging with three gradient echo times in a preclinical perfusion study. Six female domestic pigs, German-landrace or hybrid-form, were scanned for 11 minutes respectively during administration of gadolinium-based contrast agent. Influences of reconstruction methods and training data were investigated. The separation into T1- and T2*-dependent signal contributions was achieved by fitting a standard analytical model to the acquired multi-echo data. The application of SMS yielded sufficient temporal resolution for the detection of the arterial input function in major vessels, while anatomical coverage allowed perfusion analysis of muscle tissue. The separation of the MR signal into T1- and T2*-dependent components allowed the correction of susceptibility related changes. We demonstrate a novel sequence for dynamic contrast-enhanced MRI that meets the requirements of temporal resolution (Δt < 1.5 s) and image quality. The incorporation of SMS into multi-contrast, segmented EPI can overcome existing limitations of dynamic contrast enhancement and dynamic susceptibility contrast methods, when applied separately. The new approach allows both techniques to be combined in a single acquisition with a large spatial coverage.

Prospective motion correction in 2D multishot MRI using EPI navigators and multislice-to-volume image registration.

PURPOSE: Prospective motion correction reduces artifacts in MRI by correcting for subject motion in real time, but techniques are limited for multishot 2-dimensional (2D) sequences. This study addresses this limitation by using 2D echo-planar imaging (EPI) slice navigator acquisitions together with a multislice-to-volume image registration. METHODS: The 2D-EPI navigators were integrated into 2D imaging sequences to allow a rapid, real-time motion correction based on the registration of three navigator slices to a reference volume. A dedicated slice-iteration scheme was used to limit mutual spin-saturation effects between navigator and image data. The method was evaluated using T2 -weighted spin echo and multishot rapid acquisition with relaxation enhancement (RARE) sequences, and its motion-correction capabilities were compared with those of periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER). Validation was performed in vivo using a well-defined motion protocol. RESULTS: Data acquired during subject motion showed residual motion parameters within ±0.5 mm and ±0.5°, and demonstrated a substantial improvement in image quality compared with uncorrected scans. In a comparison to PROPELLER, the proposed technique preserved a higher level of anatomical detail in the presence of subject motion. CONCLUSIONS: EPI-navigator-based prospective motion correction using multislice-to-volume image registration can substantially reduce image artifacts, while minimizing spin-saturation effects. The method can be adapted for use in other 2D MRI sequences and promises to improve image quality in routine clinical examinations. Magn Reson Med 78:2127-2135, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Prospective motion correction in diffusion-weighted imaging using intermediate pseudo-trace-weighted images.

Subject head motion is a major challenge in diffusion-weighted imaging, which requires a precise alignment of images from different time points to allow a reliable quantification of diffusion parameters within each voxel. The technique requires long measurement times, making it highly sensitive to long-term subject motion, even when head restraint is used. Current methods of data analysis rely on retrospective motion correction, but there are potential benefits to using prospective motion correction, in which motion is tracked and compensated for during data acquisition. This technique is regularly used to enhance image quality in blood-oxygen-level dependent (BOLD) imaging, but its application to diffusion-weighted imaging has been limited by the contrast variation between images acquired with different diffusion-gradient directions. This paper describes a novel approach to this topic that exploits the rotational invariance of the trace of the diffusion tensor to reduce the effect of this contrast variation, making it possible to perform a fast image registration using a least-squares cost function. This results in an image-based motion detection algorithm that can be applied in real time during data acquisition to adapt the slice position and orientation in response to subject motion. The motion detection capabilities of the technique were evaluated in a study of ten subjects with b-values up to 3000s/mm². The resulting motion-parameter estimates were in close agreement with reference values provided by interleaved low-b-value images with a correlation coefficient of R=0.9634 for the voxel displacements measured across all subjects and b-values. The technique was also used to perform prospective motion correction on a standard clinical MRI system with b-values up to 2000s/mm². The correction was evaluated in 3 subjects using interleaved low-b-value images, retrospective image registration using the AFNI processing package and mean diffusivity histogram analysis. Compared to acquisitions without motion correction, prospective motion correction based on pseudo-trace-weighted images was found to provide a robust method for substantially reducing the level of misregistration between volumes. In most cases, misregistrations were reduced to less than 0.2mm of translation and 0.2° of rotation for an isotropic voxel size of 2mm, yielding high-quality diffusion parameter maps even in the absence of head restraint and post-acquisition image registration.

Readout-segmented echo-planar imaging in diffusion-weighted mr imaging in breast cancer: comparison with single-shot echo-planar imaging in image quality.

OBJECTIVE: The purpose of this study was to compare the image quality of standard single-shot echo-planar imaging (ss-EPI) and that of readout-segmented EPI (rs-EPI) in patients with breast cancer. MATERIALS AND METHODS: Seventy-one patients with 74 breast cancers underwent both ss-EPI and rs-EPI. For qualitative comparison of image quality, three readers independently assessed the two sets of diffusion-weighted (DW) images. To evaluate geometric distortion, a comparison was made between lesion lengths derived from contrast enhanced MR (CE-MR) images and those obtained from the corresponding DW images. For assessment of image parameters, signal-to-noise ratio (SNR), lesion contrast, and contrast-to-noise ratio (CNR) were calculated. RESULTS: The rs-EPI was superior to ss-EPI in most criteria regarding the qualitative image quality. Anatomical structure distinction, delineation of the lesion, ghosting artifact, and overall image quality were significantly better in rs-EPI. Regarding the geometric distortion, lesion length on ss-EPI was significantly different from that of CE-MR, whereas there were no significant differences between CE-MR and rs-EPI. The rs-EPI was superior to ss-EPI in SNR and CNR. CONCLUSION: Readout-segmented EPI is superior to ss-EPI in the aspect of image quality in DW MR imaging of the breast.