Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals.

BACKGROUND: Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images. METHODS: Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. RESULTS: Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5 ± 0.3) was significantly higher than for Native 4D flow (0.7 ± 0.1, p < 0.01) and was comparable to 2D flow (2.3 ± 0.9, p = 0.02). Image quality scores of SyNAPS 4D flow from the experts (M.P.: 1.9 ± 0.3, E.T.: 2.5 ± 0.5) were overall significantly higher than the scores from Native 4D flow (M.P.: 1.6 ± 0.6, p = 0.03, E.T.: 0.8 ± 0.4, p < 0.01) but still significantly lower than the scores from the reference 2D flow datasets (M.P.: 2.8 ± 0.4, p < 0.01, E.T.: 3.5 ± 0.7, p < 0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69 ± 0.24 for the AAo and 0.83 ± 0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12 ± 0.48 for the AAo and 0.08 ± 0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2 = 0.83) and peak flow (r2 = 0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2 = 0.79) and peak flow (r2 = 0.76). CONCLUSION: The feasibility and utility of SyNAPS were demonstrated for joint whole-heart anatomical and flow MRI without requiring electrocardiography gating, respiratory navigators, or contrast agents. Using SyNAPS, a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents.

SPARCQ: A new approach for fat fraction mapping using asymmetries in the phase-cycled balanced SSFP signal profile.

PURPOSE: To develop SPARCQ (Signal Profile Asymmetries for Rapid Compartment Quantification), a novel approach to quantify fat fraction (FF) using asymmetries in the phase-cycled balanced SSFP (bSSFP) profile. METHODS: SPARCQ uses phase-cycling to obtain bSSFP frequency profiles, which display asymmetries in the presence of fat and water at certain TRs. For each voxel, the measured signal profile is decomposed into a weighted sum of simulated profiles via multi-compartment dictionary matching. Each dictionary entry represents a single-compartment bSSFP profile with a specific off-resonance frequency and relaxation time ratio. Using the results of dictionary matching, the fractions of the different off-resonance components are extracted for each voxel, generating quantitative maps of water and FF and banding-artifact-free images for the entire image volume. SPARCQ was validated using simulations, experiments in a water-fat phantom and in knees of healthy volunteers. Experimental results were compared with reference proton density FFs obtained with 1 H-MRS (phantoms) and with multiecho gradient-echo MRI (phantoms and volunteers). SPARCQ repeatability was evaluated in six scan-rescan experiments. RESULTS: Simulations showed that FF quantification is accurate and robust for SNRs greater than 20. Phantom experiments demonstrated good agreement between SPARCQ and gold standard FFs. In volunteers, banding-artifact-free quantitative maps and water-fat-separated images obtained with SPARCQ and ME-GRE demonstrated the expected contrast between fatty and non-fatty tissues. The coefficient of repeatability of SPARCQ FF was 0.0512. CONCLUSION: SPARCQ demonstrates potential for fat quantification using asymmetries in bSSFP profiles and may be a promising alternative to conventional FF quantification techniques.

Focused navigation for respiratory-motion-corrected free-running radial 4D flow MRI.

PURPOSE: To validate a respiratory motion correction method called focused navigation (fNAV) for free-running radial whole-heart 4D flow MRI. METHODS: Using fNAV, respiratory signals derived from radial readouts are converted into three orthogonal displacements, which are then used to correct respiratory motion in 4D flow datasets. Hundred 4D flow acquisitions were simulated with non-rigid respiratory motion and used for validation. The difference between generated and fNAV displacement coefficients was calculated. Vessel area and flow measurements from 4D flow reconstructions with (fNAV) and without (uncorrected) motion correction were compared to the motion-free ground-truth. In 25 patients, the same measurements were compared between fNAV 4D flow, 2D flow, navigator-gated Cartesian 4D flow, and uncorrected 4D flow datasets. RESULTS: For simulated data, the average difference between generated and fNAV displacement coefficients was 0.04 ± $$ \pm $$ 0.32 mm and 0.31 ± $$ \pm $$ 0.35 mm in the x and y directions, respectively. In the z direction, this difference was region-dependent (0.02 ± $$ \pm $$ 0.51 mm up to 5.85 ± $$ \pm $$ 3.41 mm). For all measurements (vessel area, net volume, and peak flow), the average difference from ground truth was higher for uncorrected 4D flow datasets (0.32 ± $$ \pm $$ 0.11 cm2 , 11.1 ± $$ \pm $$ 3.5 mL, and 22.3 ± $$ \pm $$ 6.0 mL/s) than for fNAV 4D flow datasets (0.10 ± $$ \pm $$ 0.03 cm2 , 2.6 ± $$ \pm $$ 0.7 mL, and 5.1 ± 0 $$ \pm 0 $$ .9 mL/s, p < 0.05). In vivo, average vessel area measurements were 4.92 ± $$ \pm $$ 2.95 cm2 , 5.06 ± $$ \pm $$ 2.64 cm2 , 4.87 ± $$ \pm $$ 2.57 cm2 , 4.87 ± $$ \pm $$ 2.69 cm2 , for 2D flow and fNAV, navigator-gated and uncorrected 4D flow datasets, respectively. In the ascending aorta, all 4D flow datasets except for the fNAV reconstruction had significantly different vessel area measurements from 2D flow. Overall, 2D flow datasets demonstrated the strongest correlation to fNAV 4D flow for both net volume (r2  = 0.92) and peak flow (r2  = 0.94), followed by navigator-gated 4D flow (r2  = 0.83 and r2  = 0.86, respectively), and uncorrected 4D flow (r2  = 0.69 and r2  = 0.86, respectively). CONCLUSION: fNAV corrected respiratory motion in vitro and in vivo, resulting in fNAV 4D flow measurements that are comparable to those derived from 2D flow and navigator-gated Cartesian 4D flow datasets, with improvements over those from uncorrected 4D flow.

Optogenetic stimulation of cortex to map evoked whisker movements in awake head-restrained mice.

Whisker movements are used by rodents to touch objects in order to extract spatial and textural tactile information about their immediate surroundings. To understand the mechanisms of such active sensorimotor processing it is important to investigate whisker motor control. The activity of neurons in the neocortex affects whisker movements, but many aspects of the organization of cortical whisker motor control remain unknown. Here, we filmed whisker movements evoked by sequential optogenetic stimulation of different locations across the left dorsal sensorimotor cortex of awake head-restrained mice. Whisker movements were evoked by optogenetic stimulation of many regions in the dorsal sensorimotor cortex. Optogenetic stimulation of whisker sensory barrel cortex evoked retraction of the contralateral whisker after a short latency, and a delayed rhythmic protraction of the ipsilateral whisker. Optogenetic stimulation of frontal cortex evoked rhythmic bilateral whisker protraction with a longer latency compared to stimulation of sensory cortex. Compared to frontal cortex stimulation, larger amplitude bilateral rhythmic whisking in a less protracted position was evoked at a similar latency by stimulating a cortical region posterior to Bregma and close to the midline. These data suggest that whisker motor control might be broadly distributed across the dorsal mouse sensorimotor cortex. Future experiments must investigate the complex neuronal circuits connecting specific cell-types in various cortical regions with the whisker motor neurons located in the facial nucleus.