Name: human fetal blood flow quantification with magnetic resonance imaging and motion compensation
Uploaded: 2021-01-07T13:00:00.000+00:00
Duration: 6 min 56 s
Description: Watch this Scientific Journal Video about Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation at JoVE.com

All MRI scans were performed with informed consent from volunteers as part of a study approved by our institutional research ethics board.
NOTE: The methods described below have been used on a 3T MRI system. The acquisition is performed using a radial phase contrast MRI sequence. This sequence was prepared by modifying the readout trajectory (to achieve a stellate pattern) of the manufacturer&#39;s Cartesian phase contrast MRI. The sequence and sample protocols are available upon request through our C2P exchange platform. All reconstructions in this work were performed on a standard desktop computer with the following specifications: 32 GB memory, 3.40 GHz processor with 8 cores, and 2GB graphic card with 1024 compute unified device architecture (CUDA) cores. Image reconstruction was performed on MATLAB. Nonuniform fast Fourier transform (NUFFT)29&#160;was performed on the graphics processing unit (GPU). Motion correction parameters were calculated using elastix30.&#160;Figure 1&#160;depicts the protocol in a chronological order, tracking how the acquired velocity encodes (color coded in&#160;Figure 1) are processed with representative images at each stage of reconstruction. The reconstruction code is available at https://github.com/datta-g/Fetal_PC_MRI. While we provide the steps in the protocol here, most of these algorithm steps are automated in our pipeline.
1.&#160;Subject positioning and localizer exams
<ol>
	<li>Assist the mother in positioning herself on the MRI table in her preferred comfortable position, usually supine or lateral decubitus positions, for the MRI exam.</li>
	<li>Place the cardiac coil over the abdominal region of the mother.</li>
	<li>Load the MRI table in the magnet bore and notify the mother that the scan is about to start.</li>
	<li>Run a localizer exam to locate the fetal body (resolution: 0.9 x 0.9 x 10 mm3, TE/TR: 5.0/15.0 ms, FOV: 450 x 450 mm2, slices: 6).</li>
	<li>Run a refined localizer exam to locate the fetal vasculature with the slice group centered on the fetal heart (resolution 1.1 x 1.1 x 6.0 mm3, TE/TR: 2.69/1335.4 ms, FOV: 350 x 350 mm2, slices: 10, orientation: axial to fetus).</li>
	<li>Repeat the refined localizers with sagittal and coronal orientations for a clearer view of the fetal vessels.</li>
	<li>Repeat the refined localizers in cases of gross fetal motion.</li>
</ol>
2.&#160;Acquisition of fetal blood flow data
<ol>
	<li>Locate fetal vessels using the localizer exams. For example, the descending aorta is a long straight vessel near the spine in the sagittal planes. The ascending aorta and main pulmonary arteries can be identified as vessels leaving the left and right ventricles, respectively. The ductus arteriosus can be tracked as a downstream segment of the main pulmonary artery proximal to the descending aorta. The superior vena cava can be identified from axial planes near the base of the fetal heart as the vessel adjacent to the ascending aorta.</li>
	<li>Prescribe a slice perpendicular to the axis of the fetal vessel of interest. Rotate and move the slice guideline on the MRI console computer such that it intersects the target vessel perpendicularly.</li>
	<li>Set the scan parameters (acquisition type: radial phase contrast MRI, resolution: 1.3 x 1.3 x 5.0 mm3, echo time (TE)/ repetition time (TR): 3.25/5.75 ms, field-of-view (FOV): 240 x 240 mm2, slice: 1, velocity encoding: 100-150 cm/s depending on vessel of interest, velocity encoding direction: through plane, radial views: 1500 per encode, free breathing).</li>
	<li>Run the scan and verify the prescription based on the initial time-averaged reconstruction performed and displayed on the MRI console computer. Repeat the localizer and phase contrast scans if the target vessel is absent or unidentifiable from the initial reconstruction. Acquired raw data is represented in the schematic in&#160;Figure 1A&#160;with the velocity compensated and through plane acquisitions color coded as red and blue, respectively.</li>
	<li>Repeat the fetal blood flow data acquisition for each target blood vessel. 
	NOTE: The acquired raw data (format: DAT files) must be transferred for offline reconstruction. For example, on Siemens scanners, this can be performed by running &#39;twix&#39;. The acquired raw data is right clicked from the list acquisitions and &#34;copy total raid file&#34; is chosen.</li>
</ol>
3.&#160;Motion correction of fetal measurements
<ol>
	<li>Reconstruct real-time series (temporal resolution: 370 ms, radial views: 64) from the acquired data using CS with 15 iterations of a conjugate gradient descent optimization exploiting spatial total variation (STV, weight: 0.008) and temporal total variation (TTV, weight: 0.08) regularization as represented by the schematic in&#160;Figure 1B.</li>
	<li>Select a region of interest (ROI) encompassing the vessel of interest from this first real-time reconstruction using a graphic user interface developed in MATLAB. In this step, the user must draw a contour that encloses the fetal anatomy, such as the target great vessels or the fetal heart.</li>
	<li>Perform rigid-body motion tracking with elastix30&#160;(based on normalized mutual information with empirically optimized parameters: 4 pyramid levels, 300 iterations and translational transforms).</li>
	<li>Reject tracked real-time frames that share low mutual information (MI) with all other frames (whereby MI is less than 1.5x the interquartile range from the mean MI). These frames are deemed to be represented through plane motion or gross fetal motion.</li>
	<li>Use the MRI data corresponding to the longest series of continuous real-time frames (without gaps) from the remaining frames as the quiescent period used for further reconstruction.</li>
	<li>Interpolate translational motion correction parameters from the temporal resolution of the real-time series (370 ms) to the TR of the quiescent acquisition (5.75 ms).</li>
	<li>Apply interpolated parameters to the defined quiescent period of the MRI data by modulating the phase as in: 
	<img alt="Equation 1" src="/files/ftp_upload/61953/61953_eq01.png" /> 
	 
	where&#160;s&#39;&#160;is the motion corrected data,&#160;kx&#160;and&#160;ky&#160;are the coordinates in k-space,&#160;s&#160;is the acquired uncorrected data,&#160;&#916;x&#160;and&#160;&#916;y&#160;are the tracked displacements in space, and&#160;j&#160;represents <img alt="Equation 3" src="/files/ftp_upload/61953/61953eq2.jpg" />. 
	NOTE: All numerical values of regularization coefficients in this work were optimized in earlier experiments. This was accomplished using a brute-force grid search to find the regularization coefficients that minimized the error between reconstructions of a highly sampled fetal reference dataset and retrospectively undersampled cases from the same dataset.</li>
</ol>
4.&#160;Solving for fetal heart rate
<ol>
	<li>Reconstruct a second real-time image series at a higher temporal resolution (temporal resolution: 46 ms, radial views: 8) using the acquired data using CS, again with 15 iterations of a conjugate gradient descent optimization with STV (weight: 0.008) and TTV (weight: 0.08) regularization as represented by the schematic in Figure 1C.</li>
	<li>Re-select an ROI encompassing the fetal vessel of interest.</li>
	<li>Run multiparameter MOG on the real-time series to derive the time-dependent fetal heart rate.</li>
	<li>Bin motion corrected MRI data into 15 cardiac phases using the derived heart rate waveform. In this step, the temporal boundaries of the cardiac phases are computed using the heart rate from the previous step. For instance, the boundaries for the&#160;ith&#160;phase in the&#160;kth&#160;heartbeat are given by: 
	<img alt="Equation 2a" src="/files/ftp_upload/61953/61953_eq1a.png" /> 
	<img alt="Equation 2b" src="/files/ftp_upload/61953/61953_eq1b.png" /> 
	where HR(K) is the time at which the&#160;kth&#160;heartbeat occurs. The timestamp of the&#160;nth&#160;radial acquisition is given by (n&#160;x TR). Data with timestamps falling within the boundaries of a cardiac phase are assigned to that phase. 
	NOTE: MOG is a gating technique26&#160;that comprises iterative binning of the acquired data based on a multi-parameter fetal heart rate model to create CINE images that optimize an image metric over a region of interest.</li>
</ol>
5.&#160;Reconstruction of fetal CINEs
<ol>
	<li>Reconstruct fetal flow CINEs using the binned motion corrected MRI data and CS with 10 iterations of a conjugate gradient descent optimization with STV (weight: 0.025) and TTV (weight: 0.01) regularization. Two CINEs are produced at this step: one for the flow compensated acquisition, CFC,&#160;and one with the flow encoded data, CFE, as represented in the schematic in&#160;Figure 1D.</li>
	<li>Compute the velocity image given by the phase of the elementwise product of CFE&#160;and the complex conjugate of CFC.</li>
	<li>Apply background phase correction31&#160;to correct for eddy current effects. Briefly, in this automatic step, a plane is fitted to the phase of static fetal and maternal tissues. The correction is performed by subtracting the plane from the velocity sensitive phase computed in 4.2.</li>
	<li>Write reconstructed data into DICOM files.</li>
	<li>Load DICOMs into flow analysis software, such as Segment v2.232.</li>
	<li>Draw an ROI encompassing the lumen of the blood vessel of interest using the anatomical and velocity sensitive images.</li>
	<li>Propagate the ROI to all cardiac phases and correct for changes in the vessel&#39;s diameter.</li>
	<li>Record flow measurements.</li>
</ol>

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This method enables the non-invasive measurement of blood flow in human fetal great vessels and allows for retrospective motion correction and cardiac gating by making use of iterative reconstruction techniques. Fetal blood flow quantification has been performed with MRI in the past1,3,8,9. These studies had a prospective approach to mitigate motion corruption whereby scans would be repeated if gross fetal motion was visually identified from an initial reconstruction on the scanner. The current protocol improves on this by retrospectively rejecting data corrupted by gross fetal motion and further corrects for in-plane displacements arising from subtle fetal movements or maternal respiratory motion.
This protocol makes use of a multiparameter model for MOG whereby the RR interval for each fetal heartbeat is calculated. Using a low parameter heart rate model (such as 2 parameters) is generally acceptable for short scans since the healthy fetal heart rate has a low variability33. However, low parameter models become problematic for longer scans or in cases of pathologies such as arrythmia. A multiparameter model in MOG can track these changing RR intervals, providing more accurate flows.
The current protocol allows for some modifications. First, third party software used in this study for motion tracking and flow analysis can be replaced by other available software packages. Second, the number of iterations in the conjugate gradient descent algorithms for CS can be increased. In this study, the number of iterations in each step was set at a value beyond which there were minimal improvements based on prior reconstructions. In this work, only third trimester pregnancies were scanned. In earlier pregnancies, the fetus is smaller and there may be more room for motion. However, since quiescent periods in the scan are identified retrospectively for CINE reconstructions, this protocol should be successful for flow imaging at these earlier ages. An increase in the resolution of the scans may be required to cater to smaller vessel diameters at lower gestational age. For this protocol, the reconstruction times reported in&#160;Figure 1&#160;and the Results are heavily dependent on the computational power available. For example, with better GPUs and more powerful processors, reconstruction times can be significantly reduced.
The protocol has certain limitations. First, the quality of the CINE reconstruction depends on the amount of data rejected in the motion correction step. With increasing episodes of gross fetal movements during a scan, more data is rejected. Consequently, the resulting signal-to-noise ratio (SNR) in the CINE reconstructions will decrease. Low SNR increases the uncertainty in the velocity images34&#160;and the resulting flow quantification. Performance will therefore improve with greater fetal quiescence. Second, the method depends on the definition of ROIs for motion correction and MOG. In the current implementation, this step is performed manually. We have found that the reconstruction is stable to small differences in ROI position but this process results in wait times between the data acquisition and CINE reconstructions (since there are two ROI placement steps between the three iterative reconstruction steps). This becomes more cumbersome when there is a large number of slices acquired. In future implementations of the protocol, ROI placement will be automated.
Currently, we are using the presented protocol in research studies with approval from the local ethics board. The protocol can also be used in cases in which motion is a potential problem during an MRI exam, such as in neonates or uncooperative subjects. Future directions of the method involve investigating spiral trajectories35,36, which provide more efficient sampling and a possibility for exploring real-time fetal flow.

Comprehensive assessment of the fetal circulation is necessary for monitoring fetal pathologies such as fetal growth restriction (FGR) and congenital heart disease (CHD)1,2,3. In utero, patient management and planning for postnatal care depend on the severity of the fetal pathology4,5,6,7. Feasibility of fetal blood flow quantification with MRI and its applications in assessing fetal pathologies have recently been demonstrated3,8,9. The imaging method, however, faces challenges, such as increased imaging times to achieve high spatiotemporal resolution, lack of cardiac synchronization methods, and unpredictable fetal motion10.
Fetal vasculature comprises small structures (~5 mm diameter for major blood vessels that comprise the descending aorta, ductus arteriosus, ascending aorta, main pulmonary artery, and superior vena cava11,12,13).To resolve these structures and to quantify flow, imaging at high spatial resolution is required. Moreover, the fetal heart rate is about twice that of an adult. A high temporal resolution is thus also required to resolve dynamic cardiac motion and blood flow across the fetal cardiac cycle. Conventional imaging at this high spatiotemporal resolution requires relatively long acquisition times. To address this issue, accelerated fetal MRI14,15,16&#160;has been introduced. Briefly, these acceleration techniques involve undersampling in the frequency domain during data acquisition and retrospective high-fidelity reconstruction using iterative techniques. One such approach is compressed sensing (CS) reconstruction, which allows reconstruction of images from heavily undersampled data when the reconstructed image is sparse in a known domain and undersampling artifacts are incoherent17.
Motion in fetal imaging presents a major challenge. Motion corruption can arise from maternal respiratory motion, maternal bulk motion or gross fetal movement. Maternal respiration leads to periodic translations of the fetus, whereas fetal movements are more complex. Fetal movements can be classified as localized or gross10,18. Localized movements involve motion of only segments of the body. They typically last for about 10-14 s and their frequency increases with gestation (~90 per hour at term)10. These movements generally cause small corruptions and do not affect the imaging area of interest. However, gross fetal movements can lead to severe image corruption with through plane motion components. These movements are whole body movements mediated by the spine and last for 60-90 s.
To avoid artifacts from fetal motion, steps are first taken to minimize maternal motions. Pregnant women are made more relaxed using supportive pillows on the scanner bed and dressed in comfortable gowns and may have their partners present beside the scanner to reduce claustrophobia19,20. To mitigate effects of maternal respiratory motion, studies have performed fetal MR exams under maternal breath-hold21,22,23. However, such acquisitions must be short (~15 s) given the reduced breath-hold tolerance of pregnant subjects. Recently, retrospective motion correction methods have been introduced for fetal MRI14,15,16. These methods track fetal motion using registration toolkits and correct for motion or discard uncorrectable portions of acquired data.
Finally, postnatal cardiac MR images are conventionally acquired using electrocardiogram (ECG) gating to synchronize data acquisition to the cardiac cycle. Without gating, cardiac motion and pulsatile flow from throughout the cardiac cycle are combined, producing artifacts. Unfortunately, the fetal ECG signal suffers from interference from the maternal ECG signal24&#160;and distortions from the magnetic field25. Hence, alternative non-invasive approaches to fetal cardiac gating have been proposed, including self-gating, metric optimized gating (MOG) and doppler ultrasound gating21,26,27,28.
As described in the following sections, our MRI approach to quantify fetal blood flow leverages a novel gating method, MOG, developed in our laboratory and combined with motion correction and iterative reconstruction of accelerated MRI acquisitions. The approach is based on a pipeline in a previously published study14&#160;and is composed of the following five stages: (1) fetal blood flow acquisition, (2) real-time reconstructions, (3) motion correction, (4) cardiac gating, and (5) gated reconstructions.

<table><tbody><tr><td>elastix</td><td>Image Sciences Institute, University Medical Center Utrecht</td><td></td><td>Image registration software</td></tr><tr><td>Geforce GTX 960&amp;nbsp;</td><td>Nvidia&amp;nbsp;</td><td>04G-P4-3967-KR</td><td></td></tr><tr><td>gpuNUFFT</td><td>CAI&amp;sup2;R</td><td></td><td>Non-uniform fast Fourier transform</td></tr><tr><td>MAGNETOM Prisma</td><td>Siemens</td><td>10849583</td><td></td></tr><tr><td>MATLAB</td><td>MathWorks</td><td></td><td></td></tr><tr><td>Radial Phase Contrast MRI sequence</td><td></td><td></td><td>Trajectory modification of manufacturer&#039;s Cartesian Phase Contrast sequence</td></tr><tr><td>Segment</td><td>Medvisio</td><td></td><td>Data analysis</td></tr><tr><td>VENGEANCE</td><td>Corsair</td><td>LPX DDR4-2666&amp;nbsp;</td><td></td></tr></tbody></table>

human fetal blood flow quantification with magnetic resonance imaging and motion compensation

Magnetic resonance imaging (MRI) is an important tool for the clinical assessment of cardiovascular morphology and heart function. It is also the recognized standard-of-care for blood flow quantification based on phase contrast MRI. While such measurement of blood flow has been possible in adults for decades, methods to extend this capability to fetal blood flow have only recently been developed.
Fetal blood flow quantification in major vessels is important for monitoring fetal pathologies such as congenital heart disease (CHD) and fetal growth restriction (FGR). CHD causes alterations in the cardiac structure and vasculature that change the course of blood in the fetus. In FGR, the path of blood flow is altered through the dilation of shunts such that the oxygenated blood supply to the brain is increased. Blood flow quantification enables assessment of the severity of the fetal pathology, which in turn allows for suitable&#160;in utero&#160;patient management and planning for postnatal care.
The primary challenges of applying phase contrast MRI to the human fetus include small blood vessel size, high fetal heart rate, potential MRI data corruption due to maternal respiration, unpredictable fetal movements, and lack of conventional cardiac gating methods to synchronize data acquisition. Here, we describe recent technical developments from our lab that have enabled the quantification of fetal blood flow using phase contrast MRI, including advances in accelerated imaging, motion compensation, and cardiac gating.

In general, phase MRI examinations of flow target six major fetal vessels: the descending aorta, ascending aorta, main pulmonary artery, ductus arteriosus, superior vena cava, and umbilical vein. These vessels are of interest to the clinician as they are often implicated in CHD and FGR, influencing the distribution of blood throughout the fetus9. A typical scan duration with the radial phase contrast MRI is 17 s per vessel such that the scans are short while also allowing time for enough data acquisition for CINE reconstruction. The total acquisition time, including localizers and phase contrast MRI, for the representative results was 3 min. In this study, representative results are presented using flow acquisition data from the descending aorta in two human fetuses: Fetus 1 and Fetus 2 with gestational ages (week + days) of 35+4 and 37+3, respectively.
As in&#160;Figure 1, initial real-time reconstructions (temporal resolution: 370 ms) performed for motion tracking took 45 s per reconstructed slice. Translation motion tracking took 2 min for each slice. The extracted motion parameters for Fetus 1 (Figure 2&#160;A1, maximum displacement: 1.6 mm) and Fetus 2 (Figure 2&#160;A2, maximum displacement: 1.3 mm) depict the motion of the descending aorta over the duration of the scan. The shared mutual information of each real-time frame with all other co-registered frames are shown in&#160;Figure 2&#160;B1 (Fetus 1) and&#160;Figure 2&#160;B2 (Fetus 2). In these cases, all frames shared mutual information above the cut off criteria, so no data was rejected. The second real-time reconstructions (temporal resolution: 46 ms), used to derive cardiac gating information, took 10 min for each slice. MOG derived the fetal heartbeat (RR) intervals using a multiparameter model, as shown in&#160;Figure 2&#160;C1 (Fetus 1, RR interval: 521 &#177; 20 ms) and&#160;Figure 2&#160;C2 (Fetus 2, RR interval: 457 &#177; 9 ms).
Final CINE reconstructions using the retrospectively motion-corrected and gated data took 3 min per slice. The anatomical and velocity reconstructions for Fetus 1 and Fetus 2 at peak systole are shown in&#160;Figure 3. Reconstructions with motion correction show vessels with sharper walls. Without motion correction, the descending aorta is blurrier and less conspicuous. The measured flow curves from each fetus (Figure 4) show higher peak and mean flows in the reconstructions without motion correction ([peak mean]: Fetus 1 [25.2 9.8] ml/s, Fetus 2 [34.6 10.3] ml/s]) than in those with motion correction ([peak mean]: Fetus 1 [23.5 9.2] ml/s, Fetus 2 [28.7 9.7] ml/s]).
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/61953/61953fig01.jpg" /> 
Figure 1: Pipeline to reconstruct fetal phase contrast MRI data. (A) Step 1: Golden-angle radial phase contrast MRI data (color coded as: flow compensation = red &#38; through plane encode = blue). The alternating colors depict that the flow-compensated and through-plane encoded acquisitions occur at the same spatial frequencies. (B) Step 2: Temporal windows of 370 ms for real-time reconstruction using CS with sparsity constraints (STV and TTV). Motion correction and data rejection are performed. (C) Step 3: Temporal windows of 46 ms are created for real-time reconstruction with CS (with STV and TTV sparsity constraints) for MOG. (D) Step 4: The data is binned into cardiac phases (CP), and CS is used to create a fetal flow CINE, with sparsity constraints (STV and TTV). Representative reconstructions from each CS step are shown in the Reconstructions column. Reconstructions for steps 3 and 4 are shown for a time point corresponding to peak systole. Scale bars in the top left corner of the anatomical images denote 10 mm in the image. The time specifications, in seconds, highlighted in grey represent the durations of the corresponding steps. STV: spatial total variation, TTV: temporal total variation, CS: compressed sensing, MOG: metric optimized gating, CINE: gated dynamic reconstruction.&#160;<a href="https://www.jove.com/files/ftp_upload/61953/61953fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/61953/61953fig02.jpg" /> 
Figure 2: Representative displacement and heart rate curves. A1 and A2 depict retrospectively tracked displacement curve for the scans in Fetus 1 and Fetus 2, respectively. B1 and B2 show the sum of the mutual information of a given frame with all other frames for Fetus 1 and Fetus 2, respectively. The red dotted lines represent 1.5x interquartile range below which data is rejected. C1 and C2 depict the RR intervals derived with MOG in Fetus 1 and Fetus 2, respectively. RR interval: time between consecutive heartbeats, MOG: metric optimized gating.&#160;<a href="https://www.jove.com/files/ftp_upload/61953/61953fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure3" class="xfigimg" src="/files/ftp_upload/61953/61953fig03.jpg" /> 
Figure 3: Representative velocity sensitive CINE reconstructions at peak systole. Each quadrant depicts the anatomical and velocity reconstructions. The top row shows the CINE with motion correction in Fetus 1 and Fetus 2, respectively. The bottom row shows the CINE without motion correction in Fetus 1 and Fetus 2, respectively. The red and blue arrows depict the descending aorta. Scale bars in the top left corner of the anatomical images denote 10 mm.&#160;<a href="https://www.jove.com/files/ftp_upload/61953/61953fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/61953/61953fig04.jpg" /> 
Figure 4: Representative flow curves in the fetal descending aorta. The solid and dashed data lines depict the flow curves obtained from CINE reconstructions with and without motion correction, respectively, in Fetus 1 (left) and Fetus 2 (right). <a href="https://www.jove.com/files/ftp_upload/61953/61953fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation at JoVE.com

Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Here we present a protocol for measuring fetal blood flow rapidly with MRI and retrospectively performing motion correction and cardiac gating.

Magnetic resonance imaging (MRI) is an important tool for the clinical assessment of cardiovascular morphology and heart function. It is also the ...

human-fetal-blood-flow-quantification-with-magnetic-resonance-imaging

Nanyang Technological University

Research

JoVE Journal

Medicine

2.0K Views.  University of Toronto. Here we present a protocol for measuring fetal blood flow rapidly with MRI and retrospectively performing motion correction and cardiac gating.

Video: Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking 

Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF. Current technologies for CMR are time consuming and difficult to implement in clinical practice. Feature tracking is a technology that can lead to more automization and robustness of quantitative analysis of medical images with less time consumption than comparable methods.
Methods: An automatic or manual input in a single phase serves as an initialization from which the system starts to track the displacement of individual patterns representing anatomical structures over time. The specialty of this method is that the images do not need to be manipulated in any way beforehand like e.g. tagging of CMR images.
Results: The method is very well suited for tracking muscular tissue and with this allowing quantitative elaboration of myocardium and also blood flow.
Conclusions: This new method offers a robust and time saving procedure to quantify myocardial tissue and blood with displacement, velocity and deformation parameters on regular sequences of CMR imaging. It therefore can be implemented in clinical practice.

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF.

Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that ...

Magnetic Resonance Imaging Quantification of Pulmonary Perfusion using Calibrated Arterial Spin Labeling

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, fraction (FIO2) = 0.21) hypoxia (FIO2 = 0.125), and hyperoxia 
(FIO2 = 1.00). In addition, the physiological responses of the subject are monitored in the MR scan environment. MR images 
were obtained on a 1.5 T GE MRI scanner during a breath hold from a sagittal slice in the right lung at functional residual capacity. An arterial 
spin labeling sequence (ASL-FAIRER) was used to measure the spatial distribution of pulmonary blood flow 1,2 and a multi-echo fast 
gradient echo (mGRE) sequence 3 was used to quantify the regional proton (i.e. H2O) density, allowing the quantification 
of density-normalized perfusion for each voxel (milliliters blood per minute per gram lung tissue). 
With a pneumatic switching valve and facemask equipped with a 2-way non-rebreathing valve, different oxygen concentrations 
were introduced to the subject in the MR scanner through the inspired gas tubing. A metabolic cart collected expiratory gas via expiratory tubing. Mixed expiratory O2 and CO2 concentrations, oxygen consumption, carbon dioxide production, respiratory exchange ratio, 
respiratory frequency and tidal volume were measured. Heart rate and oxygen saturation were monitored using pulse-oximetry. 
Data obtained from a normal subject showed that, as expected, heart rate was higher in hypoxia (60 bpm) than during normoxia (51) or hyperoxia (50) and the arterial oxygen saturation (SpO2) was reduced during hypoxia to 86%. Mean ventilation was 8.31 L/min BTPS during hypoxia, 7.04 L/min during normoxia, and 6.64 L/min during hyperoxia. Tidal volume was 0.76 L during hypoxia, 0.69 L during normoxia, and 0.67 L during hyperoxia. 
Representative quantified ASL data showed that the mean density normalized perfusion was 8.86 ml/min/g during hypoxia, 8.26 ml/min/g during normoxia and 8.46 ml/min/g during hyperoxia, respectively. In this subject, the relative dispersion4, an index of global heterogeneity, was increased in hypoxia (1.07 during hypoxia, 0.85 during normoxia, and 0.87 during hyperoxia) while the fractal dimension (Ds), another index of heterogeneity reflecting vascular branching structure, was unchanged (1.24 during hypoxia, 1.26 during normoxia, and 1.26 during hyperoxia). 
Overview. This protocol will demonstrate the acquisition of data to measure the distribution of pulmonary perfusion noninvasively under conditions of normoxia, hypoxia, and hyperoxia using a magnetic resonance imaging technique known as arterial spin labeling (ASL). 
Rationale: Measurement of pulmonary blood flow and lung proton density using MR technique offers high spatial resolution images which can be quantified and the ability to perform repeated measurements under several different physiological conditions. In human studies, PET, SPECT, and CT are commonly used as the alternative techniques. However, these techniques involve exposure to ionizing radiation, and thus are not suitable for repeated measurements in human subjects.

A MR imaging method to study the distribution of pulmonary blood flow under a variety of physiological conditions, in this case exposure to three different inspired oxygen concentrations: hypoxia, normoxia, and hyperoxia, is described. This technique utilizes human pulmonary physiology research techniques in an MR scanning environment.

This demonstrates a MR imaging method to measure the spatial distribution of pulmonary blood flow in healthy subjects 
during normoxia (inspired O2, ...

Murine Fetal Echocardiography

Transgenic mice displaying abnormalities in cardiac development and function represent a powerful tool for the understanding the molecular mechanisms underlying both normal cardiovascular function and the pathophysiological basis of human cardiovascular disease. Fetal and perinatal death is a common feature when studying genetic alterations affecting cardiac development 1-3. In order to study the role of genetic or pharmacologic alterations in the early development of cardiac function, ultrasound imaging of the live fetus has become an important tool for early recognition of abnormalities and longitudinal follow-up. Noninvasive ultrasound imaging is an ideal method for detecting and studying congenital malformations and the impact on cardiac function prior to death 4. It allows early recognition of abnormalities in the living fetus and the progression of disease can be followed in utero with longitudinal studies 5,6. Until recently, imaging of fetal mouse hearts frequently involved invasive methods. The fetus had to be sacrificed to perform magnetic resonance microscopy and electron microscopy or surgically delivered for transillumination microscopy. An application of high-frequency probes with conventional 2-D and pulsed-wave Doppler imaging has been shown to provide measurements of cardiac contraction and heart rates during embryonic development with databases of normal developmental changes now available 6-10. M-mode imaging further provides important functional data, although, the proper imaging planes are often difficult to obtain. High-frequency ultrasound imaging of the fetus has improved 2-D resolution and can provide excellent information on the early development of cardiac structures 11.

Fetal and perinatal death is a common feature when studying genetic alterations affecting cardiac development. High-frequency ultrasound imaging has improved 2-D resolution and can provide excellent information on early cardiac development and is an ideal method to detect the impact on cardiac structure and function prior to death.

Transgenic mice displaying abnormalities in  cardiac development and function represent a powerful tool for the understanding  the molecular mechanisms ...

High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon measuring activity on the surface of cerebral cortex rather than in subcortical regions such as midbrain and brainstem. Subcortical fMRI must overcome two challenges: spatial resolution and physiological noise. Here we describe an optimized set of techniques developed to perform high-resolution fMRI in human SC, a structure on the dorsal surface of the midbrain; the methods can also be used to image other brainstem and subcortical structures.
High-resolution (1.2 mm voxels) fMRI of the SC requires a non-conventional approach. The desired spatial sampling is obtained using a multi-shot (interleaved) spiral acquisition1. Since, T2* of SC tissue is longer than in cortex, a correspondingly longer echo time (TE ~ 40 msec) is used to maximize functional contrast. To cover the full extent of the SC, 8-10 slices are obtained. For each session a structural anatomy with the same slice prescription as the fMRI is also obtained, which is used to align the functional data to a high-resolution reference volume.
In a separate session, for each subject, we create a high-resolution (0.7 mm sampling) reference volume using a T1-weighted sequence that gives good tissue contrast. In the reference volume, the midbrain region is segmented using the ITK-SNAP software application2. This segmentation is used to create a 3D surface representation of the midbrain that is both smooth and accurate3. The surface vertices and normals are used to create a map of depth from the midbrain surface within the tissue4.
Functional data is transformed into the coordinate system of the segmented reference volume. Depth associations of the voxels enable the averaging of fMRI time series data within specified depth ranges to improve signal quality. Data is rendered on the 3D surface for visualization.
In our lab we use this technique for measuring topographic maps of visual stimulation and covert and overt visual attention within the SC1. As an example, we demonstrate the topographic representation of polar angle to visual stimulation in SC.

This article describes techniques to perform high-resolution functional magnetic resonance imaging with 1.2 mm sampling in human midbrain and subcortical structures using a 3T scanner. Use of these techniques to resolve topographic maps of visual stimulation in the human superior colliculus (SC) is given as an example.

Functional MRI (fMRI) is a widely used tool for non-invasively measuring correlates of human brain activity. However, its use has mostly been focused upon ...

Neuroscience

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound (30/45MHZ) System

Congenital heart defects (CHDs) are the most common cause of childhood morbidity and early mortality. Prenatal detection&#160;of the underlying molecular mechanisms of CHDs is&#160;crucial for inventing new preventive and therapeutic strategies. Mutant mouse models are powerful tools to discover new&#160;mechanisms&#160;and environmental stress modifiers that drive cardiac development and their potential&#160;alteration in CHDs. However, efforts to establish the causality of these putative contributors have been limited to histological&#160;and molecular studies&#160;in non-survival animal experiments, in which&#160;monitoring the key physiological and hemodynamic parameters is&#160;often absent. Live imaging technology has become an essential tool to establish the&#160;etiology of CHDs. In particular,&#160;ultrasound imaging can be used prenatally without surgically exposing the fetuses,&#160;allowing maintaining&#160;their baseline physiology while monitoring the impact of environmental stress&#160;on the hemodynamic and structural aspects of cardiac chamber development. Herein, we use the High-Frequency Ultrasound (30/45)&#160;system to examine the cardiovascular system in fetal mice at E18.5 in utero at the baseline and in response to prenatal hypoxia exposure. We demonstrate the feasibility of the system to measure cardiac chamber size, morphology, ventricular function, fetal heart rate, and umbilical artery flow indices, and their alterations in fetal mice exposed to systemic chronic hypoxia in utero in real time.

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System

High-frequency ultrasound imaging of the fetal mouse has improved imaging resolution and can provide precise non-invasive characterization of cardiac development and structural defects. The protocol outlined herein is designed to perform real-time fetal mice echocardiography in vivo.

Congenital heart defects (CHDs) are the most common cause of childhood morbidity and early mortality. Prenatal detection&#160;of the underlying molecular ...

Developmental Biology

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of living systems. Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using qMRI methods. The MRI acquisition protocol begins with localizer images (used to locate the position of the body and tissue of interest within the MRI system), quality control measurements of relevant magnetic field distributions, and structural imaging for general anatomical characterization. The qMRI portion of the protocol includes measurements of the longitudinal and transverse relaxation time constants (T1 and T2, respectively). Also acquired are diffusion-tensor MRI data, in which water diffusivity is measured and used to infer pathological processes such as edema. Quantitative magnetization transfer imaging is used to characterize the relative tissue content of macromolecular and free water protons. Lastly, fat-water MRI methods are used to characterize fibro-adipose tissue replacement of muscle. In addition to describing the data acquisition and analysis procedures, this paper also discusses the potential problems associated with these methods, the analysis and interpretation of the data, MRI safety, and strategies for artifact reduction and protocol optimization.

Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using non-invasive magnetic resonance imaging methods.

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of ...

Quantification of Mouse Heart Left Ventricular Function, Myocardial Strain, and Hemodynamic Forces by Cardiovascular Magnetic Resonance Imaging

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations result in pathology, and how myocardial diseases may be treated. Cardiovascular magnetic resonance imaging (CMR) has become an indispensable tool for a comprehensive in vivo assessment of cardiac anatomy and function. This protocol shows detailed measurements of mouse heart left ventricular function, myocardial strain, and hemodynamic forces using 7-Tesla CMR. First, animal preparation and positioning in the scanner are demonstrated. Survey scans are performed for planning imaging slices in various short- and long-axis views. A series of prospective ECG-triggered short-axis (SA) movies (or CINE images) are acquired covering the heart from apex to base, capturing end-systolic and end-diastolic phases. Subsequently, single-slice, retrospectively gated CINE images are acquired in a midventricular SA view, and in 2-, 3-, and 4-chamber views, to be reconstructed into high-temporal resolution CINE images using custom-built and open-source software. CINE images are subsequently analyzed using dedicated CMR image analysis software.
Delineating endomyocardial and epicardial borders in SA end-systolic and end-diastolic CINE images allows for the calculation of end-systolic and end-diastolic volumes, ejection fraction, and cardiac output. The midventricular SA CINE images are delineated for all cardiac time frames to extract a detailed volume-time curve. Its time derivative allows for the calculation of the diastolic function as the ratio of the early filling and atrial contraction waves. Finally, left ventricular endocardial walls in the 2-, 3-, and 4-chamber views are delineated using feature-tracking, from which longitudinal myocardial strain parameters and left ventricular hemodynamic forces are calculated. In conclusion, this protocol provides detailed in vivo quantification of the mouse cardiac parameters, which can be used to study temporal alterations in cardiac function in various mouse models of heart disease.

This study describes a comprehensive cardiovascular magnetic resonance imaging (CMR) protocol to quantify the left ventricular functional parameters of the mouse heart. The protocol describes the acquisition, post-processing, and analysis of the CMR images as well as assessment of different cardiac functional parameters.

Mouse models have contributed significantly to understanding genetic and physiological factors involved in healthy cardiac function, how perturbations ...

Bioengineering

Phase Contrast Magnetic Resonance Imaging in the Rat Common Carotid Artery

Phase contrast magnetic resonance imaging (PC-MRI) is a noninvasive approach that can quantify flow-related parameters such as blood flow. Previous studies have shown that abnormal blood flow may be associated with systemic vascular risk. Thus, PC-MRI can facilitate the translation of data obtained from animal models of cardiovascular diseases to pertinent clinical investigations. In this report, we describe the procedure for measuring blood flow in the common carotid artery (CCA) of rats using cine-gated PC-MRI and discuss relevant analysis methods. This procedure can be performed in a live, anesthetized animal and does not require euthanasia after the procedure. The proposed scanning parameters yield repeatable measurements for blood flow, indicating excellent reproducibility of the results. The PC-MRI procedure described in this article can be used for pharmacological testing, pathophysiological assessment, and cerebral hemodynamics evaluation.

The overall goal of this procedure is to measure the blood flow in the rat common carotid artery by using noninvasive phase contrast magnetic resonance imaging.

Phase contrast magnetic resonance imaging (PC-MRI) is a noninvasive approach that can quantify flow-related parameters such as blood flow. Previous ...

MRI-Arterial Spin Labeling Integration to Detect and Monitor Cerebral Blood Flow 

Construction and Application of Cerebral Functional Region-Based Cerebral Blood Flow Atlas Using Magnetic Resonance Imaging-Arterial Spin Labeling

Cerebral conditions often require precise diagnosis and monitoring, necessitating advanced imaging techniques. Current modalities may not adequately detect early signs of reversible tissue damage, underlining the need for innovative diagnostic tools that can quantify changes in cerebral blood flow (CBF) with high specificity and sensitivity.&#160;This study integrates three-dimensional arterial spin labeling (3D-ASL) with structural MRI to develop comprehensive CBF atlases that cover all main functional regions of the brain. This innovative magnetic resonance imaging- arterial spin labeling (MRI-ASL) methodology provides a rapid and noninvasive means of quantifying region-specific CBF, offering a detailed view of CBF levels across different functional regions.The comparison between chronic cerebral ischemia (CCI) patients and healthy subjects revealed significantly diminished CBF across the cerebral functional regions in the constructed CBF atlases for the former. This approach not only allows for the efficient identification of CCI by analyzing concurrent decreases in CBF across critical areas relative to healthy distributions but also enables the tracking of treatment responses and rehabilitation progress through longitudinal CBF atlases.The CBF atlas developed using the MRI-ASL technique represents a novel advancement in the field of cerebral diagnostics and patient care. By comparing regional CBF levels against normative standards, this method enhances diagnostic capabilities, enabling clinicians to provide personalized care to patients with cerebral conditions.

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders

This study integrated magnetic resonance imaging- arterial spin labeling images to derive cerebral blood flow (CBF) atlas for cerebral functional regions. Comparing typical healthy and chronic cerebral ischemia CBF atlases revealed significant differences in regional CBF distributions, enabling rapid, noninvasive assessments of functional CBF to assist in diagnosis and evaluate therapeutics.

Cerebral conditions often require precise diagnosis and monitoring, necessitating advanced imaging techniques. Current modalities may not adequately ...

Ultrafast Doppler Ultrasound for Hepatic Microvasculature Analysis in Mice

Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound

Non-invasive in vivo imaging of the vasculature is a powerful tool for studying disease mechanisms in rodents. To achieve high sensitivity imaging of the microvasculature using Doppler ultrasound methods, imaging modalities employing the concept of ultrafast imaging are preferred. By increasing the frame rate of the ultrasound scanner to thousands of frames per second, it becomes possible to improve the sensitivity of the blood flow down to 2 mm/s and to obtain functional information about the microcirculation in comparison to a sensitivity of around 1 cm/s in conventional Doppler modes. While Ultrafast Doppler ultrasound (UFUS) imaging has become adopted in neuroscience, where it can capture brain activity through neurovascular coupling, it presents greater challenges when imaging the vasculature of abdominal organs due to larger motions linked to breathing. The liver, positioned anatomically under the diaphragm, is particularly susceptible to out-of-plane movement and oscillating respiratory motion. These artifacts not only adversely affect Doppler imaging but also complicate the anatomical analysis of vascular structures and the computation of vascular parameters. Here, we present a qualitative and quantitative imaging analysis of the hepatic vasculature in mice by UFUS. We identify major anatomical vascular structures and provide graphical illustrations of the hepatic macroscopical anatomy, comparing it to an in-depth anatomical assessment of the hepatic vasculature based on Doppler readouts. Additionally, we have developed a quantification protocol for robust measurements of hepatic blood volume of the microvasculature over time. To contemplate further research, qualitative vascular analysis provides a comprehensive overview and suggests a standardized terminology for researchers working with mouse models of liver disease. Furthermore, it offers the opportunity to apply ultrasound as a non-invasive complementary method to inspect hepatic vascular defects in vivo and measure functional microvascular alterations deep within the organ before unraveling blood vessel anomalies at the micron scale levels using ex vivo staining on tissue sections.

Ultrafast Doppler ultrasound (UFUS) with high spatial resolution (100 &#956;m) and sensitivity represents a suitable noninvasive imaging modality for obtaining a comprehensive qualitative overview of the hepatic vasculature. UFUS also facilitates quantitative measurements of the microvasculature, aiming to enhance our understanding of vascular disease mechanisms.

Non-invasive in vivo imaging of the vasculature is a powerful tool for studying disease mechanisms in rodents. To achieve high sensitivity imaging of the ...

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Imaging and Quantification of the Hepatic Vasculature of Mice Using Ultrafast Doppler Ultrasound