This research was supported by the Basic Science Research Program through the National Research Foundation of Korea, which is funded by the Ministry of Education (2021R1I1A3040346, 2020R1A4A1019475, 2021R1C1C1003481, and HI19C0760). This study was also supported by 2018 Research Grant (PoINT) from Kangwon National University.

NOTE: The protocol is largely composed of three stages: (1) model fabrication, (2) MRI scan and parameter selection, and (3) data analysis. Figure 1 is a flow diagram showing the overall process of the protocol.
1. Model fabrication
<ol>
	<li>Aortic root model
	<ol>
		<li>As shown in Figure 2, determine the parameter values of the aortic root, such as valve base diameter and sinus radius. For this experiment, the values were DA = 32.24 mm, DO = 26 mm, LB = 8.84 mm, LA = 26 mm, rmin = 16.64 mm, rmax = 21.32 mm.</li>
		<li>Run the 3D modeling software by clicking Sketch &#62; Tools Sketch Tools &#62; Sketch Picture. 
		NOTE: Solidwork is used for 3D modeling in the experiment.</li>
		<li>To make a sinus model, sketch circles corresponding to rmax and rmin using the circle tool. Draw a curved line of the sinus using the free curve function11, click Loft Tool and select the sketch area for loft.</li>
		<li>Sketch additional circles on the top and bottom of the current model, click Extrude Tool, and select the circles. Set the options as 20 mm downward and 30 mm upward. Make a hexahedron model of size 100 mm x 100 mm x 76 mm in the same way.</li>
		<li>Click Combine Tool from Insert &#62; Features &#62; Combine. Select Subtract in the property manager. Select the hexahedron model and the sinus model. Fabricate the final design as an acrylic model with a 5-axis CNC machine as per manufacturer&#39;s instruction.</li>
	</ol>
	</li>
	<li>Valve frame
	<ol>
		<li>Run 3D modeling software and open a new sketch. Draw a square of size 100 mm x 100 mm and a circle of 25 mm in the center for the valve base, manually. Click the Extrude Tool and adjust the height of the valve base to 5 mm.</li>
		<li>Extrude the circle with a height of 23.5 mm and a thickness of 3 mm thick. Divide the model into 12 uniform pieces using Line Tool so that each piece has 30&#176;. Select three pieces with 120&#176; intervals and extrude with a height of 16.5 mm to make three pillars.</li>
		<li>Click Fillet Tool and select the pillars. Adjust the fillet radius at the top and bottom as 4 mm and 10 mm, respectively. Save it in an STL file format.</li>
		<li>3D-print the valve frame. Set the infill density to 100% and use acrylonitrile butadiene styrene as fill material. See Figure 3 for the shape and dimensions of the aortic valve frame.</li>
	</ol>
	</li>
	<li>Aortic regurgitation model using expanded polytetrafluoroethylene (ePTFE)
	<ol>
		<li>Run the 3D modeling software and open a new sketch. Draw a horizontal line of 23.24 mm and a vertical line of 15 mm with reference to Figure 4A. 
		NOTE: The geometric parameters of the valve&#39;s base, height, and leaflet free-edge length were chosen according to a previous study12.</li>
		<li>Click 3 Point Arc Tool from the arc command manager and set two points on each end of the horizontal line and the last point on the end of the vertical line. Extrude the sketch with a thickness of 5 mm. Export the model with STL file format and 3D print it.</li>
		<li>Overlap the ePTFE membrane in two layers and draw three leaflet borders at intervals of 2 mm using the printed leaflet. Suture along the drawn lines and side borders at 1 mm intervals with a polyamide suture with a diameter of 0.1 mm. Suture the ePTFE valve from top to bottom on the frame at 1 mm intervals.</li>
		<li>Cut the outer side of the membrane and suture it with each other. Perform the following three modifications to obtain three different models.
		<ol>
			<li>Dilatation model: Reduce the ratio of the designed leaflet parameters to 90%.</li>
			<li>Perforation model: Make a circular hole with a diameter of 2 mm using scissors in the center of one leaflet.</li>
			<li>Prolapse: Fix the two commissures of the valve at a hole with a low post height. 
			NOTE: Figure 4 shows the materials and fabrication method of ePTFE valve. Figure 5 shows the characteristics of each AR-type.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
2. MRI scan and parameter selection
<ol>
	<li>Prepare the experimental system consisting of an AR model, aortic sinus model, a heart simulation pump, and MRI.</li>
	<li>Set the experiment models in the MRI room and connect the pump, reservoir, and models using a 25 mm (inner diameter) silicone tube. Use a 10 cm long cable tie to fasten the connection parts to prevent possible leakage.</li>
	<li>Use a motor-controlled piston pump to simulate the aortic blood flow waveforms to generate a physiological flow waveform through the flow circuit system. Use water as the working fluid and attach one-way valves to the inlet and outlet to prevent backflow. Details of the flow pump can be found in the previous study23.</li>
	<li>Locate the model within the field of view (FOV) of the MRI. Perform a scout scan to observe phantom images in the coronal, axial, and sagittal views in MRI operating console monitor. This image is used as a guide to position the following image sequences.</li>
	<li>Locate the 2D image plane in the center of the aorta model. Run a variable velocity-encoding parameter (VENC) 2D phase-contrast imaging to select the most appropriate VENC value for 4D flow MRI.</li>
	<li>Set VENC to a 10% higher value in 4D flow MRI to minimize possible velocity aliasing7. Enter the desired spatial resolution and the temporal resolution on the MRI console. The spatial and temporal resolution for the aortic flow is recommended to be 2-3 mm and 20-40 ms, respectively7. Table 2 shows the MRI scan parameters.</li>
	<li>Acquire data for both with and without flow using the 3 types of AR valves and the without valve.</li>
</ol>
3. Data analysis
<ol>
	<li>Data sorting and correction
	<ol>
		<li>Copy raw data files from the scanner to proceed with the data analysis. Sort the dicom files according to the header named series description using the Dicom sort software. Click Sort Images in Dicom sort software to sort three-directional phase images and magnitude images in separate folders.</li>
		<li>Load magnitude image into the ITK-snap software. Click Brush in the ITK-snap and manually paint the internal fluid region of the phantom using the brush tool. Save segmented image.</li>
		<li>(Optional) Load both phase image data obtained with the flow on and off using MATLAB. Subtract the data with the flow by the data without flow to remove background errors. Repeat this for every direction and cardiac cycle.</li>
		<li>Calculate the velocity of 5D matrix phase data (row x column x slice x direction x time) using a vendor-specific pixel-to-velocity equation. In general, the maximum intensity of the pixel corresponds to the selected VENC value.</li>
	</ol>
	</li>
	<li>Visualization
	<ol>
		<li>Load the 5D matrix velocity from step 3.1.4 into flow visualization analysis software. 
		NOTE: Input velocity matrix may vary according to the analysis software. Ensight users should follow Ensight gold case format guide13.</li>
		<li>Click the Isosurface Part, change the data type from isosurface to isovolume for 3D analysis by clicking the Isovolume button. Drag the speed data in the variables command manager, add it to the isovolume to check the velocity distribution of the model.</li>
		<li>Click Particle Trace Emitters Tool in the main menu. Check Advanced Option for a more accurate analysis. Select the desired visualization such as Streamlines or Pathlines in creation.</li>
		<li>For this experiment, set the following value: Emit From Option = Part, Part ID = 2, No. of Emitters = 10000, Direction = +/-. Create and check the results over time.</li>
		<li>Right-click the Particle Trace model and click the Color by. Select the velocity component to color the streamline with the velocity.</li>
	</ol>
	</li>
	<li>Quantification
	<ol>
		<li>Load the velocity data (step 3.1.4) and segmented image (step 3.1.2) onto MATLAB. Set the velocity outside of the segmentation region to zero. This can be easily performed by elementwise multiplying the segmented matrix data and the velocity matrix data.</li>
		<li>Check if the velocity data has phase-wrapping using the Imshow function of MATLAB. Inversion of the velocity direction indicates phase-wrapping.</li>
		<li>Slice the desired plane of the matrix data. Sum all velocity data within the plane and multiply spatial resolution to calculate the flow rate through the plane. Sum all flow rates throughout the cardiac cycle and multiply the temporal resolution to calculate the stroke volume.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

Four-dimensional flow MRI has recently been verified by various ex vivo and in vivo studies as an application for clinical routine use14. As the 4D flow MRI obtains 3D velocity information over the entire cardiac cycle, one strong application is a direct quantification of the valvular regurgitant volume, which conventional 2D Doppler echocardiography is not capable of quantifying15. In vitro experiments using 4D Flow MRI can provide the 3D flow velocity and related hemodynamic parameters which can be used for investigating the relationship between cardiovascular disease and hemodynamics. However, despite its promising capability, no systematic studies on this application have been reported yet. This is possibly due to the lack of well-controlled in vitro experiments that mimic the regurgitation of the tri-leaflet valves.
Recent developments in in vitro studies have provided more accurate and realistic experimental methods to access the pre- and post-valvular hemodynamics16,17. Coupled with an optical image-based particle image velocimetry (PIV), accurate measurement and quantification of the flow around the valve was possible in previous in vitro studies18. However, accurate 3D flow fields, especially for the post-valvular flow, were limited owing to the opaque model and refraction. On the other hand, 3D velocity measurements using MRI were also limited, as metal components cannot be used19,20.
Hence in this study, a protocol to build a flow experimental platform that is MR compatible and highly modifiable to reproduce various clinical scenarios of valvular diseases is introduced. The ePTFE membrane is used to mimic the tricuspid valve without metal components as it has been widely used as a valve and vascular graft material due to its high tensile strength and chemical resistance17,21,22. Based on ePTFE films, three different origins of the AR have been reproduced (dilatation, perforation, and prolapse) as well as a model without a valve for comparison. The next important step in this flow experimental protocol is MR imaging and quantification. A motor-controlled piston pump that can simulate the aortic blood flow waveforms is used to generate a physiological flow waveform through the flow circuit system. Details of the flow pump can be found in the previous study23. As this study also aims to validate the accuracy of the 4D flow MRI in flow quantification, all the imaging parameters are selected based on the previous study which summarizes the parameters that can be used in the clinical routine24. As the MRI system includes inherent errors due to imperfections such as eddy currents and nonlinearity of the magnetic field25, the background correction strategy is applied prior to the actual data quantification as described in step 3.1.3.
The hand-made aortic regurgitation model suggested in this study showed similar hemodynamic characteristics of regurgitant jet according to model classification as previous studies reported26,27. The closed shape was symmetrical, and a straight jet occurred at the center of the valve in the dilatation model. A posteriorly directed eccentric jet appears owing to cusp damage in the perforation model. Partial prolapse of the valve shows a jet whose direction was bent from the culprit cup owing to limited mobility. The aortic regurgitation volume directly measured using the 4D flow MRI was overestimated in the without valve and dilatation model, while it was largely underestimated in the prolapse model when compared with the ground truth. However, when the regurgitant fraction was calculated, the largest bias was only 11% in the prolapse model. This strongly indicates that not only the regurgitant flow but also the normal aortic jet was affected by the MR scan. At the current stage, individual scan parameters were not optimized for each AR model. A future systemic parameter study may improve the accuracy of regurgitant volume measurement. Alternatively, the use of regurgitant fraction is more robust as it cancels out the inherent errors in 4D flow MRI but also is clinically more relevant than simply measuring the absolute regurgitant volume.
In conclusion, this study suggests an MR compatible in vitro flow experimental model that is highly modifiable to simulate various types of AR. Also, the accuracy of AR volume measurement using 4D flow MRI was compared. The limitation of this study is that the motion of the aortic valve was not simulated, which can affect the actual development of the regurgitant jet. In addition, the partial volume effect and temporal averaging nature of the 4D-flow MRI may limit the accuracy of the flow measurement, especially considering the high dynamic range of velocity within the jet and surroundings. Therefore, further systematic parameter study is required.

Aortic regurgitation (AR) refers to the backward flow from the aorta into the left ventricle during the diastolic phase of the ventricle. AR is typically classified into aortic dilatation, cups prolapse, cups perforation, cups retraction, and others1. Chronic AR may cause the volume overload of the LV mainly due to hypertrophy and dilatation, and eventually causes its decompensation2. Acute AR is mainly caused by infectious endocarditis, aortic dissection, and traumatic rupture, which leads to hemodynamic emergencies2.
Current clinical standards for AR diagnosis are mainly based on transthoracic echocardiography (TTE) or transesophageal echocardiography (TEE)3. Despite the advantages of real-time imaging and short exam time, the accuracy of echocardiography is highly operator-dependent. Especially for the regurgitant volume measurement, direct measurement of the regurgitant volume is limited as the regurgitant jet shifts out of the two-dimensional (2D) measurement plane due to the motion of the aortic valve. Indirect estimation using proximal iso-velocity surface area (PISA) methods are often used, but assumptions such as circular orifice area often limit the accurate measurement4.
Recent medical guidelines5 also recommend cardiac MR (CMR), especially for moderate or severe AR patients to compensate for the limitation of echocardiography by measuring the mass and global function of the LV. Structural parameters such as aortic leaflets and LV size, and flow parameters such as jet width, vena contracta width, and regurgitant volume can also be comprehensively considered in AR diagnosis6. However, aortic regurgitation volume estimated with the LV global function may fail especially for patients with other heart valvular diseases or shunt.
Alternatively, 4D flow MRI has been considered as a promising technique that can directly measure the regurgitant volume with time-resolved velocity information within the volume of interest7. The motion of the valve according to the time can be easily tracked and compensated when measuring the regurgitant flow volume8,9. Also, an arbitrary plane perpendicular to the regurgitant jet can be retrospectively positioned, which increases the accuracy of the measurement10. However, as the 4D flow MRI inherently obtains the spatiotemporally averaged information, the accuracy of this technique still warrants validation by using well-controlled in vitro flow experiments.
This study aims to (i) develop MRI compatible in vitro experimental platform that can reproduce the different clinical scenarios of AR (dilatation, perforation, and prolapse) and (ii) enrich our understanding of 4D flow MRI performance in quantifying different AR at these AR models. In addition, 3D hemodynamic visualization and quantification based on 4D flow MRI were conducted according to the various clinical scenarios. This protocol is not limited to AR and can be extended to other types of valvular disease studies that require a series of in vitro experiments and hemodynamic quantification.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3D modeling software(SolidWorks)</td>
			<td>Dassault Syst&#232;mes SolidWorks Corporation</td>
			<td></td>
			<td>Waltham, MA, USA</td>
		</tr>
		<tr>
			<td>3D printer</td>
			<td>Zortrax S.A.</td>
			<td></td>
			<td>the construction of a three-dimensional object from a CAD model or a digital 3D model,(zortrax m200 plus, Zortrax S.A.,Olsztyn, Poland)</td>
		</tr>
		<tr>
			<td>Dicom sort</td>
			<td>Open source software</td>
			<td></td>
			<td>Jonathan Suever, Software Engineer</td>
		</tr>
		<tr>
			<td>Ensight</td>
			<td>Ansys</td>
			<td></td>
			<td>Flow visualization software (Canonsburg, PA, USA).</td>
		</tr>
		<tr>
			<td>Expanded Polytetrafluoroethylene(ePTFE)</td>
			<td>SANG-A-FRONTEC</td>
			<td></td>
			<td>Medical membrane (ePTFE,SANG-A-FRONTEC, Incheon, korea)</td>
		</tr>
		<tr>
			<td>Itk snap software</td>
			<td>Open source software</td>
			<td></td>
			<td>GNU General Public License,</td>
		</tr>
		<tr>
			<td>MATLAB</td>
			<td>MathWorks</td>
			<td></td>
			<td>Natick, MA, USA</td>
		</tr>
		<tr>
			<td>MRI</td>
			<td>Siemens</td>
			<td></td>
			<td>3T, Erlangen, Germany</td>
		</tr>
		<tr>
			<td>Scissors</td>
			<td>Scanlan International Inc</td>
			<td>n43 1765</td>
			<td>7007-454, Scanlan International Inc., Saint Paul, USA</td>
		</tr>
		<tr>
			<td>Suture</td>
			<td>AILEE</td>
			<td>NB530</td>
			<td>Ailee, Polyamide suture, UPS 5-0</td>
		</tr>
	</tbody>
</table>

in vitro assessment of aortic regurgitation using four-dimensional flow magnetic resonance imaging

Aortic regurgitation (AR) refers to backward blood flow from the aorta into the left ventricle (LV) during ventricular diastole. The regurgitant jet arising from the complex shape is characterized by the three-dimensional flow and high-velocity gradient, sometimes limiting an accurate measurement of the regurgitant volume using 2D echocardiography. Recently developed four-dimensional flow magnetic resonance imaging (4D flow MRI) enables three-dimensional volumetric flow measurements, which can be used to accurately quantify the amount of the regurgitation. This study focuses on (i) magnetic resonance compatible AR model fabrication (dilatation, perforation, and prolapse) and (ii) systematic analysis of the performance of 4D flow MRI in AR quantification. The results indicated that the formation of the forward and backward jets over time was highly dependent on the types of AR origin. The amount of regurgitation volume bias for the model types were -7.04%, -33.21%, 6.75%, and 37.04% compared to the ground truth (48 mL) volume measured from the pump stroke volume. The largest error of the regurgitation fraction was around 12%. These results indicate that careful selection of imaging parameters is required when absolute regurgitation volume is important. The suggested in vitro flow phantom can easily be modified to simulate other valvular diseases such as aortic stenosis or bicuspid aortic valve (BAV) and can be used as a standard platform to test different MRI sequences in the future.

Three representative classes of aortic regurgitation models were fabricated, and one case without a valve was fabricated for comparison (Figure 3). The dilation model clearly showed incomplete closure of the valve leaflet due to the smaller-sized leaflets. A hole was punctured on one of the leaflets using scissors to mimic the perforation model. One leaflet of the prolapse model looked smaller than the other two leaflets because the two commissures were sutured at a position lower than the original height. There were no significant differences from the top view.
With the 3D velocity information acquired over time using 4D flow MRI, streamlines of normal and regurgitation jets were visualized during systole and diastole (Figure 6). The forward jet was straight in all models except for the perforation model. In the perforation model, a wall-biased jet occurred during the systole phase. The regurgitating jet showed a different velocity and shape according to the AR classification. In the case of without a valve, an overall forward and backward flow occurred. The regurgitant jet of the dilation model came out from the center and tended to change directions over time. The perforation and prolapse model regurgitant jet leaned toward the wall. The peak velocity of the forward and regurgitant jet was 0.28 m/s, -0.29 m/s in the model without valve, 2.03 m/s, -3.53 m/s in the dilatation model, 2.52 m/s, -3.13 m/s in the perforation model, and 2.76 m/s, -2.88 m/s in the prolapse model.
Figure 7&#160;shows the flow rate for each valve and the forward and regurgitant volumes in a 3D plane away from the valve base. The flow rates showed different waveforms and quantities for each model. The amount of regurgitation volume was 51.38 mL, 63.94 mL, 44.76 mL, and 30.22 mL for without valve, dilatation, perforation, and prolapse models, respectively. The bias for without valve, dilatation, perforation, and prolapse model were -7.04%, -33.21%, 6.75%, and 37.04%, respectively, compared to the ground truth (48 mL) measured from the pump stroke volume. The positive percentage values indicate underestimation while the negative percentage values represent over estimation. The regurgitation fraction error was -7.78%, -6.00%, 0.33% and -11.18% for without valve, dilatation, perforation and prolapse model, respectively.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/63491/63491fig01.jpg" /> 
Figure 1: Workflow diagram of the protocol. This experimental protocol mainly consists of model fabrication, MRI scan, and data analysis. In the model fabrication step, the outer aortic root model and four different types of AR model (without valve, dilatation, prolapse, and perforation) are fabricated. During the MRI scan, scout imaging followed by multi-VENC scan and 4D flow MRI is performed. The data analysis part includes data sorting, image segmentation, velocity calculation, visualization, and quantification. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig01large.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/63491/63491fig02.jpg" /> 
Figure 2: Schematic and designed acrylic model of the aortic root (A) Geometrical characterization and parameters of the aortic root geometry. (B) Aortic root 3D model in multi-dimensional view. DA: diameter of sinotubular junction (STJ), DO: diameter of annulus, rmax: maximum sinus diameter, rmin: minimum sinus diameter, LA: height of sinus, LB: height of STJ. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/63491/63491fig03.jpg" /> 
Figure 3: Aortic regurgitation frame and model (A) Geometrical information of the aortic valve frame which is used to hold the leaflet. Holes around the body of the frame is where the suture line passes. (B) Example of ePTFE membrane sutured valve. (C) En-face view of the in vitro models: without valve, dilation, perforation and prolapse fabricated in this study. The arrow indicates the damaged cusp. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig03large.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/63491/63491fig04.jpg" /> 
Figure 4: Material and fabrication step of ePTFE leaflet. (A) Using 3D printed leaflets as a guide, leaflets are made using ePTFE membrane. (B) Drawing, suturing, cutting and fixing steps of the ePTFE valve. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/63491/63491fig05.jpg" /> 
Figure 5: Fabrication methods of different AR models. (A) Dilatation model, (B) perforation model, and (C) prolapse model. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/63491/63491fig06.jpg" /> 
Figure 6: Streamline visualization according to aortic regurgitation type. A streamline visualization at systole (left of each panel) and diastole (right of each panel) according to aortic regurgitation type. (A) Model without valve (the diastole/systole image are the same due to lack of a valve), (B) dilatation, (C) perforation, and (D) prolapse. Systole and diastole data were taken where the inlet velocity is the highest and the lowest during the cardiac cycle. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/63491/63491fig07.jpg" /> 
Figure 7: Flow rate and stroke volume. The flow rate and stroke volume for (A) model without valve, (B) dilatation, (C) perforation, and (D) prolapse. The flow rate and stroke volume are measured at the plane (solid line) three-diameter downstream to the valve annulus.&#160;The blue and red colors indicate the forward and regurgitating flows, respectively. <a href="https://www.jove.com/files/ftp_upload/63491/63491fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td rowspan="2">Ratio 
			(Do= 26 mm)</td>
			<td>DA/Do</td>
			<td>LA/Do</td>
			<td>LB/Do</td>
			<td>rmax/Do</td>
			<td>rmin/Do</td>
		</tr>
		<tr>
			<td>1.24</td>
			<td>1</td>
			<td>0.34</td>
			<td>0.82</td>
			<td>0.64</td>
		</tr>
	</tbody>
</table>
Table 1. Geometrical parameters of the aortic root geometry shown in Figure1.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Temporal resolution</td>
			<td>0.025 ms/40 phases</td>
		</tr>
		<tr>
			<td>Spatial resolution</td>
			<td>2mm x 2mm/0.5 pixel per 1 mm</td>
		</tr>
		<tr>
			<td>Matrix</td>
			<td>96 x 160 x 26 pixel</td>
		</tr>
		<tr>
			<td>Slice thickness</td>
			<td>2 mm</td>
		</tr>
		<tr>
			<td>Echo time</td>
			<td>2.54 ms</td>
		</tr>
		<tr>
			<td>Encoding velocity</td>
			<td>25-330 cm/s</td>
		</tr>
	</tbody>
</table>
Table 2. 4D Flow MRI sequence parameters in vitro.

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In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Aortic regurgitation is an aortic valve heart disease. This manuscript demonstrates how four-dimensional flow magnetic resonance imaging can evaluate aortic regurgitation using in vitro heart valves mimicking aortic regurgitation.

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Aortic regurgitation (AR) refers to backward blood flow from the aorta into the left ventricle (LV) during ventricular diastole. The regurgitant jet ...

in-vitro-assessment-aortic-regurgitation-using-four-dimensional-flow

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3.2K Views.  Kangwon National University. Aortic regurgitation is an aortic valve heart disease. This manuscript demonstrates how four-dimensional flow magnetic resonance imaging can evaluate aortic regurgitation using in vitro heart valves mimicking aortic regurgitation.

Video: In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging

Determining 3D Flow Fields via Multi-camera Light Field Imaging

In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and observed phenomena in fluid flows. Thus, a need exists for an accessible method capable of resolving three-dimensional (3D) data sets for a range of problems. We present a novel technique for performing quantitative 3D imaging of many types of flow fields. The 3D technique enables investigation of complicated velocity fields and bubbly flows. Measurements of these types present a variety of challenges to the instrument. For instance, optically dense bubbly multiphase flows cannot be readily imaged by traditional, non-invasive flow measurement techniques due to the bubbles occluding optical access to the interior regions of the volume of interest. By using Light Field Imaging we are able to reparameterize images captured by an array of cameras to reconstruct a 3D volumetric map for every time instance, despite partial occlusions in the volume. The technique makes use of an algorithm known as synthetic aperture (SA) refocusing, whereby a 3D focal stack is generated by combining images from several cameras post-capture 1. Light Field Imaging allows for the capture of angular as well as spatial information about the light rays, and hence enables 3D scene reconstruction. Quantitative information can then be extracted from the 3D reconstructions using a variety of processing algorithms. In particular, we have developed measurement methods based on Light Field Imaging for performing 3D particle image velocimetry (PIV), extracting bubbles in a 3D field and tracking the boundary of a flickering flame. We present the fundamentals of the Light Field Imaging methodology in the context of our setup for performing 3DPIV of the airflow passing over a set of synthetic vocal folds, and show representative results from application of the technique to a bubble-entraining plunging jet.

A technique for performing quantitative three-dimensional (3D) imaging for a range of fluid flows is presented. Using concepts from the area of Light Field Imaging, we reconstruct 3D volumes from arrays of images. Our 3D results span a broad range including velocity fields and multi-phase bubble size distributions.

In the field of fluid mechanics, the resolution of computational schemes has outpaced experimental methods and widened the gap between predicted and ...

Measuring Material Microstructure Under Flow Using 1-2 Plane Flow-Small Angle Neutron Scattering

A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is presented. The SANS shear cell consists of a concentric cylinder Couette geometry that is sealed and rotating about a horizontal axis so that the vorticity direction of the flow field is aligned with the neutron beam enabling scattering from the 1-2 plane of shear (velocity-velocity gradient, respectively). This approach is an advance over previous shear cell sample environments as there is a strong coupling between the bulk rheology and microstructural features in the 1-2 plane of shear. Flow-instabilities, such as shear banding, can also be studied by spatially resolved measurements. This is accomplished in this sample environment by using a narrow aperture for the neutron beam and scanning along the velocity gradient direction. Time resolved experiments, such as flow start-ups and large amplitude oscillatory shear flow are also possible by synchronization of the shear motion and time-resolved detection of scattered neutrons. Representative results using the methods outlined here demonstrate the useful nature of spatial resolution for measuring the microstructure of a wormlike micelle solution that exhibits shear banding, a phenomenon that can only be investigated by resolving the structure along the velocity gradient direction. Finally, potential improvements to the current design are discussed along with suggestions for supplementary experiments as motivation for future experiments on a broad range of complex fluids in a variety of shear motions.

A shear cell is developed for small-angle neutron scattering measurements in the velocity-velocity gradient plane of shear and is used to characterize complex fluids. Spatially resolved measurements in the velocity gradient direction are possible for studying shear-banding materials. Applications include investigations of colloidal dispersions, polymer solutions, and self-assembled structures.

A new small-angle neutron scattering (SANS) sample environment optimized for studying the microstructure of complex fluids under simple shear flow is ...

Phase Diagram Characterization Using Magnetic Beads as Liquid Carriers

Magnetic beads with ~1.9 &#181;m average diameter were used to transport microliter volumes of liquids between contiguous liquid segments with a tube for the purpose of investigating phase change of those liquid segments. The magnetic beads were externally controlled using a magnet, allowing for the beads to bridge the air valve between the adjacent liquid segments. A hydrophobic coating was applied to the inner surface of the tube to enhance the separation between two liquid segments. The applied magnetic field formed an aggregate cluster of magnetic beads, capturing a certain liquid amount within the cluster that is referred to as carry-over volume. A fluorescent dye was added to one liquid segment, followed by a series of liquid transfers, which then changed the fluorescence intensity in the neighboring liquid segment. Based on the numerical analysis of the measured fluorescence intensity change, the carry-over volume per mass of magnetic beads has been found to be ~2 to 3 &#181;l/mg. This small amount of liquid allowed for the use of comparatively small liquid segments of a couple hundred microliters, enhancing the feasibility of the device for a lab-in-tube approach. This technique of applying small compositional variation in a liquid volume was applied to analyzing the binary phase diagram between water and the surfactant C12E5 (pentaethylene glycol monododecyl ether), leading to quicker analysis with smaller sample volumes than conventional methods.

Here, we present a protocol to investigate multi-component phase diagrams using externally controlled magnetic beads as liquid carriers in a lab-in-tube approach. This approach can aid in applications that seek to gather further information on phase change in complex liquid systems.

Magnetic beads with ~1.9 &#181;m average diameter were used to transport microliter volumes of liquids between contiguous liquid segments with a tube for ...

Use of a Multi-compartment Dynamic Single Enzyme Phantom for Studies of Hyperpolarized Magnetic Resonance Agents

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due to fundamental constraints imposed by the hyperpolarized state, exotic imaging and reconstruction techniques are commonly used. A practical system for characterization of dynamic, multi-spectral imaging methods is critically needed. Such a system must reproducibly recapitulate the relevant chemical dynamics of normal and pathological tissues. The most widely utilized substrate to date is hyperpolarized [1-13C]-pyruvate for assessment of cancer metabolism. We describe an enzyme-based phantom system that mediates the conversion of pyruvate to lactate. The reaction is initiated by injection of the hyperpolarized agent into multiple chambers within the phantom, each of which contains varying concentrations of reagents that control the reaction rate. Multiple compartments are necessary to ensure that imaging sequences faithfully capture the spatial and metabolic heterogeneity of tissue. This system will aid the development and validation of advanced imaging strategies by providing chemical dynamics that are not available from conventional phantoms, as well as control and reproducibility that is not possible in vivo.

A multi-compartment dynamic phantom is used to simulate some biology of interest for metabolic studies using hyperpolarized magnet resonance agents.

Imaging of hyperpolarized substrates by magnetic resonance shows great clinical promise for assessment of critical biochemical processes in real time. Due ...

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve geologic seals and allow CO2 to escape. However, the dissolution processes at reservoir conditions are poorly understood. Thus, time-resolved experiments are needed to observe and predict the nature and rate of dissolution at the pore scale. Synchrotron fast tomography is a method of taking high-resolution time-resolved images of complex pore structures much more quickly than traditional &#181;-CT. The Diamond Lightsource Pink Beam was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 hours. The images were segmented and the porosity and permeability were measured using image analysis and network extraction. Porosity increased uniformly along the length of the sample; however, the rate of increase of both porosity and permeability slowed at later times.

Synchrotron fast tomography was used to dynamically image dissolution of limestone in the presence of CO2-saturated brine at reservoir conditions. 100 scans were taken at a 6.1 &#181;m resolution over a period of 2 h.

Underground storage permanence is a major concern for carbon capture and storage. Pumping CO2 into carbonate reservoirs has the potential to dissolve ...

Frequency Mixing Magnetic Detection Scanner for Imaging Magnetic Particles in Planar Samples

The setup of a planar Frequency Mixing Magnetic Detection (p-FMMD) scanner for performing Magnetic Particles Imaging (MPI) of flat samples is presented. It consists of two magnetic measurement heads on both sides of the sample mounted on the legs of a u-shaped support. The sample is locally exposed to a magnetic excitation field consisting of two distinct frequencies, a stronger component at about 77 kHz and a weaker field at 61 Hz. The nonlinear magnetization characteristics of superparamagnetic particles give rise to the generation of intermodulation products. A selected sum-frequency component of the high and low frequency magnetic field incident on the magnetically nonlinear particles is recorded by a demodulation electronics. In contrast to a conventional MPI scanner, p-FMMD does not require the application of a strong magnetic field to the whole sample because mixing of the two frequencies occurs locally. Thus, the lateral dimensions of the sample are just limited by the scanning range and the supports. However, the sample height determines the spatial resolution. In the current setup it is limited to 2 mm. As examples, we present two 20 mm &#215; 25 mm p-FMMD images acquired from samples with 1 &#181;m diameter maghemite particles in silanol matrix and with 50 nm magnetite particles in aminosilane matrix. The results show that the novel MPI scanner can be applied for analysis of thin biological samples and for medical diagnostic purposes.

A scanner for imaging magnetic particles in planar samples was developed using the planar frequency mixing magnetic detection technique. The magnetic intermodulation product response from the nonlinear nonhysteretic magnetization of the particles is recorded upon a two-frequency excitation. It can be used to take 2D images of thin biological samples.

The setup of a planar Frequency Mixing Magnetic Detection (p-FMMD) scanner for performing Magnetic Particles Imaging (MPI) of flat samples is presented. ...

In Vitro Culture of Epicardial Cells From Mouse Embryonic Heart

During embryogenesis, the epicardial contribution to coronary vasculature development has been very well established. Cells derived from the epicardium differentiate into smooth muscle cells, fibroblasts and endothelial cells that contribute to the formation of coronary vessels. Here we have established an in vitro culture method for embryonic epicardial cells. Using genetic labelling, we have demonstrated that the majority of the migrating cells in our explant culture are of epicardial origin. Epicardial explant cells also retain the expression of epicardial markers (Wt1 and Tbx18). Furthermore, we provide evidence that epicardial explant cells undergo epithelial to mesenchymal transition (EMT), migrate and differentiate into smooth muscle cells after Transforming growth factor beta 1 (TGF-&#946;1) treatment in a manner indistinguishable from that of epicardial cells in vivo. In conclusion, we provide a novel method for the culture of embryonic epicardial cells, which will help to explore the role of specific genes in epicardial cell biology.

In Vitro Culture of Epicardial Cells From Mouse Embryonic Heart

The epicardium is an essential source of multipotent cardiovascular progenitor cells and paracrine factors that are required for cardiovascular development and regeneration. We describe here a method to culture mouse embryonic epicardial cells.

During embryogenesis, the epicardial contribution to coronary vasculature development has been very well established. Cells derived from the epicardium ...

Resonance Fluorescence of an InGaAs Quantum Dot in a Planar Cavity Using Orthogonal Excitation and Detection

The ability to perform simultaneous resonant excitation and fluorescence detection is important for quantum optical measurements of quantum dots (QDs). Resonant excitation without fluorescence detection &#8211; for example, a differential transmission measurement &#8211; can determine some properties of the emitting system, but does not allow applications or measurements based on the emitted photons. For example, the measurement of photon correlations, observation of the Mollow triplet, and realization of single photon sources all require collection of the fluorescence. Incoherent excitation with fluorescence detection &#8211; for example, above band-gap excitation &#8211; can be used to create single photon sources, but the disturbance of the environment due to the excitation reduces the indistinguishability of the photons. Single photon sources based on QDs will have to be resonantly excited to have high photon indistinguishability, and simultaneous collection of the photons will be necessary to make use of them. We demonstrate a method to resonantly excite a single QD embedded in a planar cavity by coupling the excitation beam into this cavity from the cleaved face of the sample while collecting the fluorescence along the sample&#39;s surface normal direction. By carefully matching the excitation beam to the waveguide mode of the cavity, the excitation light can couple into the cavity and interact with the QD. The scattered photons can couple to the Fabry-Perot mode of the cavity and escape in the surface normal direction. This method allows complete freedom in the detection polarization, but the excitation polarization is restricted by the propagation direction of the excitation beam. The fluorescence from the wetting layer provides a guide to align the collection path with respect to the excitation beam. The orthogonality of the excitation and detection modes enables resonant excitation of a single QD with negligible laser scattering background.

Resonant excitation of a single self-assembled quantum dot can be achieved using an excitation mode orthogonal to the fluorescence collection mode. We demonstrate a method using the waveguide and Fabry-Perot modes of a planar microcavity surrounding the quantum dots. The method allows complete freedom in the detection polarization.

The ability to perform simultaneous resonant excitation and fluorescence detection is important for quantum optical measurements of quantum dots (QDs). ...

Fabrication of Magnetic Nanostructures on Silicon Nitride Membranes for Magnetic Vortex Studies Using Transmission Microscopy Techniques

Electron and x-ray magnetic microscopies allow for high-resolution magnetic imaging down to tens of nanometers. However, the samples need to be prepared on transparent membranes which are very fragile and difficult to manipulate. We present processes for the fabrication of samples with magnetic micro- and nanostructures with spin configurations forming magnetic vortices suitable for Lorentz transmission electron microscopy and magnetic transmission x-ray microscopy studies. The samples are prepared on silicon nitride membranes and the fabrication consists of a spin coating, UV and electron-beam lithography, the chemical development of the resist, and the evaporation of the magnetic material followed by a lift-off process forming the final magnetic structures. The samples for the Lorentz transmission electron microscopy consist of magnetic nanodiscs prepared in a single lithography step. The samples for the magnetic x-ray transmission microscopy are used for time-resolved magnetization dynamic experiments, and magnetic nanodiscs are placed on a waveguide which is used for the generation of repeatable magnetic field pulses by passing an electric current through the waveguide. The waveguide is created in an extra lithography step.

A protocol for the fabrication of magnetic micro- and nanostructures with spin configurations forming magnetic vortices suitable for transmission electron microscopy (TEM) and magnetic transmission x-ray microscopy (MTXM) studies is presented.

Electron and x-ray magnetic microscopies allow for high-resolution magnetic imaging down to tens of nanometers. However, the samples need to be prepared ...

Simultaneous Measurement of Turbulence and Particle Kinematics Using Flow Imaging Techniques

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine micro-organisms, and/or sediments in the ocean, or fluidized bed reactors and combustion processes in engineered systems. In order to study the effect of turbulence on the kinematics of particles in such flows, simultaneous measurements of both the flow and particle kinematics are required. Non-intrusive, optical flow measurement techniques for measuring turbulence, or for tracking particles, exist but measuring both simultaneously can be challenging due to interference between the techniques. The method presented herein provides a low cost and relatively simple method to make simultaneous measurements of the flow and particle kinematics. A cross section of the flow is measured using a particle image velocimetry (PIV) technique, which provides two components of velocity in the measurement plane. This technique utilizes a pulsed-laser for illumination of the seeded flow field that is imaged by a digital camera. The particle kinematics are simultaneously imaged using a light emitting diode (LED) line light that illuminates a planar cross section of the flow that overlaps with the PIV field-of-view (FOV). The line light is of low enough power that it does not affect the PIV measurements, but powerful enough to illuminate the larger particles of interest imaged using the high-speed camera. High-speed images that contain the laser pulses from the PIV technique are easily filtered by examining the summed intensity level of each high-speed image. By making the frame rate of the high-speed camera incommensurate with that of the PIV camera frame rate, the number of contaminated frames in the high-speed time series can be minimized. The technique is suitable for mean flows that are predominantly two-dimensional, contain particles that are at least 5 times the mean diameter of the PIV seeding tracers, and are low in concentration.

The technique described herein offers a low cost and relatively simple method to simultaneously measure particle kinematics and turbulence in flows with low particle concentrations. The turbulence is measured using particle image velocimetry (PIV), and particle kinematics are calculated from images obtained with a high-speed camera in an overlapping field-of-view.

Numerous problems in scientific and engineering fields involve understanding the kinematics of particles in turbulent flows, such as contaminants, marine ...