A Spatiotemporal exploration and 3D modeling of blood flow in healthy carotid artery bifurcation from two modalities: Ultrasound-Doppler and phase contrast MRI.
Summary (3 min read)
1. Introduction
- Vascular maladies may be caused by thrombi and can lead to stroke [18].
- Blood flow analysis can confirm the presence of a local vessel anomaly, its impact on the blood flow pattern and its possible evolution [7, 26, 25, 10].
- Few studies compared velocity measurements in the carotid artery between US-Doppler and PC-MRI [15, 16, 38, 28].
- Section 2 describes the imaging data sets and the analysis methodology.
2. Material and Methods
- The arterial geometrical model was extracted from MR anatomical images and the hemodynamic modeling was performed from the obtained models.
- The velocity waveforms from both PC-MRI and US-Doppler were extracted at three locations: the right CCA, ECA and ICA.
2.1.1. PC-MR imaging
- The PC-MR images were acquired with a clinical 1.5 T Philips system (Ingenia, Philips medical systems, Best, the Netherlands) using 20 channels phased array head neck spine coil.
- Fifty 2D anatomical images were acquired in axial orientation to cover cervical region Arij Debbich et al.: Preprint submitted to Elsevier Page 2 of 16 Figure 3: Growing carotid scanning windows size.
- Key points are located in: CCA at 1.5 cm from the bifurcation, ECA and ICA: at 1 cm from the bifurcation.
- The ideal velocity encoding (VENC) should be high enough to avoid aliasing and as low as possible to reduce velocity noise [47].
- The total scan time for an exam was approximately 7 minutes.
2.1.2. US-Doppler imaging
- All US-Doppler exams were conducted by a radiologist (B.H) with 10 years’ experience in cardiovascular imaging.
- Clinical General Electric ultrasound systems (LOGIQ E9, GE Healthcare, Milwaukee, WI, USA) with 9 MHz linear probe were used.
- US-Doppler images were matrices of dimension 720x960.
- To extract the velocity waveform, the authors chose a profile of one cardiac cycle , fixed the two profile axes and selected 14 feature points on these profiles including PSV and EDV.
- The USDoppler profile point digitization was performed using the Engauge Digitizer software [29].
2.2. PC-MRI Velocity profile extraction
- Three velocity waveforms were extracted from PC-MRI at locations CCA, ECA, and ICA during a cardiac cycle which was divided into 14 time points.
- The following values were deduced from the interpolated waveforms: - Velocity variation at a given pixel VMRIpixel .
- - Maximum velocity at a given pixel within its eight neighbors VMRImax.-.
- As the MRI and the US-Doppler examinations were not acquired at the same time, there might be some physiological variations [16].
2.3. Arterial model reconstruction and computational mesh generation
- The geometrical characteristics of all the vessel segments for the ten subjects are given in Table1.
- The carotid lumen was separated from the rest of the structures by applying an intensity threshold.
- The model was further re-meshed using an Octree surface refinement based on prismatic wall [20].
- Some studies adopted the rheological Newtonian behavior for the carotid artery (stationary viscosity) because it is simpler than the hemodynamic modeling with a non Newtonian behavior and arguing it has aminor impact on the results [33].
2.4. Boundary conditions
- One of their objectives was to investigate the impact of the inlet boundary conditions on the simulation results.
- These inlets were pulsed over time and were composed of the two usual physiological phases during a cardiac cycle: systole and diastole.
- Velocity profile for every subject was matched to VMRImax inthe CCA, 3.3 cm from the carotid bifurcation to conform to the CCA dimension in the geometrical model.
- (5) where ℎt is the maximal parabolic magnitude matching the VMRImax or VUS at time t. (xc , yc) and R are respectively thecenter coordinates and the radius of the CCA inlet section.
- All meshes brought velocity profiles close to each other.
2.5. Simulated velocity profiles
- Simulated velocity profiles Vsim were extracted at threelocations of the carotid bifurcation: 1.5 cm from the bifurcation in the CCA and 1 cm up the bifurcation in ECA and ICA.
- The values were extracted using CFD-POST from ANSYS software.
3. Results
- Velocity waveforms were extracted from PC-MRI (VMRImax, VMRIpixel and VMRImean) and Doppler-US (VUS)imaging data for ten volunteers at the three localizations of the carotid artery.
- The first one, called VSIM_MRI, is based on PC-MRI data VMRImaxprofile used as inlet boundary condition.
- The authors did not integrate the pixel-based PC-MRI velocity VMRIpixel in the tables since its values werebetween those of VMRImax and VMRImean and were noisier.
3.1. Analysis of PC-MRI velocities
- Typical measured velocity waveforms from PC-MRI are presented in Figure 4. ECA and ICA relative to V MRImax for PC-MRI (up) and V US for US-Doppler (down).
- The authors noted that a velocity profile over the CCA diameter at a given location was almost parabolic for all time points . and end diastolic (ED) time points every centimeter from the CCA to the carotid sinus, ICA and ECA .
- There were significant variations de- tected in the carotid sinus site: a progressive decrease of the maximum velocity and a disruption of the profile shape.
3.2. Analysis of PC-MRI and US velocity measurements
- Unlike the difference observed by Harloff et al.[15] for ICA, PSV of PC-MRI was on average less than US-Doppler by about 17.6%.
- The same tendency was observed in CCA PSV (mean difference of 21.8 cm/s), to a much lower extent for CCA EDV .
- Diastolic velocity profiles are less dissimilar except in ICA for the two modalities.
- The mean velocity waveforms of the ten volunteers relative to PC-MRI and US-Doppler in CCA, ECA and ICA are plotted in Figure 10.
3.3. Analysis of simulated velocity waveforms
- Overall, the numerical velocity waveforms were closer to the PC-MRI ones independent of the arterial input function considered (US or MRI).
- The numerical velocities were compared to in vivo measurements through the global and the local indicators defined in section 3 .
- The mean difference between measurements and simulation for PSV and EDV was greater.
- From Tables 2, 3 and 4, it can be noted that the mean PSV of the ten subjects from VSIM_MRImax is lower than that from VSIM_US.
4. Discussion
- The PC-MRI velocity behavior in the carotid bifurcation was investigated in time and space.
- It was observed that the velocity estimation increased with the window size up to maximum .
- This can be difficult to achieve when dealing with a PC-MRI and US-Doppler comparative study like ours for two reasons related to US measurements: i) lack of convenient accessibility for radiologists.
- The arterial wall pulsatility has not been considered as it would have brought many additional issues with less mastered modeling methods (Fluid Structure Interaction).
- Locally, the mean difference between VSIM_MRImax and VMRImax varied from 22% to 32% according to the local dif-ference metric at peak systole PSV and from 29% to 37%according to the local difference metric at end diastole EDV.
5. Conclusion
- The authors investigated blood velocity quantification over the carotid artery bifurcation from PC-MRI and US-Doppler, and 3D velocity modeling from these modalities.
- PC-MRI data analysis showed velocity across the section of the artery follows a parabolic profile except in the sinus region.
- Overall, the authors found numerical velocities based on PC-MRI velocity inlet closer to measurements than those based on Doppler-US velocity inlet.
- Therefore, from their experiments, the PC-MRI-based hemodynamic modeling approach could be reasonably more realistic.
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"A Spatiotemporal exploration and 3D..." refers background in this paper
...Several in vivo [15, 16, 28, 17, 30] , in vitro [45, 21, 2], in-silico [23, 19, 49, 33, 11], and mixed imageCFD (Computational Fluid Dynamics) [22, 36] approaches have focused on this artery and associated anomalies....
[...]
59 citations
"A Spatiotemporal exploration and 3D..." refers background or methods in this paper
...ii) measurements of blood flow velocity (Ultrasound Doppler (US-Doppler) [46] or phase contrast Magnetic Resonance (PC-MRI) [41]) to provide at least arterial input functions....
[...]
...Realistic image-based patient specific CFDmodeling requires the extraction of several pieces of information from medical data with at least: i) the vascular morphology frommedical imaging (Computed tomographyAngiography (CTA) [43] orMagnetic Resonance Imaging (MRI) [41])....
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54 citations
"A Spatiotemporal exploration and 3D..." refers background in this paper
...Several in vivo [15, 16, 28, 17, 30] , in vitro [45, 21, 2], in-silico [23, 19, 49, 33, 11], and mixed imageCFD (Computational Fluid Dynamics) [22, 36] approaches have focused on this artery and associated anomalies....
[...]
50 citations
"A Spatiotemporal exploration and 3D..." refers background or result in this paper
...Several in vivo [15, 16, 28, 17, 30] , in vitro [45, 21, 2], in-silico [23, 19, 49, 33, 11], and mixed imageCFD (Computational Fluid Dynamics) [22, 36] approaches have focused on this artery and associated anomalies....
[...]
...This observation agrees with several CFD simulations in previous works [37, 40, 11, 12]....
[...]