Measuring Flows in Patient-Specific Aneurysms

Correlation between the two techniques in the airways may differ from that in previously reported vascular studies for several reasons. Respiratory PC MRI involves inhalation of exogeneous 129Xe gas as a contrast agent whilst in hemodynamics endogenous blood is imaged directly. In fact, in some cardiovascular studies, PC MRI velocity values are used to define the CFD inlet boundary condition , thus leading to better agreement in the upstream flow rates.

Computational fluid dynamics methods can be used to compute the velocity field in patient-specific vascular geometries for pulsatile physiological flow. The effect of the inlet flow rate conditions on calculated velocity fields was investigated. We assessed the internal consistency of our approach by comparing CFD predictions of the in-plane velocity field to the corresponding in vivo MR velocimetry measurements. Patient-specific surface models of four basilar artery aneurysms were constructed from contrast-enhanced MR angiography data.

A positive-space model of the vascular geometry was 3D printed (ProJet printer—3D Systems), embedded into a tear-resistant silicone block and then cut from the block. The metal model was embedded in optically clear polydimethylsiloxane silicone (PDMS—Slygard 184) which was allowed to cure until hardened, then the metal was melted out from the clear PDMS. Figure 9 Comparison of in vivo and CFD predictions of DF in different regions of the airways for the Respimat inhaler with a fenoterol formulation considering one SIP geometry in each lung lobe.

Thrombus formation was predicted by repeating CFD analysis, and analysis was repeated 50 times. A) 2D velocity maps for PC MRI and CFD data and the difference between them, and b) correlation plots and histograms presented as in Fig 6, after down-sampling of the PC MRI data in plane by 3×3 voxels and re-sampling the CFD data to the corresponding resolution. D) data in c) after removal (“erosion”) of the boundary layer of pixels from the 2D maps shown in Fig 5 . Histograms of velocity values derived from PC MRI and CFD are displayed in blue and red color, respectively.

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In general, each modality yields a unique set of strengths and weaknesses as well as varying accuracy, physiological fidelity and resolution. The results here demonstrated that WSS, OSI and RRT maintained differing behaviour when subjected to these flow domain variations across modalities. This study is the first in vivo human comparison of CFD simulations of respiratory airflow and establishes a method for future validation of CFD simulation results by comparison to PC MRI velocity anna kharchenko maps. Qualitative agreement between the two techniques was good, with high and low velocity regions and features such as high flow jets occurring in the same spatial locations. This study lays the groundwork for future validation studies in healthy subjects and in patients with airway disease. Such future validation studies based on the techniques demonstrated here will aid the clinical adoption of CFD simulations as a means to assess airway disease and treatment strategies.

cfd en vivo

Figure 4 Mass fraction of the particle size distribution produced by the Novolizer DPI and Respimat SMI inhalers. Values for the Respimat PSD were reported in the study of Steed et al. , whereas new values for the Novolizer at a constant flow rate of 80 LPM were measured in this study. MRI-based measurements of aerosol deposition in the lung of healthy and elastase-treated rats. Reproducibility of haemodynamical simulations in a subject-specific stented aneurysm model–a report on the Virtual Intracranial Stenting Challenge 2007. Figure 7 Regional deposition fraction predictions for the Novolizer in B4-B7 and B8-B15 implementing the more accurate polydisperse simulation vs. the monodisperse approximation. Implementing the correction factor of 1.25×MMAD cannot fully account for deposition of the polydisperse aerosol in these two different lung regions.

In vivo validation of numerical prediction for turbulence intensity in an aortic coarctation

To synchronize flow rate measurements with the MRI acquisition, the MRI scanner outputs a 5-volt trigger signal at the start of each dynamic image acquisition. The LabChart software recorded the flow rate data and these trigger signals simultaneously . Synchronizing flow rate measurements and image acquisition allowed temporal alignment of CFD simulation results and PC MRI velocimetry. In vivo validation of respiratory CFD simulations is difficult due to the challenges in directly measuring airflow within the large airways as stated above; instruments placed inside the airway to measure airflow disrupt natural physiology and airflow.

cfd en vivo

We are using this bioreactor to study the proPLT formation process and enhance in vitro PLP yields. Experimental studies were conducted to validate the simulations in terms of streamline profiles and flow patterns with and without cell capture. Microenvironment characteristics include but are not limited to extracellular matrix protein coatings. Furthermore, the design of the bioreactor allows for a wide physiological shear rate range.

The full resolution CFD WSS distribution maintained a larger spread of WSS values than all other modalities and maintained the largest WSS magnitudes. Similar OSI distributions for the basilar tip aneurysm were observed for all modalities except the full resolution CFD. The average OSI of the STB changed from 0.17 to 0.08, while CFD went from 0.04 to 0.07 when voxel averaged.

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The predicted particle locations are refined by iteratively ‘shaking’ them within a tolerance, minimizing the residual between the subsequent particle image and the predicted particle image. STB was done using 12 iterations for both the outer and inner equiti broker review loops with an allowed particle triangulation error of 1.5 voxels and particle position shaking of 0.1 voxels. As opposed to planar and stereo PIV [27–29], currently no methods to evaluate uncertainty in volumetric PIV/STB processing have been reported.

  • The spatial averaging process performed to combine CFD results across the PC MRI slice (see Comparing Velocities from PC MRI and CFD–Alignment and Resolution) also has some effect on the velocity profiles in the foot-head and anterior-posterior directions.
  • In general, velocity in the foot-to-head direction, vFH, showed the highest velocity values, which is expected as the direction of airflow is largely aligned with the main axis of the airway.
  • A contrast-enhanced MR angiography and a time-resolved 2D PCMRI measurement were also performed to acquire data needed to perform subsequent image-based computational fluid dynamics modeling.

Since 129Xe is not normally inhaled, it is useful to determine what sort of breathing maneuver the 129Xe inhalation would represent in air. The concept of dynamic similarity implies that the flow patterns recorded with 129Xe will be equivalent to air flowing at a different flow rate. This equivalent flow rate, QAir, can be calculated by equating the Reynolds numbers of the xenon flow, ReXe, and the equivalent airflow, ReAir. Many airway diseases result in obstruction of the large airways, including obstructive sleep apnea , medialized vocal folds, tracheomalacia, laryngomalacia, bronchomalacia, and subglottic stenosis [1–3]. These diseases often result in multiple sites of obstruction, and/or may occur with comorbid lung abnormalities. Currently, there are no clinical methods to assess the contribution of each site of obstruction to respiratory symptoms.

Recombinant Human Complement factor D(CFD)

2) Inhaled 129Xe will take longer to displace the air that was initially inside the airway due to the low velocities in the boundary layer. 3) The slow-moving flow in the boundary layer will also remain in the airway for longer. Hyperpolarized 129Xe MR signal decays according to radiofrequency pulse excitation and the longitudinal relaxation time , and thus, the longer the 129Xe remains in the airway, the more signal decay it will be subjected to. To eliminate this potential source of error, the boundary layer was removed by eroding the mask by 1 voxel at the boundary and the agreement between the two methods was re-evaluated. A further possible cause for differences in PC MRI- and CFD-derived velocity maps reported in this in vivo study compared to previous studies is upper airway motion.

Computational fluid dynamics simulations of respiratory airflow have the potential to change the clinical assessment of regional airway function in health and disease, in pulmonary medicine and otolaryngology. For example, in diseases where multiple sites of airway obstruction occur, such as obstructive sleep apnea , CFD simulations can identify which sites of obstruction contribute most to airway resistance and may therefore be candidate sites for airway surgery. The main barrier to clinical uptake of respiratory CFD to date has been the difficulty in validating CFD results against a clinical gold standard. Invasive instrumentation of the upper airway to measure respiratory airflow velocity or pressure can disrupt the airflow and alter the subject’s natural breathing patterns.

Current clinical gold-standard methods of airway evaluation such as spirometry are limited to global assessments of the entire airway, and provide little information on the level of the airway that causes symptoms. In vivo regional measurements are rare due to the difficulty in instrumenting the airway without disrupting its natural physiology and airflow. RRT is a measure of the flow stagnation or the residence of fluid particles near the wall.

As seen in figure 6, all modalities had uniquely different regions of normalized low WSS and RRT in the aneurysmal sacs of both geometries, even across cases which had strong agreement in the flow patterns and velocity distributions (i.e. 4D flow and CFD for the ICA aneurysm). In this study, one WSS calculation methodology was used and variations in the proximity of the velocity vectors to the wall were mitigated to ensure consistent calculation bias across cases. Furthermore, Cebral et al. showed inflow waveform changes can cause variability in the magnitude but not spatial variation of haemodynamic metrics and van Ooij et al. demonstrated similar findings regarding spatial resolution.

In particular, the velocity is sensitive to exact geometric position and therefore any image registration errors; such misalignment can affect high flow velocity features in terms of both position and magnitude. Despite its clinical importance, accurately assessing the progression and risk of rupture of cerebral aneurysms is challenging. Hemodynamic factors play an important role in aneurysm progression, but previous studies have reported contradictory findings, preventing specific mechanisms from being defined.

The CFD geometry was obtained from 1H MR images acquired while the subject was breathing restfully, but the 129Xe PC MRI data were acquired while the subject was inhaling as slowly as possible. In addition, a different radiofrequency coil was used for MR signal detection due to the different nuclei and since these coils were incompatible, the subject may have changed position during the coil switching process. While image registration was performed to account for any bulk subject motion, this may have been imperfect.

For reference, we note that it is common practice to use an in-plane resolution ~3–4 mm and slice thickness of 10–15 mm for 129Xe MR imaging of lung ventilation. A time-series of up to 10 images of each slice was acquired; depending on scan parameters, the acquisition time for a single slice with three-directional velocity encoding ranged from time series analysis james d. hamilton 3–5 seconds. Fig 2 shows example 1H anatomical MRI images, along with representative dynamic 129Xe gas PC MR images, in each of the three subjects. The inlet flow rate was computed from the velocity fields for all modalities in the basilar tip and ICA aneurysms to ensure agreement across modalities and is shown in figure 3a,b, respectively.