Inter-patient variations in flow boundary conditions at middle cerebral artery from 7T PC-MRI and influence on Computational Fluid Dynamics of intracranial aneurysms

The effects of aperture position and length in side-vented needles on root canal irrigation: A computational fluid dynamics study

INTRODUCTION

Root canal irrigation is crucial for infection control during root canal treatment. Side-vented needles for positive pressure irrigation are commonly used in clinical practice. However, variations in needle design among manufacturers can impact the fluid dynamics of irrigation. This study aims to use computational fluid dynamics to explore the flow characteristics of different needle aperture lengths and positions, and their effects on the effectiveness and safety of irrigation, using a validated passive scalar transport numerical model.

METHODS

The validation of the CFD irrigant model was achieved by comparing it with an in vitro irrigation experiment model. The CFD model used scalar concentration, while the in vitro experiment model used red dye tracing. Using a standard 30G side-vented needle as a reference, virtual needle models featuring four aperture lengths and three positions were created. These virtual irrigation needles were then placed in two root canal geometries for CFD simulation to evaluate fluid exchange capabilities and related fluid dynamic parameters.

RESULTS

The results of the CFD simulation, using a scalar transport model, closely matched the in vitro tracer tests for irrigation experiments across seven root canal geometries. The CFD analysis indicated that positioning the aperture lower increased the irrigant exchange distance. Notably, decreasing the aperture length to 0.25x, and positioning it at the lower end of the needle significantly increased exchange distance and shear stress, while reducing apical pressure.

CONCLUSIONS

These results indicate that the position and length of the aperture affect the exchange distance of irrigant flow, wall shear stress, and apical pressure. The CFD validation model for scalar transport, based on a steady state, can function as a valuable tool for optimizing the side-vented needle in research. Further research on the design of side-vented needles will enhance the understanding of flow characteristics beneficial for irrigation efficiency in clinical practice.

Experimental study using phantom models of cerebral aneurysms and 4D-DSA to measure blood flow on 3D-color-coded images

BACKGROUND

The current 3D-iFlow application can only measure the arrival time of contrast media through intensity values. If the flow rate could be estimated by 3D-iFlow, patient-specific hemodynamics could be determined within the scope of normal diagnostic management, eliminating the need for additional resources for blood flow rate estimation.

OBJECTIVE

The aim of this study is to develop and validate a method for measuring the flow rate by data obtained from 3D-iFlow images - a prototype application in Four-dimensional digital subtraction angiography (4D-DSA).

METHODS

Using phantom model and experimental circuit with circulating glycerin solution, an equation for the relationship between contrast media intensity and flow rate was developed. Applying the equation to the aneurysm phantom models, the derived flow rate was evaluated.

RESULTS

The average errors between the derived flow rate and setting flow rate became larger when the glycerin flow and the X-rays from the X-ray tube of the angiography system were parallel to each other or when the measurement point included overlaps with other contrast enhanced areas.

CONCLUSION

Although the error increases dependent on the imaging direction and overlap of contrast enhanced area, the developed equation can estimate the flow rate using the image intensity value measured on 3D-iFlow based on 4D-DSA.

Hemodynamic Parameters in the Parent Arteries of Unruptured Intracranial Aneurysms Depend on Aneurysm Size and Are Different Compared to Contralateral Arteries: A 7 Tesla 4D Flow MRI Study

BACKGROUND

Different Circle of Willis (CoW) variants have variable prevalences of aneurysm development, but the hemodynamic variation along the CoW and its relation to presence and size of unruptured intracranial aneurysms (UIAs) are not well known.

PURPOSE

Gain insight into hemodynamic imaging markers of the CoW for UIA development by comparing these outcomes to the corresponding contralateral artery without an UIA using 4D flow magnetic resonance imaging (MRI).

STUDY TYPE

Retrospective, cross-sectional study.

SUBJECTS

Thirty-eight patients with an UIA, whereby 27 were women and a mean age of 62 years old.

FIELD STRENGTH/SEQUENCE

Four-dimensional phase-contrast (PC) MRI with a 3D time-resolved velocity encoded gradient echo sequence at 7 T.

ASSESSMENT

Hemodynamic parameters (blood flow, velocity pulsatility index [vPI], mean velocity, distensibility, and wall shear stress [peak systolic (WSSMAX ), and time-averaged (WSSMEAN )]) in the parent artery of the UIA were compared to the corresponding contralateral artery without an UIA and were related to UIA size.

STATISTICAL TESTS

Paired t-tests and Pearson Correlation tests. The threshold for statistical significance was P < 0.05 (two-tailed).

RESULTS

Blood flow, mean velocity, WSSMAX , and WSSMEAN were significantly higher, while vPI was lower, in the parent artery relative to contralateral artery. The WSSMAX of the parent artery significantly increased linearly while the WSSMEAN decreased linearly with increasing UIA size.

CONCLUSIONS

Hemodynamic parameters and WSS differ between parent vessels of UIAs and corresponding contralateral vessels. WSS correlates with UIA size, supporting a potential hemodynamic role in aneurysm pathology.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Sensitivity of hostile hemodynamics to aneurysm geometry via unsupervised shape interpolation

BACKGROUND AND OBJECTIVE

Vessel geometry and hemodynamics are intrinsically linked, whereby geometry determines hemodynamics, and hemodynamics influence vascular remodeling. Both have been used for testing clinical outcomes, but geometry/morphology generally has less uncertainty than hemodynamics derived from medical image-based computational fluid dynamics (CFD). To provide clinical utility, CFD-based hemodynamic parameters must be robust to modeling errors and/or uncertainties, but must also provide useful information not more-easily extracted from shape alone. The objective of this study was to methodically assess the response of hemodynamic parameters to gradual changes in shape created using an unsupervised 3D shape interpolation method.

METHODS

We trained the neural network NeuroMorph on 3 patient-derived intracranial aneurysm surfaces (labelled A, B, C), and then generated 3 distinct morph sequences (A→B, B→C, C→A) each containing 10 interpolated surfaces. From high-fidelity CFD simulation of these, we calculated a variety of common reduced hemodynamic parameters, including many previously associated with aneurysm rupture, and analyzed their responses to changes in shape, and their correlations.

RESULTS

The interpolated surfaces demonstrate complex, gradual changes in branch angles, vessel diameters, and aneurysm morphology. CFD simulation showed gradual changes in aneurysm jetting characteristics and wall-shear stress (WSS) patterns, but demonstrated a range of responses from the reduced hemodynamic parameters. Spatially and temporally averaged parameters including time-averaged WSS, time-averaged velocity, and low-shear area (LSA) showed low variation across all morph sequences, while parameters of flow complexity such as oscillatory shear, spectral broadening, and spectral bandedness indices showed high variation between slightly-altered neighboring surfaces. Correlation analysis revealed a great deal of mutual information with easier-to-measure shape-based parameters.

CONCLUSIONS

In the absence of large clinical datasets, unsupervised shape interpolation provides an ideal laboratory for exploring the delicate balance between robustness and sensitivity of nominal hemodynamic predictors of aneurysm rupture. Parameters like time-averaged WSS and LSA that are highly "robust" may, as a result, be effectively redundant to morphological predictors, whereas more sensitive parameters may be too uncertain for practical clinical use. Understanding these sensitivities may help identify parameters that are capable of providing added value to rupture risk assessment.

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI

OBJECTIVE

Wall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance imaging (PC-MRI) coupled with advanced image acceleration techniques allows a highly resolved visualization of near-wall hemodynamic parameters patterns in in vitro IAs, paving the way for more robust risk assessment of their growth and rupture.

MATERIALS AND METHODS

We performed pulsatile flow measurements inside three in vitro models of patient-specific IAs using 7 T PC-MRI. To this end, we built an MRI-compatible test bench, which faithfully reproduced a typical physiological intracranial flow rate in the models.

RESULTS

The ultra-high field 7 T images revealed WSS patterns with high spatiotemporal resolution. Interestingly, the high oscillatory shear index values were found in the core of low WSS vortical structures and in flow stream intersecting regions. In contrast, maxima of WSS occurred around the impinging jet sites.

CONCLUSIONS

We showed that the elevated signal-to-noise ratio arising from 7 T PC-MRI enabled to resolve high and low WSS patterns with a high degree of detail.

Hemodynamic Analysis Shows High Wall Shear Stress Is Associated with Intraoperatively Observed Thin Wall Regions of Intracranial Aneurysms

BACKGROUND

Studying the relationship between hemodynamics and local intracranial aneurysm (IA) pathobiology can help us understand the natural history of IA. We characterized the relationship between the IA wall appearance, using intraoperative imaging, and the hemodynamics from CFD simulations.

METHODS

Three-dimensional geometries of 15 IAs were constructed and used for CFD. Two-dimensional intraoperative images were subjected to wall classification using a machine learning approach, after which the wall type was mapped onto the 3D surface. IA wall regions included thick (white), normal (purple-crimson), and thin/translucent (red) regions. IA-wide and local statistical analyses were performed to assess the relationship between hemodynamics and wall type.

RESULTS

Thin regions of the IA sac had significantly higher WSS, Normalized WSS, WSS Divergence and Transverse WSS, compared to both normal and thick regions. Thicker regions tended to co-locate with significantly higher RRT than thin regions. These trends were observed on a local scale as well. Regression analysis showed a significant positive correlation between WSS and thin regions and a significant negative correlation between WSSD and thick regions.

CONCLUSION

Hemodynamic simulation results were associated with the intraoperatively observed IA wall type. We consistently found that elevated WSS and WSS_Norm were associated with thin regions of the IA wall rather than thick and normal regions.

Reliability of using generic flow conditions to quantify aneurysmal haemodynamics: A comparison against simulations incorporating boundary conditions measured in vivo

BACKGROUND AND OBJECTIVES

Initiation, growth, and rupture of intracranial aneurysms are believed to be closely related to their local haemodynamic environment. While haemodynamics can be characterised by use of computational fluid dynamics (CFD), its reliability depends heavily upon accurate assumption of the boundary conditions. Herein, we compared the simulated aneurysmal haemodynamics obtained by use of generic boundary conditions against those obtained under flow conditions measured in vivo.

METHODS

We prospectively recruited 19 patients with intracranial aneurysms requiring 3-dimensional rotational angiography, during which blood pressure at the internal carotid artery was probed by catheter and flowrate measured by a dedicated software tool. Using these flow conditions measured in vivo, we quantified the aneurysmal haemodynamics for each patient by CFD, and then compared the results with those derived from a generic condition reported in the literature, in terms of the time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), and percentage of the intra-aneurysmal flow (PIAF). In addition, the effects on aneurysmal haemodynamics of different outflow strategies (splitting method vs. Murray's Law) and simulation schemes (transient vs. steady-state) relative to each flow condition were also assessed.

RESULTS

Differences in the simulated TAWSS (-6.08 ± 10.64 Pa, p = 0.001), OSI (0.06 ± 0.13, p = 0.001), and PIAF (-0.05 ± 0.20, p = 0.012) between the patient-specific and generic boundary conditions were found to be statistically significant, in contrast to that in the RRT (49 ± 307 Pa^-1, p = 0.062). Outflow strategies did not yield statistically significant differences in any of the investigated parameters (all p > 0.05); rather, the resulting parameters were found to be in good correlations (all r > 0.71, p < 0.001). Difference between the aneurysmal TAWSS and the WSS derived from cycle-averaged flowrate condition was found to be minor (0.66 ± 1.36 Pa, p = 0.000), so was that between PIAFs obtained respectively from the transient and steady-state simulations (0.02 ± 0.05, p = 0.000).

CONCLUSIONS

Incorporating into simulation the patient-specific boundary conditions is critical for CFD to characterise aneurysmal haemodynamics, while outflow strategies may not introduce significant uncertainties. Steady-state simulation incorporating the cycle-averaged flow condition may produce unbiased WSS and PIAF compared to the transient analysis.

Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging

Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases. In this work, we put forth a physics-informed deep learning framework that augments sparse clinical measurements with one-dimensional (1D) reduced-order model (ROM) simulations to generate physically consistent brain hemodynamic parameters with high spatiotemporal resolution. Transcranial Doppler (TCD) ultrasound is one of the most common techniques in the current clinical workflow that enables noninvasive and instantaneous evaluation of blood flow velocity within the cerebral arteries. However, it is spatially limited to only a handful of locations across the cerebrovasculature due to the constrained accessibility through the skull's acoustic windows. Our deep learning framework uses in vivo real-time TCD velocity measurements at several locations in the brain combined with baseline vessel cross-sectional areas acquired from 3D angiography images and provides high-resolution maps of velocity, area, and pressure in the entire brain vasculature. We validate the predictions of our model against in vivo velocity measurements obtained via four-dimensional (4D) flow magnetic resonance imaging (MRI) scans. We then showcase the clinical significance of this technique in diagnosing cerebral vasospasm (CVS) by successfully predicting the changes in vasospastic local vessel diameters based on corresponding sparse velocity measurements. We show this capability by generating synthetic blood flow data after cerebral vasospasm at various levels of stenosis. Here, we demonstrate that the physics-based deep learning approach can estimate and quantify the subject-specific cerebral hemodynamic variables with high accuracy despite lacking knowledge of inlet and outlet boundary conditions, which is a significant limitation for the accuracy of the conventional purely physics-based computational models.

Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond

Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown significant promising results, ML for the prediction of biomechanics such as blood flow or tissue dynamics is in its infancy. This perspective article discusses some of the challenges in using ML for replacing well-established physics-based models in cardiovascular biomechanics. Specifically, we discuss the large landscape of input features in 3D patient-specific modeling as well as the high-dimensional output space of field variables that vary in space and time. We argue that the end purpose of such ML models needs to be clearly defined and the tradeoff between the loss in accuracy and the gained speedup carefully interpreted in the context of translational modeling. We also discuss several exciting venues where ML could be strategically used to augment traditional physics-based modeling in cardiovascular biomechanics. In these applications, ML is not replacing physics-based modeling, but providing opportunities to solve ill-defined problems, improve measurement data quality, enable a solution to computationally expensive problems, and interpret complex spatiotemporal data by extracting hidden patterns. In summary, we suggest a strategic integration of ML in cardiovascular biomechanics modeling where the ML model is not the end goal but rather a tool to facilitate enhanced modeling.

Extraction of patient-specific boundary conditions from 4D-DSA and their influence on CFD simulations of cerebral aneurysms

We developed a new technique for extracting patient-specific inflow conditions, such as the pulse cycle duration and blood flow velocity, from four-dimensional digital subtraction angiography images and experimentally examined its validity. The maximum error between the values extracted by the technique and measured values was 14.3%. We performed blood flow simulations and calculated representative haemodynamic parameters. The maximum differences between the parameters obtained using general and patient-specific inflow conditions were approximately 400%, 150%, and 50% for the velocity, normalised wall shear stress, and pressure loss coefficient, respectively. These results indicate that patient-specific conditions are critical for accurately reproducing aneurysmal haemodynamics.

Combination of Morphological and Hemodynamic Parameters for Assessing the Rupture Risk of Intracranial Aneurysms: a Retrospective Study On Mirror Middle Cerebral Artery Aneurysms

Discordant findings were frequently reported by studies dedicated to exploring the association of morphological/hemodynamic factors with the rupture of intracranial aneurysms (IAs), probably owing to insufficient control of confounding factors. In this study, we aimed to minimize the influences of confounding factors by focusing IAs of interest on mirror aneurysms and, meanwhile, modeling IAs together with the cerebral arterial network to improve the physiological fidelity of hemodynamic simulation. 52 mirror aneurysms located at the middle cerebral artery (MCA) in 26 patients were retrospectively investigated. Numerical tests performed on two randomly selected patients demonstrated that over truncation of cerebral arteries proximal to the MCA during image-based model reconstruction led to uncertain changes in computed values of intra-aneurysmal hemodynamic parameters, which justified the minimal truncation strategy adopted in our study. Five morphological parameters (i.e., volume (V), height (H), dome area (DA), non-sphericity index (NSI), and size ratio (SR)) and two hemodynamic parameters (i.e., peak WSS (peakWSS), and pressure loss coefficient (PLc)) were found to differ significantly between the ruptured and unruptured aneurysms and proved by receiver operating characteristic (ROC) analysis to have potential value for differentiating the rupture status of aneurysm with the areas under curve (AUCs) ranging from 0.681 to 0.763. Integrating V, SR, peakWSS and PLc or some of them into regression models considerably improved the classification of aneurysms, elevating AUC up to 0.864, which indicates that morphological and hemodynamic parameters have complementary roles in assessing the risk of aneurysm rupture.

Aneurysm risk metrics and hemodynamics are associated with greater vessel wall enhancement in intracranial aneurysms

Vessel wall enhancement (VWE) in contrast-enhanced magnetic resonance imaging (MRI) is a potential biomarker for intracranial aneurysm (IA) risk stratification. In this study, we investigated the relationship between VWE features, risk metrics, morphology and hemodynamics in 41 unruptured aneurysms. We reconstructed the IA geometries from MR angiography and mapped pituitary stalk-normalized MRI intensity on the aneurysm surface using an in-house tool. For each case, we calculated the maximum intensity (CRstalk) and IA risk (via size and the rupture resemblance score (RRS)). We performed correlation analysis to assess relationships between CRstalk and IA risk metrics (size and RRS), as well as each parameter encompassed in RRS, i.e. aneurysmal size ratio (SR), normalized wall shear stress (WSS) and oscillatory shear index. We found that CRstalk had a strong correlation (Pearson correlation coefficient, PCC = 0.630) with size and a moderate correlation (PCC = 0.472) with RRS, indicating an association between VWE and IA risk. Furthermore, CRstalk had a weak negative correlation with normalized WSS (PCC = -0.320) and a weak positive correlation with SR (PCC = 0.390). Local voxel-based analysis showed only a weak negative correlation between normalized WSS and contrast-enhanced MRI signal intensity (PCC = -0.240), suggesting that if low-normalized WSS induces enhancement-associated pathobiology, the effect is not localized.

Hemodynamic Investigation of the Effectiveness of a Two Overlapping Flow Diverter Configuration for Cerebral Aneurysm Treatment

Flow diverters (FDs) are widely employed as endovascular treatment devices for large or wide-neck cerebral aneurysms. Occasionally, overlapped FDs are deployed to enhance the flow diversion effect. In this study, we investigated the hemodynamics of overlapping FDs via computational fluid dynamics (CFD) simulations. We reproduced the arterial geometry of a patient who had experienced the deployment of two overlapping FDs. We utilized two stent patterns, namely the patterns for one FD and two overlapping FDs. We calculated the velocity, mass flow rate, wall shear stress, and pressure loss coefficient as well as their change rates for each pattern relative to the no-FD pattern results. The CFD simulation results indicated that the characteristics of the blood flow inside the aneurysm were minimally affected by the deployment of a single FD; in contrast, the overlapping FD pattern results revealed significant changes in the flow. Further, the velocity at an inspection plane within the aneurysm sac decreased by up to 92.2% and 31.0% in the cases of the overlapping and single FD patterns, respectively, relative to the no-FD pattern. The simulations successfully reproduced the hemodynamics, and the qualitative and quantitative investigations are meaningful with regard to the clinical outcomes of overlapped FD deployment.

FSI modeling on the effect of artery-aneurysm thickness and coil embolization in patient cases

BACKGROUND AND OBJECTIVE

The attainment of a methodology to simulate the hemodynamic in patient-specific cerebral vessels with aneurysms is still a challenge. The novelty of this work is focused on the effect of coil embolization in a realistic cerebral aneurysm, according to the vessel wall thickness and aneurysm thickness, through transient FSI simulations.

METHODS

The quality of the mesh for simulations was checked with a specific mesh convergence study; and the numerical methodology was validated using numerical research data of the literature. The model was implemented in ANSYS® software. The total deformation and equivalent stress evolution in the studied cases, before and after coil embolization, were compared. More than 20 different models were employed due to different arterial wall thickness and aneurysm wall thickness combinations.

RESULTS

The obtained results have showed that deformation and stress values are highly influenced with the sac thickness. The thinner sac aneurysm thickness is, the greater deformation and stress are. The results after coil embolization process have highlighted that considering typical values of arterial wall thickness and aneurysm thickness 0.3 mm and 0.15 mm respectively, a deformation reduction around 50% and a stress reduction around 70% can be achieved.

CONCLUSIONS

The proposed methodology is a step forward in the personalized medicine, quantifying the aneurysm rupture risk reduction, and helping the medical team in the preoperative planning, or to deciding the optimal treatment.