Dataset Information

Challenges in hemodynamics assessment in complex neurovascular geometries using computational fluid dynamics and benchtop flow simulation in 3D printed patient specific phantoms.

ABSTRACT:

Purpose

Complex hemodynamics assessments, as those related to carotid stenosis, are not always easily straightforward due to multifaceted challenges presented by the collateral flow in the Circle of Willis (CoW) and brain flow autoregulation. Advanced computational and benchtop methods to investigate hemodynamics aspects related to such complex flows are often used, however both have limitations and could lead to results which may diverge. In this study we investigated these aspects by performing correlated computational fluid dynamics (CFD) simulations and benchtop experiments in patient specific 3D printed phantoms.

Materials and methods

To investigate the flow in patients with carotid stenosis, we built two patient specific phantoms which contained the arterial lesion of interest, all main arteries leading to the brain, the CoW and main arteries branching from it. Each phantom was connected to a generic aortic arch. A programmable pump was connected and flow parameters were measured proximal and distal to the lesion and the contralateral arteries. The patient 3D geometry was used to perform a set of CFD simulations where inflow boundary conditions matched the experimental ones. Flow conditions were recorded at the same locations as the experimental setup. Further exploration into the translation from experimental to CFD was also performed by customizing vascular segmentation and physically manipulating arterial compliance properties.

Results

We initially observed significant differences between the CFD recordings and the experimental setup. Most of the differences were due to changes in phantom geometry when subjected to physiological pressures and simplistic outflow boundary conditions in the CFD simulations which do not account for pulsatility and nonlinear phenomena. Further work confirms the need for dynamic mesh behavior within CFD simulations attempting to computationally mimic 3D-printed benchtop experiments. Additionally, CFD simulation may benefit from considering geometry specific to a 3D-printed vascular phantom.

SUBMITTER: Paccione E

PROVIDER: S-EPMC8018694 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:To assess whether in-silico models can be used to predict the risk of thrombus formation in pulmonary artery pressure sensors (PAPS), a chronic animal study using pigs was conducted. Computed tomography (CT) data was acquired before and immediately after implantation, as well as one and three months after the implantation. Devices were implanted into 10 pigs, each one in the left and right pulmonary artery (PA), to reduce the required number of animal experiments. The implantation procedure aimed at facilitating optimal and non-optimal positioning of the devices to increase chances of thrombus formation. Eight devices were positioned non-optimally. Three devices were positioned in the main PA instead of the left and right PA. Pre-interventional PA geometries were reconstructed from the respective CT images, and the devices were virtually implanted at the exact sites and orientations indicated by the follow-up CT after one month. Transient intra-arterial hemodynamics were calculated using computational fluid dynamics. Volume flow rates were modelled specifically matching the animals body weights. Wall shear stresses (WSS) and oscillatory shear indices (OSI) before and after device implantation were compared. Simulations revealed no relevant changes in any investigated hemodynamic parameters due to device implantation. Even in cases, where devices were implanted in a non-optimal manner, no marked differences in hemodynamic parameters compared to devices implanted in an optimal position were found. Before implantation time and surface-averaged WSS was 2.35±0.47 Pa, whereas OSI was 0.08±0.17, respectively. Areas affected by low WSS magnitudes were 2.5±2.7 cm2, whereas the areas affected by high OSI were 18.1±6.3 cm2. After device implantation, WSS and OSI were 2.45±0.49 Pa and 0.08±0.16, respectively. Surface areas affected by low WSS and high OSI were 2.9±2.7 cm2, and 18.4±6.1 cm2, respectively. This in-silico study indicates that no clinically relevant differences in intra-arterial hemodynamics are occurring after device implantation, even at non-optimal positioning of the sensor. Simultaneously, no embolic events were observed, suggesting that the risk for thrombus formation after device implantation is low and independent of the sensor position.

Project description:PurposeInterventional fluorescence imaging is increasingly being utilized to quantify cancer biomarkers in both clinical and preclinical models, yet absolute quantification is complicated by many factors. The use of optical phantoms has been suggested by multiple professional organizations for quantitative performance assessment of fluorescence guidance imaging systems. This concept can be further extended to provide standardized tools to compare and assess image analysis metrics.Procedures3D-printed fluorescence phantoms based on solid tumor models were developed with representative bio-mimicking optical properties. Phantoms were produced with discrete tumors embedded with an NIR fluorophore of fixed concentration and either zero or 3% non-specific fluorophore in the surrounding material. These phantoms were first imaged by two fluorescence imaging systems using two methods of image segmentation, and four assessment metrics were calculated to demonstrate variability in the quantitative assessment of system performance. The same analysis techniques were then applied to one tumor model with decreasing tumor fluorophore concentrations.ResultsThese anatomical phantom models demonstrate the ability to use 3D printing to manufacture anthropomorphic shapes with a wide range of reduced scattering (μs': 0.24-1.06 mm-1) and absorption (μa: 0.005-0.14 mm-1) properties. The phantom imaging and analysis highlight variability in the measured sensitivity metrics associated with tumor visualization.Conclusions3D printing techniques provide a platform for demonstrating complex biological models that introduce real-world complexities for quantifying fluorescence image data. Controlled iterative development of these phantom designs can be used as a tool to advance the field and provide context for consensus-building beyond performance assessment of fluorescence imaging platforms, and extend support for standardizing how quantitative metrics are extracted from imaging data and reported in literature.