Collaborating investigators: Prof. CW McIntyre, Dr. SR Kharche.
Description: The host group is led by renowned clinical-imaging expert Dr CW McIntyre and experienced computer scientist-applied mathematician Dr S. R. Kharche. The project entails simulations of blood flow, CT agent and drug transport in the liver and kidneys. The in silico models test the effectiveness of new therapies. The models also provide the means to perform virtual imaging that supports clinical imaging research design. Module testing is planned during the first year (2020-2021) of the project. Computational imaging case studies are expected to lead to tested platform release with increased functionality, tested working models.
The host group have previously implemented two new modules into SimVascular platform that permit computational imaging based investigations. To permit simulation of blood flow throughout an organ (vascular and tissue spaces), a new core module implementing Darcy’s law (White et al., 2016) has already been integrated into the platform (Figure 2, A). In case vasculature geometries are unavailable, another new module based on biophysical morphometry and space filling algorithm (Kharche et al., 2018) has been implemented into SimVascular (Figure 2, B). During the project, the two modules will be thoroughly tested and used in case studies simulating CT agent movement in organs under disease (dialysis induced ischemic stress) and therapy (therapeutic hypothermia) conditions.
Planned delivery date: December 2020.
Data: Clinical CT, VPH human images for anatomy, Poland kidney data set, liver vasculature model.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Prof. Ting-Yim Lee and Dr. Aaron So; Overseas.
Description: The Ting Lee team will be onboarded at the onset of the project as they intend contributing to the image processing part of the WP. The models are planned to be provided to the team by the end of the first year.
The platform’s core modules will be used without modification. Team #1 have already provided 25 CTA (Figure 3, A) and corresponding angiograms. The imaging data will be collaboratively processed by host and team #1 members to generate a repository of coronary vasculature structural models (Figure 3, B). Simultaneously, realistic physiological LPNs and effects of intramyocardial pressure will be implemented (Kim et al., 2010). By combining the structures and LPNs, working FSI models will be tested for use in the Lee group. FFRCT estimation in the complete data set will then be performed collaboratively as a case study and platform application.
Planned delivery date: Segmentation by Dec. 2020, FFRCT template simulation by April 2021.
Data:25 CT imaging data sets, along with invasive measurement of FFR. All data is anonymized.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Prof. Udunna Anazodo
Description: The Anazodo team will be onboarded at the onset of the project as they will participate in the image processing part. It is expected that models will be delivered to them in the first year of the project.
The Anazodo team (team #2) have provided 12 MRA data sets to the project. The data consists of healthy and aged brains. The MRA images will be collaboratively processed by the host and Anazodo teams using SimVascular platform to generate cerebrovascular arterial trees (Wright et al., 2013) within the first year of the project (Figure 5). Fluid flow in these arterial geometries will be simulated using FSI modeling. In the FSI models, amyloid plaque effects will be implemented by assigning literature derived vascular wall properties. LPNs will be implemented to simulate autoregulation bearing inlet and outlet boundary conditions. As the cerebrovascular geometry is large, a computationally efficient 1D model will be implemented (Alastruey et al., 2007; Melis et al., 2019) that deploys SimVascular platform’s 1D solver module, called SV1DSolve. The model will be provided to team #2 to perform the case studies with relevance to identification of cerebral blood flow affecting factors.
Planned delivery date: Segmentation by Dec. 2020, 1D template simulation by April 2021.
Data:The Anazodo team (team #2) have provided 12 MRA data sets to the project.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Prof. Tamie L. Poepping.
Description: Heterogeneous vascular wall properties and aneurysm growth functionality will be implemented. Detailed LPNs will provide physiological boundary conditions. Further, known flow diverting devices’ representations will be included into the model.
Whereas no modification to the core modules of the platform is required for WP4, a new cerebral aneurysm model repository (Figure 6) will be implemented. WP4 consists of two concurrent parts.
In the first part, a working FSI model will be implemented using available 3D geometries (Figure 6). Heterogeneous vascular wall properties and aneurysm growth functionality will be implemented. Detailed LPNs will provide physiological boundary conditions. Further, known flow diverting devices’ representations will be included into the model (Cebral et al., 2011a).
Measures such as oscillatory wall shear-stress metrics (e.g., oscillatory shear index) and relative residence times (Butty et al., 2002) will be computed to construct a rupture risk index. Other measures for risk of rupture, such as in-flow jet properties, shear concentration, viscous dissipation, and complexity of flow (Cebral et al., 2011b), will also be computed. The FSI models will be used to further define the nature of subject specific clinical-experimental-computational data flow in the second part of the work.
In the second part, modeling based on clinical and experimental data will be undertaken. The imaging data, typically in the form of 4D MRI or MRA, and flow rate data obtained using modalities such as phase-contrast magnetic resonance imaging (Ferrandez et al., 2000) for inlet boundary conditions will also be provided. The whole body model from the Goldman team will be used to confirm consistency of all boundary conditions.
Data:Open Source data.
Simulations: 1D, FSI, embedding into UA whole brain vasculature.
Publications: None to date.
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Collaborating investigators: Prof. Donald G. Welsh.
Description: The WP3 FSI model will be adapted in this part of the project. The role of CoW variants in the presence of vasospasm on blood flow profiles will be simulated (Alastruey et al., 2007; Melis et al., 2019) to provide pressure, flow, as well as their time derivatives as biomarkers that can be combined to generate waveform features that are easy to obtain clinically.
The Welsh and Finger groups have agreed to provide subject specific data in the second year of the project. Upon assessment of the nature of the data, the generic model will be adapted to generate subject specific models to provide personalized risk assessment.
Planned delivery date: Use UA model and do experiments by April 2021.
Data: Subject specific data from Welsh and Finger groups.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Prof. Geoffrey Pickering.
Description: The platform’s model repository will be extended in this part of the project, without modification to core modules. Available model geometries (Figure 7, B) combined with physiological boundary condition using LPNs will be implemented to provide the Pickering group with a FSI model capable of simulating aortic dissection. The Pickering group are preparing standard clinical monitoring data (Pirola et al., 2018; Bonfanti et al., 2019) which will assess platform applicability from image processing to 3D hemodynamic FSI simulations. The data will consist of clinical CT scans, contrast enhanced CT, aortic doppler ultrasound, and invasive blood pressure measurements. Together, the data will permit construction and validation of personalized in silico 3D aorta models that permit accurate estimation of dissection wall shear indices.
Planned delivery date: Use literature models and do experiments by December 2021.
Data: From literature, unless we are given images.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Dr. D. Goldman.
Description: The whole body 1D arteriovenous model (Muller & Toro, 2014; Blanco et al., 2015) will be implemented into the platform at an early stage of the project (Figure 8). A validated dialysis vascular circuit model (Huberts et al., 2012a; Huberts et al., 2012b) will be implemented in line with SimVascular’s modular programming paradigm, and coupled to the 1D model. The highly scalable 1D solver module, called “SV1DSolve” in the platform will be used extensively in this model. Accurate physiological lumped parameter networks’ boundary conditions (Chnafa et al., 2018) will be implemented. The model will be used to quantify the effects of dialysis and hypothermia on clinically measurable hemodynamic parameters. WP7, Deliverables and timeline: WP7 will be led by Prof. Goldman with support from the developer team. This work package’s tasks will span the duration of the project with onboarding at the onset. Dr. McIntyre has agreed to provide ultrasound (echocardiography and Transcranial Doppler), CT, and cine-MRI data to this work package to assist with testing and scientific investigations. If time permits, a whole body small animal (rodent) model will be implemented to assist onboarding of additional basic science research teams (Aslanidou et al., 2016).
Planned delivery date: Whole body models and dialysis model by Dec. 2020, studies rest of the time.
Data: 1D whole body arterio-venous models of human and mouse vasculature, 0D model of dialysis circuit.
Simulations: None to date.
Publications: None to date.
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Collaborating investigators: Dr. Guido Filler.
Description: To simulate metabolism of drugs studied by GF recently.
Planned delivery date: Use the kidney model for this study, delivery around Dec 2021.
Data: AKI model, drug metabolism in children from Guido.
Simulations: None to date.
Publications: None to date.
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