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Báez-Yáñez MG, Schellekens W, Bhogal AA, Roefs ECA, van Osch MJP, Siero JCW, Petridou N. A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595716. [PMID: 38826311 PMCID: PMC11142244 DOI: 10.1101/2024.05.24.595716] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Wouter Schellekens
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Donders Centre for Cognitive Neuroimaging, Radboud UMC, Nijmegen, Netherlands
| | - Alex A Bhogal
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Emiel C A Roefs
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Matthias J P van Osch
- C.J. Gorter MRI Center, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Jeroen C W Siero
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Natalia Petridou
- Translational Neuroimaging Group, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
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Rundfeldt HC, Lee CM, Lee H, Jung KH, Chang H, Kim HJ. Cerebral perfusion simulation using realistically generated synthetic trees for healthy and stroke patients. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 244:107956. [PMID: 38061114 DOI: 10.1016/j.cmpb.2023.107956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Revised: 11/17/2023] [Accepted: 11/27/2023] [Indexed: 01/26/2024]
Abstract
BACKGROUND AND OBJECTIVE Cerebral vascular diseases are among the most burdensome diseases faced by society. However, investigating the pathophysiology of diseases as well as developing future treatments still relies heavily on expensive in-vivo and in-vitro studies. The generation of realistic, patient-specific models of the cerebrovascular system capable of simulating hemodynamics and perfusion promises the ability to simulate diseased states, therefore accelerating development cycles using in silico studies and opening opportunities for the individual assessment of diseased states, treatment planning, and the prediction of outcomes. By providing a patient-specific, anatomically detailed and validated model of the human cerebral vascular system, we aim to provide the basis for future in silico investigations of the cerebral physiology and pathology. METHODS In this retrospective study, a processing pipeline for patient-specific quantification of cerebral perfusion was developed and applied to healthy individuals and a stroke patient. Major arteries are segmented from 3T MR angiography data. A synthetic tree generation algorithm titled tissue-growth based optimization (GBO)1 is used to extend vascular trees beyond the imaging resolution. To investigate the anatomical accuracy of the generated trees, morphological parameters are compared against those of 7 T MRI, 9.4 T MRI, and dissection data. Using the generated vessel model, hemodynamics and perfusion are simulated by solving one-dimensional blood flow equations combined with Darcy flow equations. RESULTS Morphological data of three healthy individuals (mean age 47 years ± 15.9 [SD], 2 female) was analyzed. Bifurcation and physiological characteristics of the synthetically generated vessels are comparable to those of dissection data. The inability of MRI based segmentation to resolve small branches and the small volume investigated cause a mismatch in the comparison to MRI data. Cerebral perfusion was estimated for healthy individuals and a stroke patient. The simulated perfusion is compared against Arterial-Spin-Labeling MRI perfusion data. Good qualitative agreement is found between simulated and measured cerebral blood flow (CBF)2. Ischemic regions are predicted well, however ischemia severity is overestimated. CONCLUSIONS GBO successfully generates detailed cerebral vascular models with realistic morphological parameters. Simulations based on the resulting networks predict perfusion territories and ischemic regions successfully.
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Affiliation(s)
- Hans Christian Rundfeldt
- Korea Advanced Institute of Science and Technology, Mechanical Engineering, Republic of Korea; Karlsruhe Institute of Technology, Mechanical Engineering, Germany
| | - Chang Min Lee
- Korea Advanced Institute of Science and Technology, Mechanical Engineering, Republic of Korea
| | - Hanyoung Lee
- Chung-ang University, College of Pharmacy, Republic of Korea
| | - Keun-Hwa Jung
- Seoul National University Hospital, Department of Neurology, Republic of Korea
| | - Hyeyeon Chang
- Konyang University Hospital, Department of Neurology, Republic of Korea
| | - Hyun Jin Kim
- Korea Advanced Institute of Science and Technology, Mechanical Engineering, Republic of Korea.
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Samavaki M, Söderholm S, Nia AZ, Pursiainen S. Modeling of blood flow in cerebral arterial circulation and its dynamic impact on electrical conductivity in a realistic multi-compartment head model. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 244:107983. [PMID: 38157828 DOI: 10.1016/j.cmpb.2023.107983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/08/2023] [Accepted: 12/15/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND OBJECTIVE This study aims to assess the dynamic impact of non-Newtonian cerebral arterial circulation on electrical conductivity within a realistic multi-compartment head model. Evaluating this research question is crucial and challenging due to its relevance to electrophysiological modalities like transcranial electrical stimulation (tES), electro-/magnetoencephalography (EEG/MEG), and electrical impedance tomography (EIT). In these modalities, accurate forward modeling depends on the electrical conductivity, which is affected by complex tortuous vessel networks, limited data acquisition in Magnetic Resonance Imaging (MRI), and non-linear blood flow phenomena, including shear rate and viscosity in non-Newtonian fluid. METHODS To obtain an approximation for the blood concentration, we first use Navier-Stokes equations (NSEs) to solve for the pressure and velocity of the blood in the major vessels. Then Fick's law is used to solve for the blood concentration in the tissues. Finally, Archie's law is used to estimate the electrical conductivity distribution based on the blood concentration. RESULTS The results, obtained with an open 7 Tesla MRI dataset, suggest that a dynamic model of cerebral blood flow (CBF) for both arterial and microcirculation can be established; we find blood pressure and electrical conductivity distributions given a numerically simulated pulse sequence and approximate the blood concentration and electrical conductivity inside the brain based on those. CONCLUSIONS Our model provides an approximation of the dynamical blood flow and the corresponding electrical conductivity distribution in the different parts of the brain. The advantage of our approach is that it is applicable with limited a priori information about the blood flow and with an arbitrary head model distinguishing the arteries.
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Affiliation(s)
- Maryam Samavaki
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland.
| | - Santtu Söderholm
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
| | - Arash Zarrin Nia
- Faculty of Mathematics, K. N. Toosi University of Technology, Mirdamad Blvd, No. 470, Tehran, 1676-53381, Iran
| | - Sampsa Pursiainen
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
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Samavaki M, Oluwatoki Yusuf Y, Nia AZ, Söderholm S, Lahtinen J, Galaz Prieto F, Pursiainen S. Pressure-Poisson equation in numerical simulation of cerebral arterial circulation and its effect on the electrical conductivity of the brain. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107844. [PMID: 37852144 DOI: 10.1016/j.cmpb.2023.107844] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 09/28/2023] [Accepted: 10/03/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND AND OBJECTIVE This study considers dynamic modeling of the cerebral arterial circulation and reconstructing an atlas for the electrical conductivity of the brain. Electrical conductivity is a governing parameter in several electrophysiological modalities applied in neuroscience, such as electroencephalography (EEG), transcranial electrical stimulation (tES), and electrical impedance tomography (EIT). While high-resolution 7-Tesla (T) Magnetic Resonance Imaging (MRI) data allow for reconstructing the cerebral arteries with a cross-sectional diameter larger than the voxel size, electrical conductivity cannot be directly inferred from MRI data. Brain models of electrophysiology typically associate each brain tissue compartment with a constant electrical conductivity, omitting any dynamic effects of cerebral blood circulation. Incorporating those effects poses the challenge of solving a system of incompressible Navier-Stokes equations (NSEs) in a realistic multi-compartment head model. However, using a simplified circulation model is well-motivated since, on the one hand, the complete system does not always have a numerically stable solution and, on the other hand, the full set of arteries cannot be perfectly reconstructed from the MRI data, meaning that any solution will be approximative. METHODS We postulate that circulation in the distinguishable arteries can be estimated via the pressure-Poisson equation (PPE), which is coupled with Fick's law of diffusion for microcirculation. To establish a fluid exchange model between arteries and microarteries, a boundary condition derived from the Hagen-Poisseuille model is applied. The relationship between the estimated volumetric blood concentration and the electrical conductivity of the brain tissue is approximated through Archie's law for fluid flow in porous media. RESULTS Through the formulation of the PPE and a set of boundary conditions (BCs) based on the Hagen-Poisseuille model, we obtained an equivalent formulation of the incompressible Stokes equation (SE). Thus, allowing effective blood pressure estimation in cerebral arteries segmented from open 7T MRI data. CONCLUSIONS As a result of this research, we developed and built a useful modeling framework that accounts for the effects of dynamic blood flow on a novel MRI-based electrical conductivity atlas. The electrical conductivity perturbation obtained in numerical experiments has an appropriate overall match with previous studies on this subject. Further research to validate these results will be necessary.
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Affiliation(s)
- Maryam Samavaki
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland.
| | - Yusuf Oluwatoki Yusuf
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland; Aix Marseille Univ, CNRS, Centrale Marseille, Institut Fresnel, Marseille, France
| | - Arash Zarrin Nia
- Faculty of Mathematics, K. N. Toosi University of Technology, Mirdamad Blvd, No. 470, Tehran, 1676-53381, Iran
| | - Santtu Söderholm
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
| | - Joonas Lahtinen
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
| | - Fernando Galaz Prieto
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
| | - Sampsa Pursiainen
- Mathematics, Computing Sciences, Tampere University, Korkeakoulunkatu 1, Tampere University, 33014, Finland
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Báez-Yáñez MG, Siero JCW, Petridou N. A mechanistic computational framework to investigate the hemodynamic fingerprint of the blood oxygenation level-dependent signal. NMR IN BIOMEDICINE 2023; 36:e5026. [PMID: 37643645 DOI: 10.1002/nbm.5026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 07/18/2023] [Accepted: 07/28/2023] [Indexed: 08/31/2023]
Abstract
Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is one of the most used imaging techniques to map brain activity or to obtain clinical information about human cortical vasculature, in both healthy and disease conditions. Nevertheless, BOLD fMRI is an indirect measurement of brain functioning triggered by neurovascular coupling. The origin of the BOLD signal is quite complex, and the signal formation thus depends, among other factors, on the topology of the cortical vasculature and the associated hemodynamic changes. To understand the hemodynamic evolution of the BOLD signal response in humans, it is beneficial to have a computational framework available that virtually resembles the human cortical vasculature, and simulates hemodynamic changes and corresponding MRI signal changes via interactions of intrinsic biophysical and magnetic properties of the tissues. To this end, we have developed a mechanistic computational framework that simulates the hemodynamic fingerprint of the BOLD signal based on a statistically defined, three-dimensional, vascular model that approaches the human cortical vascular architecture. The microvasculature is approximated through a Voronoi tessellation method and the macrovasculature is adapted from two-photon microscopy mice data. Using this computational framework, we simulated hemodynamic changes-cerebral blood flow, cerebral blood volume, and blood oxygen saturation-induced by virtual arterial dilation. Then we computed local magnetic field disturbances generated by the vascular topology and the corresponding blood oxygen saturation changes. This mechanistic computational framework also considers the intrinsic biophysical and magnetic properties of nearby tissue, such as water diffusion and relaxation properties, resulting in a dynamic BOLD signal response. The proposed mechanistic computational framework provides an integrated biophysical model that can offer better insights regarding the spatial and temporal properties of the BOLD signal changes.
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Affiliation(s)
- Mario Gilberto Báez-Yáñez
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen C W Siero
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Natalia Petridou
- Department of Radiology, Centre for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
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Epp R, Glück C, Binder NF, El Amki M, Weber B, Wegener S, Jenny P, Schmid F. The role of leptomeningeal collaterals in redistributing blood flow during stroke. PLoS Comput Biol 2023; 19:e1011496. [PMID: 37871109 PMCID: PMC10621965 DOI: 10.1371/journal.pcbi.1011496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 11/02/2023] [Accepted: 09/03/2023] [Indexed: 10/25/2023] Open
Abstract
Leptomeningeal collaterals (LMCs) connect the main cerebral arteries and provide alternative pathways for blood flow during ischaemic stroke. This is beneficial for reducing infarct size and reperfusion success after treatment. However, a better understanding of how LMCs affect blood flow distribution is indispensable to improve therapeutic strategies. Here, we present a novel in silico approach that incorporates case-specific in vivo data into a computational model to simulate blood flow in large semi-realistic microvascular networks from two different mouse strains, characterised by having many and almost no LMCs between middle and anterior cerebral artery (MCA, ACA) territories. This framework is unique because our simulations are directly aligned with in vivo data. Moreover, it allows us to analyse perfusion characteristics quantitatively across all vessel types and for networks with no, few and many LMCs. We show that the occlusion of the MCA directly caused a redistribution of blood that was characterised by increased flow in LMCs. Interestingly, the improved perfusion of MCA-sided microvessels after dilating LMCs came at the cost of a reduced blood supply in other brain areas. This effect was enhanced in regions close to the watershed line and when the number of LMCs was increased. Additional dilations of surface and penetrating arteries after stroke improved perfusion across the entire vasculature and partially recovered flow in the obstructed region, especially in networks with many LMCs, which further underlines the role of LMCs during stroke.
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Affiliation(s)
- Robert Epp
- Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
| | - Chaim Glück
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Nadine Felizitas Binder
- Deptartment of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Mohamad El Amki
- Deptartment of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Susanne Wegener
- Deptartment of Neurology, University Hospital Zurich and University of Zurich, Zurich, Switzerland
| | - Patrick Jenny
- Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
| | - Franca Schmid
- Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
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7
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Lee YT, Chen SJ. Graph theory applications in congenital heart disease. Sci Rep 2023; 13:11135. [PMID: 37429950 DOI: 10.1038/s41598-023-38233-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 07/05/2023] [Indexed: 07/12/2023] Open
Abstract
Graph theory can be used to address problems with complex network structures. Congenital heart diseases (CHDs) involve complex abnormal connections between chambers, vessels, and organs. We proposed a new method to represent CHDs based on graph theory, wherein vertices were defined as the spaces through which blood flows and edges were defined by the blood flow between the spaces and direction of the blood flow. The CHDs of tetralogy of Fallot (TOF) and transposition of the great arteries (TGA) were selected as examples for constructing directed graphs and binary adjacency matrices. Patients with totally repaired TOF, surgically corrected d-TGA, and Fontan circulation undergoing four-dimensional (4D) flow magnetic resonance imaging (MRI) were included as examples for constructing the weighted adjacency matrices. The directed graphs and binary adjacency matrices of the normal heart, extreme TOF undergoing a right modified Blalock-Taussig shunt, and d-TGA with a ventricular septal defect were constructed. The weighted adjacency matrix of totally repaired TOF was constructed using the peak velocities obtained from 4D flow MRI. The developed method is promising for representing CHDs and may be helpful in developing artificial intelligence and conducting future research on CHD.
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Affiliation(s)
- Yao-Ting Lee
- Department of Medical Imaging, National Taiwan University Hospital and Children Hospital, National Taiwan University, 7 Chung-Shan South Road, Taipei, 10002, Taiwan
| | - Shyh-Jye Chen
- Department of Medical Imaging, National Taiwan University Hospital and Children Hospital, National Taiwan University, 7 Chung-Shan South Road, Taipei, 10002, Taiwan.
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Müller LO, Watanabe SM, Toro EF, Feijóo RA, Blanco PJ. An anatomically detailed arterial-venous network model. Cerebral and coronary circulation. Front Physiol 2023; 14:1162391. [PMID: 37435309 PMCID: PMC10332167 DOI: 10.3389/fphys.2023.1162391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 05/22/2023] [Indexed: 07/13/2023] Open
Abstract
In recent years, several works have addressed the problem of modeling blood flow phenomena in veins, as a response to increasing interest in modeling pathological conditions occurring in the venous network and their connection with the rest of the circulatory system. In this context, one-dimensional models have proven to be extremely efficient in delivering predictions in agreement with in-vivo observations. Pursuing the increase of anatomical accuracy and its connection to physiological principles in haemodynamics simulations, the main aim of this work is to describe a novel closed-loop Anatomically-Detailed Arterial-Venous Network (ADAVN) model. An extremely refined description of the arterial network consisting of 2,185 arterial vessels is coupled to a novel venous network featuring high level of anatomical detail in cerebral and coronary vascular territories. The entire venous network comprises 189 venous vessels, 79 of which drain the brain and 14 are coronary veins. Fundamental physiological mechanisms accounting for the interaction of brain blood flow with the cerebro-spinal fluid and of the coronary circulation with the cardiac mechanics are considered. Several issues related to the coupling of arterial and venous vessels at the microcirculation level are discussed in detail. Numerical simulations are compared to patient records published in the literature to show the descriptive capabilities of the model. Furthermore, a local sensitivity analysis is performed, evidencing the high impact of the venous circulation on main cardiovascular variables.
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Affiliation(s)
- Lucas O. Müller
- Department of Mathematics, University of Trento, Trento, Italy
| | - Sansuke M. Watanabe
- Federal University of Agreste de Pernambuco, UFAPE, Garanhuns, Brazil
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
| | - Eleuterio F. Toro
- Laboratory of Applied Mathematics, Department of Civil, Environmental and Mechanical Engineering, University of Trento, Trento, Italy
| | - Raúl A. Feijóo
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
- National Laboratory for Scientific Computing, LNCC/MCTI, Petrópolis, Brazil
| | - Pablo J. Blanco
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
- National Laboratory for Scientific Computing, LNCC/MCTI, Petrópolis, Brazil
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Daher A, Payne S. A network-based model of dynamic cerebral autoregulation. Microvasc Res 2023; 147:104503. [PMID: 36773930 DOI: 10.1016/j.mvr.2023.104503] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/21/2023] [Accepted: 02/06/2023] [Indexed: 02/11/2023]
Abstract
Cerebrovascular diseases continue to be one of the leading causes of morbidity and mortality in humans. Abnormalities in dynamic cerebral autoregulation (dCA) have been implicated in many of these disease conditions. Accurate models are therefore needed to better understand the complex pathophysiology behind impaired dCA. We thus present here a simple framework for modelling a vessel-driven network model of dCA in the microvasculature, as opposed to the conventional compartmental modelling approach. Network models incorporate the actual connectivity and anatomy of the vasculature, thereby allowing us to include and trace changes in the calibre and morphology of individual vessels, investigate the spatial specificity and heterogeneity of the various control mechanisms to help disentangle their contributions, and link the model parameters to the actual network physiology. The proposed control feedback mechanisms are incorporated at the level of the individual vessel, and the dynamic pressure and flow fields are solved for here within a simple vessel network. In response to an upstream pressure drop, the network is found to be able to recover cerebral blood flow (CBF) while exhibiting the characteristic autoregulatory behaviour in terms of changes in vessel calibre and the biphasic flow response. We assess the feasibility of our formulation in larger networks by comparing the simulation results to those obtained using a one-dimensional (1D) model of CBF applied to the same microvasculature network and find that our model results are in very good agreement with the 1D solution, while significantly reducing the computational cost, thus enabling more detailed models of network behaviour to be adopted in the future. Accurate and computationally feasible models of dCA that are more representative of the vasculature can help increase the translatability of haemodynamic models into the clinical environment, which would help develop more informed treatment guidelines for patients with cerebrovascular diseases.
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Affiliation(s)
- Ali Daher
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, United Kingdom.
| | - Stephen Payne
- Institute of Applied Mechanics, National Taiwan University, Taiwan
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10
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Fritz M. Tumor Evolution Models of Phase-Field Type with Nonlocal Effects and Angiogenesis. Bull Math Biol 2023; 85:44. [PMID: 37081144 DOI: 10.1007/s11538-023-01151-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/27/2023] [Indexed: 04/22/2023]
Abstract
In this survey article, a variety of systems modeling tumor growth are discussed. In accordance with the hallmarks of cancer, the described models incorporate the primary characteristics of cancer evolution. Specifically, we focus on diffusive interface models and follow the phase-field approach that describes the tumor as a collection of cells. Such systems are based on a multiphase approach that employs constitutive laws and balance laws for individual constituents. In mathematical oncology, numerous biological phenomena are involved, including temporal and spatial nonlocal effects, complex nonlinearities, stochasticity, and mixed-dimensional couplings. Using the models, for instance, we can express angiogenesis and cell-to-matrix adhesion effects. Finally, we offer some methods for numerically approximating the models and show simulations of the tumor's evolution in response to various biological effects.
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Affiliation(s)
- Marvin Fritz
- Computational Methods for PDEs, Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria.
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11
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A skeleton context-aware 3D fully convolutional network for abdominal artery segmentation. Int J Comput Assist Radiol Surg 2023; 18:461-472. [PMID: 36273078 DOI: 10.1007/s11548-022-02767-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 09/26/2022] [Indexed: 11/05/2022]
Abstract
PURPOSE This paper aims to propose a deep learning-based method for abdominal artery segmentation. Blood vessel structure information is essential to diagnosis and treatment. Accurate blood vessel segmentation is critical to preoperative planning. Although deep learning-based methods perform well on large organs, segmenting small organs such as blood vessels is challenging due to complicated branching structures and positions. We propose a 3D deep learning network from a skeleton context-aware perspective to improve segmentation accuracy. In addition, we propose a novel 3D patch generation method which could strengthen the structural diversity of a training data set. METHOD The proposed method segments abdominal arteries from an abdominal computed tomography (CT) volume using a 3D fully convolutional network (FCN). We add two auxiliary tasks to the network to extract the skeleton context of abdominal arteries. In addition, our skeleton-based patch generation (SBPG) method further enables the FCN to segment small arteries. SBPG generates a 3D patch from a CT volume by leveraging artery skeleton information. These methods improve the segmentation accuracies of small arteries. RESULTS We used 20 cases of abdominal CT volumes to evaluate the proposed method. The experimental results showed that our method outperformed previous segmentation accuracies. The averaged precision rate, recall rate, and F-measure were 95.5%, 91.0%, and 93.2%, respectively. Compared to a baseline method, our method improved 1.5% the averaged recall rate and 0.7% the averaged F-measure. CONCLUSIONS We present a skeleton context-aware 3D FCN to segment abdominal arteries from an abdominal CT volume. In addition, we propose a 3D patch generation method. Our fully automated method segmented most of the abdominal artery regions. The method produced competitive segmentation performance compared to previous methods.
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Abdellah M, Cantero JJG, Guerrero NR, Foni A, Coggan JS, Calì C, Agus M, Zisis E, Keller D, Hadwiger M, Magistretti PJ, Markram H, Schürmann F. Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience. Brief Bioinform 2022; 24:6847753. [PMID: 36434788 PMCID: PMC9851302 DOI: 10.1093/bib/bbac491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/27/2022] [Accepted: 10/14/2022] [Indexed: 11/27/2022] Open
Abstract
Ultraliser is a neuroscience-specific software framework capable of creating accurate and biologically realistic 3D models of complex neuroscientific structures at intracellular (e.g. mitochondria and endoplasmic reticula), cellular (e.g. neurons and glia) and even multicellular scales of resolution (e.g. cerebral vasculature and minicolumns). Resulting models are exported as triangulated surface meshes and annotated volumes for multiple applications in in silico neuroscience, allowing scalable supercomputer simulations that can unravel intricate cellular structure-function relationships. Ultraliser implements a high-performance and unconditionally robust voxelization engine adapted to create optimized watertight surface meshes and annotated voxel grids from arbitrary non-watertight triangular soups, digitized morphological skeletons or binary volumetric masks. The framework represents a major leap forward in simulation-based neuroscience, making it possible to employ high-resolution 3D structural models for quantification of surface areas and volumes, which are of the utmost importance for cellular and system simulations. The power of Ultraliser is demonstrated with several use cases in which hundreds of models are created for potential application in diverse types of simulations. Ultraliser is publicly released under the GNU GPL3 license on GitHub (BlueBrain/Ultraliser). SIGNIFICANCE There is crystal clear evidence on the impact of cell shape on its signaling mechanisms. Structural models can therefore be insightful to realize the function; the more realistic the structure can be, the further we get insights into the function. Creating realistic structural models from existing ones is challenging, particularly when needed for detailed subcellular simulations. We present Ultraliser, a neuroscience-dedicated framework capable of building these structural models with realistic and detailed cellular geometries that can be used for simulations.
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Affiliation(s)
- Marwan Abdellah
- Corresponding authors. Marwan Abdellah, Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. E-mail: ; Felix Schürmann, Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. E-mail:
| | | | - Nadir Román Guerrero
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Alessandro Foni
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Jay S Coggan
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Corrado Calì
- Biological and Environmental Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia,Neuroscience Institute Cavalieri Ottolenghi (NICO) Orbassano, Italy,Department of Neuroscience, University of Torino Torino, Italy
| | - Marco Agus
- Visual Computing Center King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia,College of Science and Engineering Hamad Bin Khalifa University Doha, Qatar
| | - Eleftherios Zisis
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Daniel Keller
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Markus Hadwiger
- Visual Computing Center King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia
| | - Pierre J Magistretti
- Biological and Environmental Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal, Saudi Arabia
| | - Henry Markram
- Blue Brain Project (BBP) École Polytecnique Fédérale de Lausanne (EPFL) Geneva, Switzerland
| | - Felix Schürmann
- Corresponding authors. Marwan Abdellah, Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. E-mail: ; Felix Schürmann, Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland. E-mail:
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13
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A Primer on the Dynamical Systems Approach to Transport in Porous Media. Transp Porous Media 2022. [DOI: 10.1007/s11242-022-01811-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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14
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Bhargava A, Monteagudo B, Kushwaha P, Senarathna J, Ren Y, Riddle RC, Aggarwal M, Pathak AP. VascuViz: a multimodality and multiscale imaging and visualization pipeline for vascular systems biology. Nat Methods 2022; 19:242-254. [PMID: 35145319 PMCID: PMC8842955 DOI: 10.1038/s41592-021-01363-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 11/29/2021] [Indexed: 12/19/2022]
Abstract
Despite advances in imaging, image-based vascular systems biology has remained challenging because blood vessel data are often available only from a single modality or at a given spatial scale, and cross-modality data are difficult to integrate. Therefore, there is an exigent need for a multimodality pipeline that enables ex vivo vascular imaging with magnetic resonance imaging, computed tomography and optical microscopy of the same sample, while permitting imaging with complementary contrast mechanisms from the whole-organ to endothelial cell spatial scales. To achieve this, we developed 'VascuViz'-an easy-to-use method for simultaneous three-dimensional imaging and visualization of the vascular microenvironment using magnetic resonance imaging, computed tomography and optical microscopy in the same intact, unsectioned tissue. The VascuViz workflow permits multimodal imaging with a single labeling step using commercial reagents and is compatible with diverse tissue types and protocols. VascuViz's interdisciplinary utility in conjunction with new data visualization approaches opens up new vistas in image-based vascular systems biology.
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Affiliation(s)
- Akanksha Bhargava
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Benjamin Monteagudo
- Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Priyanka Kushwaha
- Departments of Orthopedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Janaka Senarathna
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yunke Ren
- Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ryan C Riddle
- Departments of Orthopedic Surgery, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Research and Development Service, Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Manisha Aggarwal
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Arvind P Pathak
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Electrical Engineering, The Johns Hopkins University, Baltimore, MD, USA.
- The Sidney Kimmel Comprehensive Cancer Center, The Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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15
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Qohar UNA, Zanna Munthe-Kaas A, Nordbotten JM, Hanson EA. A nonlinear multi-scale model for blood circulation in a realistic vascular system. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201949. [PMID: 34966547 PMCID: PMC8633777 DOI: 10.1098/rsos.201949] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2020] [Accepted: 10/28/2021] [Indexed: 06/14/2023]
Abstract
In the last decade, numerical models have become an increasingly important tool in biological and medical science. Numerical simulations contribute to a deeper understanding of physiology and are a powerful tool for better diagnostics and treatment. In this paper, a nonlinear multi-scale model framework is developed for blood flow distribution in the full vascular system of an organ. We couple a quasi one-dimensional vascular graph model to represent blood flow in larger vessels and a porous media model to describe flow in smaller vessels and capillary bed. The vascular model is based on Poiseuille's Law, with pressure correction by elasticity and pressure drop estimation at vessels' junctions. The porous capillary bed is modelled as a two-compartment domain (artery and venous) using Darcy's Law. The fluid exchange between the artery and venous capillary bed compartments is defined as blood perfusion. The numerical experiments show that the proposed model for blood circulation: (i) is closely dependent on the structure and parameters of both the larger vessels and of the capillary bed, and (ii) provides a realistic blood circulation in the organ. The advantage of the proposed model is that it is complex enough to reliably capture the main underlying physiological function, yet highly flexible as it offers the possibility of incorporating various local effects. Furthermore, the numerical implementation of the model is straightforward and allows for simulations on a regular desktop computer.
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Affiliation(s)
- Ulin Nuha A. Qohar
- Department of Mathematics, University of Bergen, Allegaten 41, Bergen 5008, Norway
| | | | | | - Erik Andreas Hanson
- Department of Mathematics, University of Bergen, Allegaten 41, Bergen 5008, Norway
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16
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Polimeni JR, Lewis LD. Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response. Prog Neurobiol 2021; 207:102174. [PMID: 34525404 PMCID: PMC8688322 DOI: 10.1016/j.pneurobio.2021.102174] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 07/30/2021] [Accepted: 09/08/2021] [Indexed: 12/20/2022]
Abstract
Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.
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Affiliation(s)
- Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Laura D Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Biomedical Engineering, Boston University, Boston, MA, USA.
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17
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Cury LFM, Maso Talou GD, Younes-Ibrahim M, Blanco PJ. Parallel generation of extensive vascular networks with application to an archetypal human kidney model. ROYAL SOCIETY OPEN SCIENCE 2021; 8:210973. [PMID: 34966553 PMCID: PMC8633801 DOI: 10.1098/rsos.210973] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Accepted: 10/28/2021] [Indexed: 05/25/2023]
Abstract
Given the relevance of the inextricable coupling between microcirculation and physiology, and the relation to organ function and disease progression, the construction of synthetic vascular networks for mathematical modelling and computer simulation is becoming an increasingly broad field of research. Building vascular networks that mimic in vivo morphometry is feasible through algorithms such as constrained constructive optimization (CCO) and variations. Nevertheless, these methods are limited by the maximum number of vessels to be generated due to the whole network update required at each vessel addition. In this work, we propose a CCO-based approach endowed with a domain decomposition strategy to concurrently create vascular networks. The performance of this approach is evaluated by analysing the agreement with the sequentially generated networks and studying the scalability when building vascular networks up to 200 000 vascular segments. Finally, we apply our method to vascularize a highly complex geometry corresponding to the cortex of a prototypical human kidney. The technique presented in this work enables the automatic generation of extensive vascular networks, removing the limitation from previous works. Thus, we can extend vascular networks (e.g. obtained from medical images) to pre-arteriolar level, yielding patient-specific whole-organ vascular models with an unprecedented level of detail.
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Affiliation(s)
- L. F. M. Cury
- National Laboratory for Scientific Computing, LNCC/MCTI, Petrópolis, Brazil
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
| | - G. D. Maso Talou
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - M. Younes-Ibrahim
- Faculty of Medical Sciences, Rio de Janeiro State University, UERJ, Rio de Janeiro, Brazil
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
| | - P. J. Blanco
- National Laboratory for Scientific Computing, LNCC/MCTI, Petrópolis, Brazil
- National Institute of Science and Technology in Medicine Assisted by Scientific Computing, INCT-MACC, Petrópolis, Brazil
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18
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Zisis E, Keller D, Kanari L, Arnaudon A, Gevaert M, Delemontex T, Coste B, Foni A, Abdellah M, Calì C, Hess K, Magistretti PJ, Schürmann F, Markram H. Digital Reconstruction of the Neuro-Glia-Vascular Architecture. Cereb Cortex 2021; 31:5686-5703. [PMID: 34387659 PMCID: PMC8568010 DOI: 10.1093/cercor/bhab254] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/05/2021] [Accepted: 07/06/2021] [Indexed: 01/21/2023] Open
Abstract
Astrocytes connect the vasculature to neurons mediating the supply of nutrients and biochemicals. They are involved in a growing number of physiological and pathophysiological processes that result from biophysical, physiological, and molecular interactions in this neuro-glia-vascular ensemble (NGV). The lack of a detailed cytoarchitecture severely restricts the understanding of how they support brain function. To address this problem, we used data from multiple sources to create a data-driven digital reconstruction of the NGV at micrometer anatomical resolution. We reconstructed 0.2 mm3 of the rat somatosensory cortex with 16 000 morphologically detailed neurons, 2500 protoplasmic astrocytes, and its microvasculature. The consistency of the reconstruction with a wide array of experimental measurements allows novel predictions of the NGV organization, allowing the anatomical reconstruction of overlapping astrocytic microdomains and the quantification of endfeet connecting each astrocyte to the vasculature, as well as the extent to which they cover the latter. Structural analysis showed that astrocytes optimize their positions to provide uniform vascular coverage for trophic support and signaling. However, this optimal organization rapidly declines as their density increases. The NGV digital reconstruction is a resource that will enable a better understanding of the anatomical principles and geometric constraints, which govern how astrocytes support brain function.
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Affiliation(s)
- Eleftherios Zisis
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Daniel Keller
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Lida Kanari
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Alexis Arnaudon
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Michael Gevaert
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Thomas Delemontex
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Benoît Coste
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Alessandro Foni
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Marwan Abdellah
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Corrado Calì
- Neuroscience Institute Cavalieri Ottolenghi, Orbassano, Turin 10043, Italy
- Department of Neuroscience, University of Torino, Torino 10126, Italy
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
| | - Kathryn Hess
- Laboratory for Topology and Neuroscience, Brain Mind Institute, École polytechnique fédérale de Lausanne (EPFL), Lausanne 1015, Switzerland
| | - Pierre Julius Magistretti
- Biological and Environmental Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955, Saudi Arabia
| | - Felix Schürmann
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
| | - Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne (EPFL), Campus Biotech, Geneva 1202, Switzerland
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19
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Graff BJ, Payne SJ, El-Bouri WK. The Ageing Brain: Investigating the Role of Age in Changes to the Human Cerebral Microvasculature With an in silico Model. Front Aging Neurosci 2021; 13:632521. [PMID: 34421568 PMCID: PMC8374868 DOI: 10.3389/fnagi.2021.632521] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 07/12/2021] [Indexed: 11/25/2022] Open
Abstract
Ageing causes extensive structural changes to the human cerebral microvasculature, which have a significant effect on capillary bed perfusion and oxygen transport. Current models of brain capillary networks in the literature focus on healthy adult brains and do not capture the effects of ageing, which is critical when studying neurodegenerative diseases. This study builds upon a statistically accurate model of the human cerebral microvasculature based on ex-vivo morphological data. This model is adapted for “healthy” ageing using in-vivo measurements from mice at three distinct age groups—young, middle-aged, and old. From this new model, blood and molecular exchange parameters are calculated such as permeability and surface-area-to-volume ratio, and compared across the three age groups. The ability to alter the model vessel-by-vessel is used to create a continuous gradient of ageing. It was found that surface-area-to-volume ratio reduced in old age by 6% and permeability by 24% from middle-age to old age, and variability within the networks also increased with age. The ageing gradient indicated a threshold in the ageing process around 75 years old, after which small changes have an amplified effect on blood flow properties. This gradient enables comparison of studies measuring cerebral properties at discrete points in time. The response of middle aged and old aged capillary beds to micro-emboli showed a lower robustness of the old age capillary bed to vessel occlusion. As the brain ages, there is thus increased vulnerability of the microvasculature—with a “tipping point” beyond which further remodeling of the microvasculature has exaggerated effects on the brain. When developing in-silico models of the brain, age is a very important consideration to accurately assess risk factors for cognitive decline and isolate early biomarkers of microvascular health.
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Affiliation(s)
- Barnaby J Graff
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Stephen J Payne
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom
| | - Wahbi K El-Bouri
- Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.,Liverpool Centre for Cardiovascular Science, University of Liverpool & Liverpool Heart and Chest Hospital, Liverpool, United Kingdom.,Department of Cardiovascular and Metabolic Medicine, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, United Kingdom
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20
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Ji X, Ferreira T, Friedman B, Liu R, Liechty H, Bas E, Chandrashekar J, Kleinfeld D. Brain microvasculature has a common topology with local differences in geometry that match metabolic load. Neuron 2021; 109:1168-1187.e13. [PMID: 33657412 PMCID: PMC8525211 DOI: 10.1016/j.neuron.2021.02.006] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 12/09/2020] [Accepted: 02/03/2021] [Indexed: 01/03/2023]
Abstract
The microvasculature underlies the supply networks that support neuronal activity within heterogeneous brain regions. What are common versus heterogeneous aspects of the connectivity, density, and orientation of capillary networks? To address this, we imaged, reconstructed, and analyzed the microvasculature connectome in whole adult mice brains with sub-micrometer resolution. Graph analysis revealed common network topology across the brain that leads to a shared structural robustness against the rarefaction of vessels. Geometrical analysis, based on anatomically accurate reconstructions, uncovered a scaling law that links length density, i.e., the length of vessel per volume, with tissue-to-vessel distances. We then derive a formula that connects regional differences in metabolism to differences in length density and, further, predicts a common value of maximum tissue oxygen tension across the brain. Last, the orientation of capillaries is weakly anisotropic with the exception of a few strongly anisotropic regions; this variation can impact the interpretation of fMRI data.
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Affiliation(s)
- Xiang Ji
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Tiago Ferreira
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | - Beth Friedman
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093, USA
| | - Rui Liu
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Hannah Liechty
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Erhan Bas
- Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, VA 20147, USA
| | | | - David Kleinfeld
- Department of Physics, University of California, San Diego, La Jolla, CA 92093, USA; Section of Neurobiology, University of California, San Diego, La Jolla, CA 92093, USA.
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21
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Adaptive constrained constructive optimisation for complex vascularisation processes. Sci Rep 2021; 11:6180. [PMID: 33731776 PMCID: PMC7969782 DOI: 10.1038/s41598-021-85434-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 02/26/2021] [Indexed: 11/09/2022] Open
Abstract
Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures. Moreover, this vascular outgrowth can be performed either from scratch or from an existing network of vessels. Hence, the vascular territory is defined as a partition of vascular, avascular and carriage domains (the last one contains vessels but not terminals) allowing one to model complex vascular domains. In turn, the multi-staged space-filling approach allows one to delineate a sequence of biologically-inspired stages during the vascularisation process by exploiting different constraints, optimisation strategies and domain partitions stage by stage, improving the consistency with the architectural hierarchy observed in anatomical structures. With these features, the aDaptive CCO (DCCO) algorithm proposed here aims at improving the modelled network anatomy. The capabilities of the DCCO algorithm are assessed with a number of anatomically realistic scenarios.
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22
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van Dijk JA, Fracasso A, Petridou N, Dumoulin SO. Validating Linear Systems Analysis for Laminar fMRI: Temporal Additivity for Stimulus Duration Manipulations. Brain Topogr 2021; 34:88-101. [PMID: 33210193 PMCID: PMC7803719 DOI: 10.1007/s10548-020-00808-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Accepted: 11/05/2020] [Indexed: 11/26/2022]
Abstract
Advancements in ultra-high field (7 T and higher) magnetic resonance imaging (MRI) scanners have made it possible to investigate both the structure and function of the human brain at a sub-millimeter scale. As neuronal feedforward and feedback information arrives in different layers, sub-millimeter functional MRI has the potential to uncover information processing between cortical micro-circuits across cortical depth, i.e. laminar fMRI. For nearly all conventional fMRI analyses, the main assumption is that the relationship between local neuronal activity and the blood oxygenation level dependent (BOLD) signal adheres to the principles of linear systems theory. For laminar fMRI, however, directional blood pooling across cortical depth stemming from the anatomy of the cortical vasculature, potentially violates these linear system assumptions, thereby complicating analysis and interpretation. Here we assess whether the temporal additivity requirement of linear systems theory holds for laminar fMRI. We measured responses elicited by viewing stimuli presented for different durations and evaluated how well the responses to shorter durations predicted those elicited by longer durations. We find that BOLD response predictions are consistently good predictors for observed responses, across all cortical depths, and in all measured visual field maps (V1, V2, and V3). Our results suggest that the temporal additivity assumption for linear systems theory holds for laminar fMRI. We thus show that the temporal additivity assumption holds across cortical depth for sub-millimeter gradient-echo BOLD fMRI in early visual cortex.
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Affiliation(s)
- Jelle A van Dijk
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands.
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands.
| | - Alessio Fracasso
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Natalia Petridou
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Serge O Dumoulin
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Experimental Psychology, Utrecht University, Utrecht, The Netherlands
- Experimental and Applied Psychology, VU University, Amsterdam, The Netherlands
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23
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Deepa Maheshvare M, Raha S, Pal D. A Graph-Based Framework for Multiscale Modeling of Physiological Transport. FRONTIERS IN NETWORK PHYSIOLOGY 2021; 1:802881. [PMID: 36925576 PMCID: PMC10013063 DOI: 10.3389/fnetp.2021.802881] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 11/30/2021] [Indexed: 11/13/2022]
Abstract
Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches in which it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here, we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective-dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element-based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from in vitro-in vivo studies and vascular topology from imaging studies for examining the structure-function relationship of complex vasculatures. The framework can advance simulation of whole-body networks at user-defined levels and is expected to find major use in personalized medicine and drug discovery.
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Affiliation(s)
- M Deepa Maheshvare
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
| | - Soumyendu Raha
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
| | - Debnath Pal
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, India
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24
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Singh M, Singh T, Soni S. Pre-operative Assessment of Ablation Margins for Variable Blood Perfusion Metrics in a Magnetic Resonance Imaging Based Complex Breast Tumour Anatomy: Simulation Paradigms in Thermal Therapies. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 198:105781. [PMID: 33065492 DOI: 10.1016/j.cmpb.2020.105781] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 09/28/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND AND OBJECTIVES Image-guided medical interventions facilitates precise visualization at treatment site. The conformal prediction for sparing healthy tissue fringes precisely in the vicinity of irregular tumour anatomy remains clinically challenging. Pre-clinical image-based computational modelling is imperative as it helps in enhancement of treatment quality, augmenting clinical-decision making, while planning, targeting, controlling, monitoring and assessing treatment response with an effective risk assessment before the onset of treatment in clinical settings. In this study, the influence of heat deposition rate (SAR), exposure duration, and variable blood perfusion metrics for a patient-specific breast tumour is quantified considering the tumour margins thereby suggesting need of geometrically accurate models. METHODS A three-dimensional realistic model mimicking dimensions of a female breast, comprising ~1.7 cm irregular tumour, was generated from patient specific two-dimensional DICOM format MRI images through image segmentation tools MIMICS 19.0® and 3-Matic 11.0® which is finally exported to COMSOL Multiphysics 5.2® as a volumetric mesh for finite element analysis. The Pennes bioheat transfer model and Arrhenius thermal damage model of cell-death are integrated to simulate a coupled biophysics problem. A comparative blood perfusion analysis is done to evaluate the response of tumour during heating considering thermal damage extent, including the tumour margins while sparing critical adjoining healthy tissues. RESULTS The evaluated thermal damage zones for 1 mm, 2 mm and 3 mm fringe heating region (beyond tumour boundary) reveals 0.09%, 0.21% and 0.34% thermal damage to the healthy tissue (which is <1%) and thus successful necrosis of the tumour. The iterative computational experiments suggests treatment margins < 5 mm are sufficient enough as heating beyond 3 mm fringe layer leads to higher damage surrounding the tumour approximately 1.5 times the tumour volume. Further, the heat-dosage requirements are 22% more for highly perfused tumour as compared to moderately perfused tumour with an approximate double time to ablate the whole tumour volume. CONCLUSIONS Depending on the blood perfusion characteristics of a tumour, it is a trade-off between heat-dosage (SAR) and exposure/treatment duration to get desired thermal damage including the irregular tumour boundaries while taking into account, the margin of healthy tissue. The suggested patient-specific integrated multiphysics-model based on MRI-Images may be implemented for pre-treatment planning based on the tumour blood perfusion to evaluate the thermal ablation zone dimensions clinically and thereby avoiding the damage of off-target tissues. Thus, risks involving underestimation or overestimation of thermal coagulation zones may be minimised while preserving the surrounding normal breast parenchyma.
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Affiliation(s)
- Manpreet Singh
- Department of Mechanical Engineering, University of Maryland Baltimore County, Baltimore, Maryland, USA; Biomedical Instrumentation Division, CSIR-Central Scientific Instruments Organisation, Chandigarh, India; Department of Mechanical Engineering, Thapar Institute of Engineering and Technology University, Patiala, Punjab, India.
| | - Tulika Singh
- Department of Radio-diagnosis and Imaging, Post Graduate Institute of Medical Education and Research, Chandigarh, India
| | - Sanjeev Soni
- Biomedical Instrumentation Division, CSIR-Central Scientific Instruments Organisation, Chandigarh, India
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25
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Tetteh G, Efremov V, Forkert ND, Schneider M, Kirschke J, Weber B, Zimmer C, Piraud M, Menze BH. DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes. Front Neurosci 2020; 14:592352. [PMID: 33363452 PMCID: PMC7753013 DOI: 10.3389/fnins.2020.592352] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 11/16/2020] [Indexed: 11/13/2022] Open
Abstract
We present DeepVesselNet, an architecture tailored to the challenges faced when extracting vessel trees and networks and corresponding features in 3-D angiographic volumes using deep learning. We discuss the problems of low execution speed and high memory requirements associated with full 3-D networks, high-class imbalance arising from the low percentage (<3%) of vessel voxels, and unavailability of accurately annotated 3-D training data-and offer solutions as the building blocks of DeepVesselNet. First, we formulate 2-D orthogonal cross-hair filters which make use of 3-D context information at a reduced computational burden. Second, we introduce a class balancing cross-entropy loss function with false-positive rate correction to handle the high-class imbalance and high false positive rate problems associated with existing loss functions. Finally, we generate a synthetic dataset using a computational angiogenesis model capable of simulating vascular tree growth under physiological constraints on local network structure and topology and use these data for transfer learning. We demonstrate the performance on a range of angiographic volumes at different spatial scales including clinical MRA data of the human brain, as well as CTA microscopy scans of the rat brain. Our results show that cross-hair filters achieve over 23% improvement in speed, lower memory footprint, lower network complexity which prevents overfitting and comparable accuracy that does not differ from full 3-D filters. Our class balancing metric is crucial for training the network, and transfer learning with synthetic data is an efficient, robust, and very generalizable approach leading to a network that excels in a variety of angiography segmentation tasks. We observe that sub-sampling and max pooling layers may lead to a drop in performance in tasks that involve voxel-sized structures. To this end, the DeepVesselNet architecture does not use any form of sub-sampling layer and works well for vessel segmentation, centerline prediction, and bifurcation detection. We make our synthetic training data publicly available, fostering future research, and serving as one of the first public datasets for brain vessel tree segmentation and analysis.
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Affiliation(s)
- Giles Tetteh
- Department of Computer Science, TU München, München, Germany
| | - Velizar Efremov
- Department of Computer Science, TU München, München, Germany
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Nils D. Forkert
- Department of Radiology, University of Calgary, Calgary, AB, Canada
| | - Matthias Schneider
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Jan Kirschke
- Neuroradiology, Klinikum Rechts der Isar, TU München, München, Germany
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Claus Zimmer
- Neuroradiology, Klinikum Rechts der Isar, TU München, München, Germany
| | - Marie Piraud
- Department of Computer Science, TU München, München, Germany
| | - Björn H. Menze
- Department of Computer Science, TU München, München, Germany
- Department for Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
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26
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Epp R, Schmid F, Weber B, Jenny P. Predicting Vessel Diameter Changes to Up-Regulate Biphasic Blood Flow During Activation in Realistic Microvascular Networks. Front Physiol 2020; 11:566303. [PMID: 33178036 PMCID: PMC7596696 DOI: 10.3389/fphys.2020.566303] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Accepted: 08/14/2020] [Indexed: 12/26/2022] Open
Abstract
A dense network of blood vessels distributes blood to different regions of the brain. To meet the temporarily and spatially varying energy demand resulting from changes in neuronal activity, the vasculature is able to locally up-regulate the blood supply. However, to which extent diameter changes of different vessel types contribute to the up-regulation, as well as the spatial and temporal characteristics of their changes, are currently unknown. Here, we present a new simulation method, which solves an inverse problem to calculate diameter changes of individual blood vessels needed to achieve predefined blood flow distributions in microvascular networks. This allows us to systematically compare the impact of different vessel types in various regulation scenarios. Moreover, the method offers the advantage that it handles the stochastic nature of blood flow originating from tracking the movement of individual red blood cells. Since the inverse problem is formulated for time-averaged pressures and flow rates, a deterministic approach for calculating the diameter changes is used, which allows us to apply the method for large realistic microvascular networks with high-dimensional parameter spaces. Our results obtained in both artificial and realistic microvascular networks reveal that diameter changes at the level of capillaries enable a very localized regulation of blood flow. In scenarios where only larger vessels, i.e., arterioles, are allowed to adapt, the flow increase cannot be confined to a specific activated region and flow changes spread into neighboring regions. Furthermore, relatively small dilations and constrictions of all vessel types can lead to substantial changes of capillary blood flow distributions. This suggests that small scale regulation is necessary to obtain a localized increase in blood flow.
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Affiliation(s)
- Robert Epp
- Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
| | - Franca Schmid
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland
| | - Patrick Jenny
- Institute of Fluid Dynamics, ETH Zurich, Zurich, Switzerland
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27
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Köppl T, Vidotto E, Wohlmuth B. A 3D-1D coupled blood flow and oxygen transport model to generate microvascular networks. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2020; 36:e3386. [PMID: 32659047 DOI: 10.1002/cnm.3386] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/18/2020] [Accepted: 07/05/2020] [Indexed: 06/11/2023]
Abstract
In this work, we introduce an algorithmic approach to generate microvascular networks starting from larger vessels that can be reconstructed without noticeable segmentation errors. Contrary to larger vessels, the reconstruction of fine-scale components of microvascular networks shows significant segmentation errors, and an accurate mapping is time and cost intense. Thus there is a need for fast and reliable reconstruction algorithms yielding surrogate networks having similar stochastic properties as the original ones. The microvascular networks are constructed in a marching way by adding vessels to the outlets of the vascular tree from the previous step. To optimise the structure of the vascular trees, we use Murray's law to determine the radii of the vessels and bifurcation angles. In each step, we compute the local gradient of the partial pressure of oxygen and adapt the orientation of the new vessels to this gradient. At the same time, we use the partial pressure of oxygen to check whether the considered tissue block is supplied sufficiently with oxygen. Computing the partial pressure of oxygen, we use a 3D-1D coupled model for blood flow and oxygen transport. To decrease the complexity of a fully coupled 3D model, we reduce the blood vessel network to a 1D graph structure and use a bi-directional coupling with the tissue which is described by a 3D homogeneous porous medium. The resulting surrogate networks are analysed with respect to morphological and physiological aspects.
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Affiliation(s)
- Tobias Köppl
- Chair for Numerics, University of Technology Munich, Garching, Germany
| | - Ettore Vidotto
- Chair for Numerics, University of Technology Munich, Garching, Germany
| | - Barbara Wohlmuth
- Chair for Numerics, University of Technology Munich, Garching, Germany
- Department of Mathematics, University of Bergen, Allegaten 41, 5020 Bergen, Norway, Germany
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28
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Donahue WP, Newhauser WD, Wong H, Moreno J, Dey J, Wilson VL. Computational feasibility of calculating the steady-state blood flow rate through the vasculature of the entire human body. Biomed Phys Eng Express 2020; 6:055026. [PMID: 33444257 DOI: 10.1088/2057-1976/abaf5d] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The human body contains approximately 20 billion individual blood vessels that deliver nutrients and oxygen to tissues. While blood flow is a well-developed field of research, no previous studies have calculated the blood flow rates through more than 5 million connected vessels. The goal of this study was to test if it is computationally feasible to calculate the blood flow rates through a vasculature equal in size to that of the human body. We designed and implemented a two-step algorithm to calculate the blood flow rates using principles of steady-state fluid dynamics. Steady-state fluid dynamics is an accurate approximation for the microvascular and venous structures in the human body. To determine the computational feasibility, we measured and evaluated the execution time, scalability, and memory usage to quantify the computational requirements. We demonstrated that it is computationally feasible to calculate the blood flow rate through 17 billion vessels in 6.5 hours using 256 compute nodes. The computational modeling of blood flow rate in entire organisms may find application in research on drug delivery, treatment of cancer metastases, and modulation of physiological performance.
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Affiliation(s)
- William P Donahue
- Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA, United States of America
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29
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Li P, Xu Y, Cao Y, Wu T. 3D Digital Anatomic Angioarchitecture of the Rat Spinal Cord: A Synchrotron Radiation Micro-CT Study. Front Neuroanat 2020; 14:41. [PMID: 32792915 PMCID: PMC7387706 DOI: 10.3389/fnana.2020.00041] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Accepted: 06/16/2020] [Indexed: 01/01/2023] Open
Abstract
Comprehensive analysis of 3D angioarchitecture within the intact rat spinal cord remains technically challenging due to its sophisticated anatomical properties. In this study, we aim to present a framework for ultrahigh-resolution digitalized mapping of the normal rat spinal cord angioarchitecture and to determine the physiological parameters using synchrotron radiation micro-CT (SRμCT). Male SD rats were used in this ex vivo study. After a proportional mixture of contrast agents perfusion, the intact spinal cord covered the cervical spinal from the upper of the 1st cervical vertebra to the 5th lumbar vertebra was harvested and cut into proper lengths within three distinct regions: Cervical 3–5 levels, Thoracic 10–12 levels, Lumbar 3–5 levels spinal cord and examined using SRμCT. This method enabled the replication of the complicated microvasculature network of the normal rat spinal cord at the ultrahigh-resolution level, allowing for the precise quantitative analysis of the vascular morphological difference among cervical, thoracic and lumbar spinal cord in a 3D manner. Apart from a series of delicate 3D digital anatomical maps of the rat spinal cord angioarchitecture ranging from the cervical and thoracic to the lumbar spinal cord were presented, the 3D reconstruction data of SRμCT made the 3D printing of the spinal cord targeted selected microvasculature reality, that possibly provided deep insight into the nature and role of spinal cord intricate angioarchitecture. Our data proposed a new approach to outline systematic visual and quantitative evaluations on the 3D arrangement of the entire hierarchical microvasculature of the normal rat spinal cord at ultrahigh resolution. The technique may have great potential and become useful for future research on the poorly understood nature and function of the neurovascular interaction, particularly to investigate their pathology changes in various models of neurovascular disease.
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Affiliation(s)
- Ping Li
- Department of Obstetrics, Xiangya Hospital, Central South University, Changsha, China.,Hunan Engineering Research Center of Early Life Development and Disease Prevention, Changsha, China
| | - Yan Xu
- Department of Sports Medicine, Xiangya Hospital, Central South University, Changsha, China.,Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China
| | - Yong Cao
- Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China.,Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Tianding Wu
- Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, Changsha, China.,Department of Spine Surgery and Orthopaedics, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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30
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Abdellah M, Guerrero NR, Lapere S, Coggan JS, Keller D, Coste B, Dagar S, Courcol JD, Markram H, Schürmann F. Interactive visualization and analysis of morphological skeletons of brain vasculature networks with VessMorphoVis. Bioinformatics 2020; 36:i534-i541. [PMID: 32657395 PMCID: PMC7355309 DOI: 10.1093/bioinformatics/btaa461] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
MOTIVATION Accurate morphological models of brain vasculature are key to modeling and simulating cerebral blood flow in realistic vascular networks. This in silico approach is fundamental to revealing the principles of neurovascular coupling. Validating those vascular morphologies entails performing certain visual analysis tasks that cannot be accomplished with generic visualization frameworks. This limitation has a substantial impact on the accuracy of the vascular models employed in the simulation. RESULTS We present VessMorphoVis, an integrated suite of toolboxes for interactive visualization and analysis of vast brain vascular networks represented by morphological graphs segmented originally from imaging or microscopy stacks. Our workflow leverages the outstanding potentials of Blender, aiming to establish an integrated, extensible and domain-specific framework capable of interactive visualization, analysis, repair, high-fidelity meshing and high-quality rendering of vascular morphologies. Based on the initial feedback of the users, we anticipate that our framework will be an essential component in vascular modeling and simulation in the future, filling a gap that is at present largely unfulfilled. AVAILABILITY AND IMPLEMENTATION VessMorphoVis is freely available under the GNU public license on Github at https://github.com/BlueBrain/VessMorphoVis. The morphology analysis, visualization, meshing and rendering modules are implemented as an add-on for Blender 2.8 based on its Python API (application programming interface). The add-on functionality is made available to users through an intuitive graphical user interface, as well as through exhaustive configuration files calling the API via a feature-rich command line interface running Blender in background mode. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Marwan Abdellah
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Nadir Román Guerrero
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Samuel Lapere
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Jay S Coggan
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Daniel Keller
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Benoit Coste
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Snigdha Dagar
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Jean-Denis Courcol
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Henry Markram
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
| | - Felix Schürmann
- Blue Brain Project (BBP), École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Geneva, Switzerland
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31
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van Dijk JA, Fracasso A, Petridou N, Dumoulin SO. Linear systems analysis for laminar fMRI: Evaluating BOLD amplitude scaling for luminance contrast manipulations. Sci Rep 2020; 10:5462. [PMID: 32214136 PMCID: PMC7096513 DOI: 10.1038/s41598-020-62165-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 03/09/2020] [Indexed: 01/18/2023] Open
Abstract
A fundamental assumption of nearly all functional magnetic resonance imaging (fMRI) analyses is that the relationship between local neuronal activity and the blood oxygenation level dependent (BOLD) signal can be described as following linear systems theory. With the advent of ultra-high field (7T and higher) MRI scanners, it has become possible to perform sub-millimeter resolution fMRI in humans. A novel and promising application of sub-millimeter fMRI is measuring responses across cortical depth, i.e. laminar imaging. However, the cortical vasculature and associated directional blood pooling towards the pial surface strongly influence the cortical depth-dependent BOLD signal, particularly for gradient-echo BOLD. This directional pooling may potentially affect BOLD linearity across cortical depth. Here we assess whether the amplitude scaling assumption for linear systems theory holds across cortical depth. For this, we use stimuli with different luminance contrasts to elicit different BOLD response amplitudes. We find that BOLD amplitude across cortical depth scales with luminance contrast, and that this scaling is identical across cortical depth. Although nonlinearities may be present for different stimulus configurations and acquisition protocols, our results suggest that the amplitude scaling assumption for linear systems theory across cortical depth holds for luminance contrast manipulations in sub-millimeter laminar BOLD fMRI.
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Affiliation(s)
- Jelle A van Dijk
- Experimental Psychology, Utrecht University, Utrecht, NL, Netherlands.
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands.
| | - Alessio Fracasso
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, G12 8QB, UK
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, NL, Netherlands
| | - Natalia Petridou
- Radiology Department, Imaging Division, Center for Image Sciences, University Medical Center Utrecht, Utrecht, NL, Netherlands
| | - Serge O Dumoulin
- Experimental Psychology, Utrecht University, Utrecht, NL, Netherlands
- Spinoza Centre for Neuroimaging, Amsterdam, NL, Netherlands
- Experimental and Applied Psychology, VU University, Amsterdam, NL, Netherlands
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32
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Kennel P, Dichamp J, Barreau C, Guissard C, Teyssedre L, Rouquette J, Colombelli J, Lorsignol A, Casteilla L, Plouraboué F. From whole-organ imaging to in-silico blood flow modeling: A new multi-scale network analysis for revisiting tissue functional anatomy. PLoS Comput Biol 2020; 16:e1007322. [PMID: 32059013 PMCID: PMC7062279 DOI: 10.1371/journal.pcbi.1007322] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2018] [Revised: 03/09/2020] [Accepted: 08/05/2019] [Indexed: 12/13/2022] Open
Abstract
We present a multi-disciplinary image-based blood flow perfusion modeling of a whole organ vascular network for analyzing both its structural and functional properties. We show how the use of Light-Sheet Fluorescence Microscopy (LSFM) permits whole-organ micro-vascular imaging, analysis and modelling. By using adapted image post-treatment workflow, we could segment, vectorize and reconstruct the entire micro-vascular network composed of 1.7 million vessels, from the tissue-scale, inside a ∼ 25 × 5 × 1 = 125mm3 volume of the mouse fat pad, hundreds of times larger than previous studies, down to the cellular scale at micron resolution, with the entire blood perfusion modeled. Adapted network analysis revealed the structural and functional organization of meso-scale tissue as strongly connected communities of vessels. These communities share a distinct heterogeneous core region and a more homogeneous peripheral region, consistently with known biological functions of fat tissue. Graph clustering analysis also revealed two distinct robust meso-scale typical sizes (from 10 to several hundred times the cellular size), revealing, for the first time, strongly connected functional vascular communities. These community networks support heterogeneous micro-environments. This work provides the proof of concept that in-silico all-tissue perfusion modeling can reveal new structural and functional exchanges between micro-regions in tissues, found from community clusters in the vascular graph.
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Affiliation(s)
- Pol Kennel
- Institute of Fluid Mechanics of Toulouse (IMFT), Toulouse University, CNRS, INPT, UPS, Toulouse, France
| | - Jules Dichamp
- Institute of Fluid Mechanics of Toulouse (IMFT), Toulouse University, CNRS, INPT, UPS, Toulouse, France
| | - Corinne Barreau
- CNRS 5273; UMR STROMALab, BP 84225, F-31 432 Toulouse Cedex 4, France
| | | | | | | | - Julien Colombelli
- Advanced Digital Microscopy Core Facility, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology. C. Baldiri Reixac, 10. E-08028 Barcelona, Spain
| | - Anne Lorsignol
- CNRS 5273; UMR STROMALab, BP 84225, F-31 432 Toulouse Cedex 4, France
| | - Louis Casteilla
- CNRS 5273; UMR STROMALab, BP 84225, F-31 432 Toulouse Cedex 4, France
| | - Franck Plouraboué
- Institute of Fluid Mechanics of Toulouse (IMFT), Toulouse University, CNRS, INPT, UPS, Toulouse, France
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33
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Ni S, Luo Z, Jiang L, Guo Z, Li P, Xu X, Cao Y, Duan C, Wu T, Li C, Lu H, Hu J. UTX/KDM6A Deletion Promotes Recovery of Spinal Cord Injury by Epigenetically Regulating Vascular Regeneration. Mol Ther 2019; 27:2134-2146. [PMID: 31495776 PMCID: PMC6904668 DOI: 10.1016/j.ymthe.2019.08.009] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Revised: 07/30/2019] [Accepted: 08/12/2019] [Indexed: 12/19/2022] Open
Abstract
The regeneration of the blood vessel system post spinal cord injury (SCI) is essential for the repair of neurological function. As a significant means to regulate gene expression, epigenetic regulation of angiogenesis in SCI is still largely unknown. Here, we found that Ubiquitously Transcribed tetratricopeptide repeat on chromosome X (UTX), the histone H3K27 demethylase, increased significantly in endothelial cells post SCI. Knockdown of UTX can promote the migration and tube formation of endothelial cells. The specific knockout of UTX in endothelial cells enhanced angiogenesis post SCI accompanied with improved neurological function. In addition, we found regulation of UTX expression can change the level of microRNA 24 (miR-24) in vitro. The physical binding of UTX to the promotor of miR-24 was indicated by chromatin immunoprecipitation (ChIP) assay. Meanwhile, methylation sequencing of endothelial cells demonstrated that UTX could significantly decrease the level of methylation in the miR-24 promotor. Furthermore, miR-24 significantly abolished the promoting effect of UTX deletion on angiogenesis in vitro and in vivo. Finally, we predicted the potential target mRNAs of miR-24 related to angiogenesis. We indicate that UTX deletion can epigenetically promote the vascular regeneration and functional recovery post SCI by forming a regulatory network with miR-24.
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Affiliation(s)
- Shuangfei Ni
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Zixiang Luo
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Liyuan Jiang
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Zhu Guo
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China; Spine Surgery Department of the Affiliated Hospital of Qingdao University, 266000 Qingdao, China
| | - Ping Li
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Xiang Xu
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China; Department of Minimally Invasive Spinal Surgery, The Second Affiliated Hospital of Inner Mongolia Medical College, Huhhot 010030, Inner Mongolia, China
| | - Yong Cao
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Chunyue Duan
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Tianding Wu
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Chengjun Li
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China
| | - Hongbin Lu
- Department of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China.
| | - Jianzhong Hu
- Department of Spine Surgery, Xiangya Hospital, Central South University, 410008 Changsha, China; Key Laboratory of Organ Injury, Aging and Regenerative Medicine of Hunan Province, 410008 Changsha, China; Research Centre of Sports Medicine, Xiangya Hospital, Central South University, 410008 Changsha, China.
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Diaz-Alvarez A, Higuchi R, Sanz-Leon P, Marcus I, Shingaya Y, Stieg AZ, Gimzewski JK, Kuncic Z, Nakayama T. Emergent dynamics of neuromorphic nanowire networks. Sci Rep 2019; 9:14920. [PMID: 31624325 PMCID: PMC6797708 DOI: 10.1038/s41598-019-51330-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 09/25/2019] [Indexed: 12/31/2022] Open
Abstract
Neuromorphic networks are formed by random self-assembly of silver nanowires. Silver nanowires are coated with a polymer layer after synthesis in which junctions between two nanowires act as resistive switches, often compared with neurosynapses. We analyze the role of single junction switching in the dynamical properties of the neuromorphic network. Network transitions to a high-conductance state under the application of a voltage bias higher than a threshold value. The stability and permanence of this state is studied by shifting the voltage bias in order to activate or deactivate the network. A model of the electrical network with atomic switches reproduces the relation between individual nanowire junctions switching events with current pathway formation or destruction. This relation is further manifested in changes in 1/f power-law scaling of the spectral distribution of current. The current fluctuations involved in this scaling shift are considered to arise from an essential equilibrium between formation, stochastic-mediated breakdown of individual nanowire-nanowire junctions and the onset of different current pathways that optimize power dissipation. This emergent dynamics shown by polymer-coated Ag nanowire networks places this system in the class of optimal transport networks, from which new fundamental parallels with neural dynamics and natural computing problem-solving can be drawn.
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Affiliation(s)
- Adrian Diaz-Alvarez
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.
| | - Rintaro Higuchi
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan
| | - Paula Sanz-Leon
- Sydney Nano Institute and School of Physics, University of Sydney, Sydney, NSW, 2006, Australia
| | - Ido Marcus
- Sydney Nano Institute and School of Physics, University of Sydney, Sydney, NSW, 2006, Australia
| | - Yoshitaka Shingaya
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan
| | - Adam Z Stieg
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.,California NanoSystems Institute (CNSI), University of California Los Angeles, 570 Westwood Plaza, Los Angeles, California, 90095, USA
| | - James K Gimzewski
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.,California NanoSystems Institute (CNSI), University of California Los Angeles, 570 Westwood Plaza, Los Angeles, California, 90095, USA.,Department of Chemistry and Biochemistry, University of California Los Angeles, 607 Charles E. Young Drive East, Los Angeles, California, 90095, USA
| | - Zdenka Kuncic
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan.,Sydney Nano Institute and School of Physics, University of Sydney, Sydney, NSW, 2006, Australia
| | - Tomonobu Nakayama
- International Center for Material Nanoarchitectonics (WPI-MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki, 305-0044, Japan. .,Sydney Nano Institute and School of Physics, University of Sydney, Sydney, NSW, 2006, Australia. .,Graduate School of Pure and Applied Sciences, University of Tsukuba, 1-1 Namiki, Tsukuba, Ibaraki, 305-0055, Japan.
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35
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Schmid F, Barrett MJP, Obrist D, Weber B, Jenny P. Red blood cells stabilize flow in brain microvascular networks. PLoS Comput Biol 2019; 15:e1007231. [PMID: 31469820 PMCID: PMC6750893 DOI: 10.1371/journal.pcbi.1007231] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2019] [Revised: 09/18/2019] [Accepted: 07/01/2019] [Indexed: 12/28/2022] Open
Abstract
Capillaries are the prime location for oxygen and nutrient exchange in all tissues. Despite their fundamental role, our knowledge of perfusion and flow regulation in cortical capillary beds is still limited. Here, we use in vivo measurements and blood flow simulations in anatomically accurate microvascular network to investigate the impact of red blood cells (RBCs) on microvascular flow. Based on these in vivo and in silico experiments, we show that the impact of RBCs leads to a bias toward equating the values of the outflow velocities at divergent capillary bifurcations, for which we coin the term “well-balanced bifurcations”. Our simulation results further reveal that hematocrit heterogeneity is directly caused by the RBC dynamics, i.e. by their unequal partitioning at bifurcations and their effect on vessel resistance. These results provide the first in vivo evidence of the impact of RBC dynamics on the flow field in the cortical microvasculature. By structural and functional analyses of our blood flow simulations we show that capillary diameter changes locally alter flow and RBC distribution. A dilation of 10% along a vessel length of 100 μm increases the flow on average by 21% in the dilated vessel downstream a well-balanced bifurcation. The number of RBCs rises on average by 27%. Importantly, RBC up-regulation proves to be more effective the more balanced the outflow velocities at the upstream bifurcation are. Taken together, we conclude that diameter changes at capillary level bear potential to locally change the flow field and the RBC distribution. Moreover, our results suggest that the balancing of outflow velocities contributes to the robustness of perfusion. Based on our in silico results, we anticipate that the bi-phasic nature of blood and small-scale regulations are essential for a well-adjusted oxygen and energy substrate supply. Glucose and oxygen are key energy sources of the brain. As energy storage capabilities are limited in the brain, a continuous supply of oxygen and glucose via the bloodstream is crucial for the brain’s functioning. The bulk of discharge occurs at the level of capillaries, which are the smallest and most frequent vessels of the cortical vasculature. Nonetheless, our understanding of perfusion and topology of the capillary bed is still limited. Here, we use in vivo two-photon based blood flow measurements and numerical simulations in large realistic microvascular networks to study the flow in the cortical microvasculature. Our results reveal that the impact of red blood cells enhances the robustness of microvascular perfusion and increases the heterogeneity in red blood cell distribution. It is well established that higher neuronal activity leads to an increase in blood flow. However, the precise regulation mechanisms and their spatial extent remain largely unknown. We show that small-scale regulations locally alter flow and red blood cell distribution. We suggest that these mechanisms are key for an efficient and flexible circulatory system. Moreover, our results reveal a novel role of the bi-phasic nature of blood.
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Affiliation(s)
- Franca Schmid
- Institute of Fluid Dynamics, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland
- Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland
- * E-mail:
| | - Matthew J. P. Barrett
- Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Winterthurerstrasse 190, Zurich, Switzerland
| | - Dominik Obrist
- ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, Bern, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Winterthurerstrasse 190, Zurich, Switzerland
| | - Patrick Jenny
- Institute of Fluid Dynamics, ETH Zurich, Sonneggstrasse 3, Zurich, Switzerland
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36
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Glioblastoma multiforme restructures the topological connectivity of cerebrovascular networks. Sci Rep 2019; 9:11757. [PMID: 31409816 PMCID: PMC6692362 DOI: 10.1038/s41598-019-47567-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 07/19/2019] [Indexed: 12/16/2022] Open
Abstract
Glioblastoma multiforme alters healthy tissue vasculature by inducing angiogenesis and vascular remodeling. To fully comprehend the structural and functional properties of the resulting vascular network, it needs to be studied collectively by considering both geometric and topological properties. Utilizing Single Plane Illumination Microscopy (SPIM), the detailed capillary structure in entire healthy and tumor-bearing mouse brains could be resolved in three dimensions. At the scale of the smallest capillaries, the entire vascular systems of bulk U87- and GL261-glioblastoma xenografts, their respective cores, and healthy brain hemispheres were modeled as complex networks and quantified with fundamental topological measures. All individual vessel segments were further quantified geometrically and modular clusters were uncovered and characterized as meta-networks, facilitating an analysis of large-scale connectivity. An inclusive comparison of large tissue sections revealed that geometric properties of individual vessels were altered in glioblastoma in a relatively subtle way, with high intra- and inter-tumor heterogeneity, compared to the impact on the vessel connectivity. A network topology analysis revealed a clear decomposition of large modular structures and hierarchical network organization, while preserving most fundamental topological classifications, in both tumor models with distinct growth patterns. These results augment our understanding of cerebrovascular networks and offer a topological assessment of glioma-induced vascular remodeling. The findings may help understand the emergence of hypoxia and necrosis, and prove valuable for therapeutic interventions such as radiation or antiangiogenic therapy.
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37
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Hodneland E, Hanson E, Sævareid O, Nævdal G, Lundervold A, Šoltészová V, Munthe-Kaas AZ, Deistung A, Reichenbach JR, Nordbotten JM. A new framework for assessing subject-specific whole brain circulation and perfusion using MRI-based measurements and a multi-scale continuous flow model. PLoS Comput Biol 2019; 15:e1007073. [PMID: 31237876 PMCID: PMC6613711 DOI: 10.1371/journal.pcbi.1007073] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 07/08/2019] [Accepted: 05/07/2019] [Indexed: 11/18/2022] Open
Abstract
A large variety of severe medical conditions involve alterations in microvascular circulation. Hence, measurements or simulation of circulation and perfusion has considerable clinical value and can be used for diagnostics, evaluation of treatment efficacy, and for surgical planning. However, the accuracy of traditional tracer kinetic one-compartment models is limited due to scale dependency. As a remedy, we propose a scale invariant mathematical framework for simulating whole brain perfusion. The suggested framework is based on a segmentation of anatomical geometry down to imaging voxel resolution. Large vessels in the arterial and venous network are identified from time-of-flight (ToF) and quantitative susceptibility mapping (QSM). Macro-scale flow in the large-vessel-network is accurately modelled using the Hagen-Poiseuille equation, whereas capillary flow is treated as two-compartment porous media flow. Macro-scale flow is coupled with micro-scale flow by a spatially distributing support function in the terminal endings. Perfusion is defined as the transition of fluid from the arterial to the venous compartment. We demonstrate a whole brain simulation of tracer propagation on a realistic geometric model of the human brain, where the model comprises distinct areas of grey and white matter, as well as large vessels in the arterial and venous vascular network. Our proposed framework is an accurate and viable alternative to traditional compartment models, with high relevance for simulation of brain perfusion and also for restoration of field parameters in clinical brain perfusion applications.
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Affiliation(s)
- Erlend Hodneland
- Norwegian Research Centre, Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland Universitetssykehus, Bergen, Norway
| | - Erik Hanson
- Department of Mathematics, University of Bergen, Bergen, Norway
| | | | | | - Arvid Lundervold
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland Universitetssykehus, Bergen, Norway
- Department of Biomedicine, University of Bergen, Bergen, Norway
| | | | - Antonella Z. Munthe-Kaas
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland Universitetssykehus, Bergen, Norway
- Department of Mathematics, University of Bergen, Bergen, Norway
| | - Andreas Deistung
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Germany
- Department of Neurology, Essen University Hospital, Essen, Germany
| | - Jürgen R. Reichenbach
- Medical Physics Group, Institute of Diagnostic and Interventional Radiology, Jena University Hospital - Friedrich Schiller University Jena, Germany
- Michael Stifel Center Jena for Data-driven and Simulation Science, Friedrich Schiller University, Jena, Germany
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38
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Gkontra P, El‐Bouri WK, Norton K, Santos A, Popel AS, Payne SJ, Arroyo AG. Dynamic Changes in Microvascular Flow Conductivity and Perfusion After Myocardial Infarction Shown by Image-Based Modeling. J Am Heart Assoc 2019; 8:e011058. [PMID: 30897998 PMCID: PMC6509718 DOI: 10.1161/jaha.118.011058] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Accepted: 02/19/2019] [Indexed: 12/26/2022]
Abstract
Background Microcirculation is a decisive factor in tissue reperfusion inadequacy following myocardial infarction ( MI ). Nonetheless, experimental assessment of blood flow in microcirculation remains a bottleneck. We sought to model blood flow properties in coronary microcirculation at different time points after MI and to compare them with healthy conditions to obtain insights into alterations in cardiac tissue perfusion. Methods and Results We developed an image-based modeling framework that permitted feeding a continuum flow model with anatomical data previously obtained from the pig coronary microvasculature to calculate physiologically meaningful permeability tensors. The tensors encompassed the microvascular conductivity and were also used to estimate the arteriole-venule drop in pressure and myocardial blood flow. Our results indicate that the tensors increased in a bimodal pattern at infarcted areas on days 1 and 7 after MI while a nonphysiological decrease in arteriole-venule drop in pressure was observed; contrary, the tensors and the arteriole-venule drop in pressure on day 3 after MI , and in remote areas, were closer to values for healthy tissue. Myocardial blood flow calculated using the condition-dependent arteriole-venule drop in pressure decreased in infarcted areas. Last, we simulated specific modes of vascular remodeling, such as vasodilation, vasoconstriction, or pruning, and quantified their distinct impact on microvascular conductivity. Conclusions Our study unravels time- and region-dependent alterations of tissue perfusion related to the structural changes occurring in the coronary microvasculature due to MI . It also paves the way for conducting simulations in new therapeutic interventions in MI and for image-based microvascular modeling by applying continuum flow models in other biomedical scenarios.
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Affiliation(s)
- Polyxeni Gkontra
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)MadridSpain
- Biomedical Image Technologies (BIT), ETSI Telecomunicación,Universidad Politécnica de MadridMadridSpain
| | - Wahbi K. El‐Bouri
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordUnited Kingdom
| | - Kerri‐Ann Norton
- Division of Science, Mathematics, and ComputingBard CollegeAnnandale‐on‐HudsonNY
| | - Andrés Santos
- Biomedical Image Technologies (BIT), ETSI Telecomunicación,Universidad Politécnica de MadridMadridSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBERBBN)MadridSpain
| | - Aleksander S. Popel
- Department of Biomedical EngineeringSchool of MedicineJohns Hopkins UniversityBaltimoreMD
| | - Stephen J. Payne
- Institute of Biomedical EngineeringDepartment of Engineering ScienceUniversity of OxfordUnited Kingdom
| | - Alicia G. Arroyo
- Centro Nacional de Investigaciones Cardiovasculares (CNIC)MadridSpain
- Centro de Investigaciones Biológicas (CIB‐CSIC)MadridSpain
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39
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Smith AF, Doyeux V, Berg M, Peyrounette M, Haft-Javaherian M, Larue AE, Slater JH, Lauwers F, Blinder P, Tsai P, Kleinfeld D, Schaffer CB, Nishimura N, Davit Y, Lorthois S. Brain Capillary Networks Across Species: A few Simple Organizational Requirements Are Sufficient to Reproduce Both Structure and Function. Front Physiol 2019; 10:233. [PMID: 30971935 PMCID: PMC6444172 DOI: 10.3389/fphys.2019.00233] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 02/22/2019] [Indexed: 02/02/2023] Open
Abstract
Despite the key role of the capillaries in neurovascular function, a thorough characterization of cerebral capillary network properties is currently lacking. Here, we define a range of metrics (geometrical, topological, flow, mass transfer, and robustness) for quantification of structural differences between brain areas, organs, species, or patient populations and, in parallel, digitally generate synthetic networks that replicate the key organizational features of anatomical networks (isotropy, connectedness, space-filling nature, convexity of tissue domains, characteristic size). To reach these objectives, we first construct a database of the defined metrics for healthy capillary networks obtained from imaging of mouse and human brains. Results show that anatomical networks are topologically equivalent between the two species and that geometrical metrics only differ in scaling. Based on these results, we then devise a method which employs constrained Voronoi diagrams to generate 3D model synthetic cerebral capillary networks that are locally randomized but homogeneous at the network-scale. With appropriate choice of scaling, these networks have equivalent properties to the anatomical data, demonstrated by comparison of the defined metrics. The ability to synthetically replicate cerebral capillary networks opens a broad range of applications, ranging from systematic computational studies of structure-function relationships in healthy capillary networks to detailed analysis of pathological structural degeneration, or even to the development of templates for fabrication of 3D biomimetic vascular networks embedded in tissue-engineered constructs.
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Affiliation(s)
- Amy F Smith
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - Vincent Doyeux
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - Maxime Berg
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - Myriam Peyrounette
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - Mohammad Haft-Javaherian
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Anne-Edith Larue
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - John H Slater
- Department of Biomedical Engineering, University of Delaware, Newark, DE, United States
| | - Frédéric Lauwers
- Toulouse NeuroImaging Center (TONIC), Université de Toulouse, INSERM, Toulouse, France.,Department of Anatomy, LSR44, Faculty of Medicine Toulouse-Purpan, Toulouse, France
| | - Pablo Blinder
- Department of Neurobiology, George S. Wise Faculty of Life Sciences, Tel-Aviv University, Tel Aviv, Israel
| | - Philbert Tsai
- Department of Physics, University of California, San Diego, La Jolla, CA, United States
| | - David Kleinfeld
- Department of Physics, University of California, San Diego, La Jolla, CA, United States
| | - Chris B Schaffer
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Nozomi Nishimura
- Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Yohan Davit
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
| | - Sylvie Lorthois
- Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France.,Nancy E. and Peter C. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, United States
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40
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Possenti L, di Gregorio S, Gerosa FM, Raimondi G, Casagrande G, Costantino ML, Zunino P. A computational model for microcirculation including Fahraeus-Lindqvist effect, plasma skimming and fluid exchange with the tissue interstitium. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3165. [PMID: 30358172 DOI: 10.1002/cnm.3165] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2018] [Revised: 09/06/2018] [Accepted: 10/19/2018] [Indexed: 06/08/2023]
Abstract
We present a two-phase model for microcirculation that describes the interaction of plasma with red blood cells. The model takes into account of typical effects characterizing the microcirculation, such as the Fahraeus-Lindqvist effect and plasma skimming. Besides these features, the model describes the interaction of capillaries with the surrounding tissue. More precisely, the model accounts for the interaction of capillary transmural flow with the surrounding interstitial pressure. Furthermore, the capillaries are represented as one-dimensional channels with arbitrary, possibly curved configuration. The latter two features rely on the unique ability of the model to account for variations of flow rate and pressure along the axis of the capillary, according to a local differential formulation of mass and momentum conservation. Indeed, the model stands on a solid mathematical foundation, which is also addressed in this work. In particular, we present the model derivation, the variational formulation, and its approximation using the finite element method. Finally, we conclude the work with a comparative computational study of the importance of the Fahraeus-Lindqvist, plasma skimming, and capillary leakage effects on the distribution of flow in a microvascular network.
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Affiliation(s)
- Luca Possenti
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Simone di Gregorio
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
- MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
| | | | - Giorgio Raimondi
- MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
| | - Giustina Casagrande
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Maria Laura Costantino
- LaBS, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Paolo Zunino
- MOX, Department of Mathematics, Politecnico di Milano, Milan, Italy
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Guo J, Keller KA, Govyadinov P, Ruchhoeft P, Slater JH, Mayerich D. Accurate flow in augmented networks (AFAN): an approach to generating three-dimensional biomimetic microfluidic networks with controlled flow. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2019; 11:8-16. [PMID: 31490456 PMCID: PMC6336169 DOI: 10.1039/c8ay01798k] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 08/30/2018] [Indexed: 05/18/2023]
Abstract
In vivo, microvasculature provides oxygen, nutrients, and soluble factors necessary for cell survival and function. The highly tortuous, densely-packed, and interconnected three-dimensional (3D) architecture of microvasculature ensures that cells receive these crucial components. The ability to duplicate microvascular architecture in tissue-engineered models could provide a means to generate large-volume constructs as well as advanced microphysiological systems. Similarly, the ability to induce realistic flow in engineered microvasculature is crucial to recapitulating in vivo-like flow and transport. Advanced biofabrication techniques are capable of generating 3D, biomimetic microfluidic networks in hydrogels, however, these models can exhibit systemic aberrations in flow due to incorrect boundary conditions. To overcome this problem, we developed an automated method for generating synthetic augmented channels that induce the desired flow properties within three-dimensional microfluidic networks. These augmented inlets and outlets enforce the appropriate boundary conditions for achieving specified flow properties and create a three-dimensional output useful for image-guided fabrication techniques to create biomimetic microvascular networks.
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Affiliation(s)
- Jiaming Guo
- Department of Electrical and Computer Engineering , University of Houston , USA .
| | - Keely A Keller
- Department of Biomedical Engineering , University of Delaware , USA
| | - Pavel Govyadinov
- Department of Electrical and Computer Engineering , University of Houston , USA .
| | - Paul Ruchhoeft
- Department of Electrical and Computer Engineering , University of Houston , USA .
| | - John H Slater
- Department of Biomedical Engineering , University of Delaware , USA
| | - David Mayerich
- Department of Electrical and Computer Engineering , University of Houston , USA .
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42
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Helthuis JHG, van Doormaal TPC, Hillen B, Bleys RLAW, Harteveld AA, Hendrikse J, van der Toorn A, Brozici M, Zwanenburg JJM, van der Zwan A. Branching Pattern of the Cerebral Arterial Tree. Anat Rec (Hoboken) 2018; 302:1434-1446. [PMID: 30332725 PMCID: PMC6767475 DOI: 10.1002/ar.23994] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 08/19/2018] [Accepted: 09/06/2018] [Indexed: 12/19/2022]
Abstract
Quantitative data on branching patterns of the human cerebral arterial tree are lacking in the 1.0–0.1 mm radius range. We aimed to collect quantitative data in this range, and to study if the cerebral artery tree complies with the principle of minimal work (Law of Murray). To enable easy quantification of branching patterns a semi‐automatic method was employed to measure 1,294 bifurcations and 2,031 segments on 7 T‐MRI scans of two corrosion casts embedded in a gel. Additionally, to measure segments with a radius smaller than 0.1 mm, 9.4 T‐MRI was used on a small cast section to characterize 1,147 bifurcations and 1,150 segments. Besides MRI, traditional methods were employed. Seven hundred thirty‐three bifurcations were manually measured on a corrosion cast and 1,808 bifurcations and 1,799 segment lengths were manually measured on a fresh dissected cerebral arterial tree. Data showed a large variation in branching pattern parameters (asymmetry‐ratio, area‐ratio, length‐radius‐ratio, tapering). Part of the variation may be explained by the variation in measurement techniques, number of measurements and location of measurement in the vascular tree. This study confirms that the cerebral arterial tree complies with the principle of minimum work. These data are essential in the future development of more accurate mathematical blood flow models. Anat Rec, 302:1434–1446, 2019. © 2018 The Authors. The Anatomical Record published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists.
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Affiliation(s)
- Jasper H G Helthuis
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.,Brain Technology Institute, Utrecht, The Netherlands
| | - Tristan P C van Doormaal
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.,Brain Technology Institute, Utrecht, The Netherlands
| | - Berend Hillen
- Departent of Anatomy, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Ronald L A W Bleys
- Department of Anatomy, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Annette van der Toorn
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Mariana Brozici
- Department of Anatomy, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Pulmonology, Heilig Hart Ziekenhuis, Mol, Belgium
| | - Jaco J M Zwanenburg
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Albert van der Zwan
- Department of Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.,Brain Technology Institute, Utrecht, The Netherlands
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43
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Lücker A, Secomb TW, Barrett MJP, Weber B, Jenny P. The Relation Between Capillary Transit Times and Hemoglobin Saturation Heterogeneity. Part 2: Capillary Networks. Front Physiol 2018; 9:1296. [PMID: 30298017 PMCID: PMC6160581 DOI: 10.3389/fphys.2018.01296] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2017] [Accepted: 08/29/2018] [Indexed: 12/22/2022] Open
Abstract
Brain metabolism is highly dependent on continuous oxygen supply. Cortical microvascular networks exhibit heterogeneous blood flow, leading to non-uniform tissue oxygenation and capillary hemoglobin saturation. We recently proposed capillary outflow saturation heterogeneity (COSH) to represent effects of heterogeneity on oxygen supply to tissue regions most vulnerable to hypoxia, and showed that diffusive oxygen exchange among red blood cells within capillaries and among capillaries (diffusive interaction) significantly reduces COSH in simplified geometrical configurations. Here, numerical simulations of oxygen transport in capillary network geometries derived from mouse somatosensory cortex are presented. Diffusive interaction was found to reduce COSH by 41 to 62% compared to simulations where diffusive interaction was excluded. Hemoglobin saturation drop across the microvascular network is strongly correlated with red blood cell transit time, but the coefficient of variation of saturation drop is approximately one third lower. Unexpectedly, the radius of the tissue cylinder supplied by a capillary correlates weakly with the anatomical tissue cylinder radius, but strongly with hemoglobin saturation. Thus, diffusive interaction contributes greatly to the microcirculation's ability to achieve tissue oxygenation, despite heterogeneous capillary transit time and hematocrit distribution. These findings provide insight into the effects of cerebral small vessel disease on tissue oxygenation and brain function.
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Affiliation(s)
- Adrien Lücker
- Department of Mechanical and Process Engineering, Institute of Fluid Dynamics, ETH Zürich, Zurich, Switzerland
| | - Timothy W Secomb
- Department of Physiology, University of Arizona, Tucson, AZ, United States
| | - Matthew J P Barrett
- Institute of Pharmacology and Toxicology, University of Zürich, Zurich, Switzerland
| | - Bruno Weber
- Institute of Pharmacology and Toxicology, University of Zürich, Zurich, Switzerland
| | - Patrick Jenny
- Department of Mechanical and Process Engineering, Institute of Fluid Dynamics, ETH Zürich, Zurich, Switzerland
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44
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Payne S, El-Bouri W. Modelling dynamic changes in blood flow and volume in the cerebral vasculature. Neuroimage 2018; 176:124-137. [DOI: 10.1016/j.neuroimage.2018.04.037] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Revised: 03/02/2018] [Accepted: 04/17/2018] [Indexed: 12/19/2022] Open
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45
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Kennel P, Teyssedre L, Colombelli J, Plouraboué F. Toward quantitative three-dimensional microvascular networks segmentation with multiview light-sheet fluorescence microscopy. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-14. [PMID: 30120828 DOI: 10.1117/1.jbo.23.8.086002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 07/18/2018] [Indexed: 05/08/2023]
Abstract
Three-dimensional (3-D) large-scale imaging of microvascular networks is of interest in various areas of biology and medicine related to structural, functional, developmental, and pathological issues. Light-sheet fluorescence microscopy (LSFM) techniques are rapidly spreading and are now on the way to offer operational solutions for large-scale tissue imaging. This contribution describes how reliable vessel segmentation can be handled from LSFM data in very large tissue volumes using a suitable image analysis workflow. Since capillaries are tubular objects of a few microns scale radius, they represent challenging structures to reliably reconstruct without distortion and artifacts. We provide a systematic analysis of multiview deconvolution image processing workflow to control and evaluate the accuracy of the reconstructed vascular network using various low to high level, metrics. We show that even if low-level structural metrics are sensitive to isotropic imaging enhancement provided by a larger number of views, functional high-level metrics, including perfusion permeability, are less sensitive. Hence, combining deconvolution and registration onto a few number of views appears sufficient for a reliable quantitative 3-D vessel segmentation for their possible use for perfusion modeling.
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Affiliation(s)
- Pol Kennel
- Toulouse University, CNRS, INPT, UPS, Institute of Fluid Mechanics of Toulouse, Toulouse, France
| | - Lise Teyssedre
- ITAV, USR 3505, National Center of Scientific Research, Toulouse, France
| | - Julien Colombelli
- Institute of Science et Technology, Advanced Digital Microscopy Core Facility, Barcelona, Spain
| | - Franck Plouraboué
- Toulouse University, CNRS, INPT, UPS, Institute of Fluid Mechanics of Toulouse, Toulouse, France
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46
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Langhoff W, Riggs A, Hinow P. Scaling behavior of drug transport and absorption in in silico cerebral capillary networks. PLoS One 2018; 13:e0200266. [PMID: 29990324 PMCID: PMC6039031 DOI: 10.1371/journal.pone.0200266] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 06/23/2018] [Indexed: 12/27/2022] Open
Abstract
Drug delivery to the brain is challenging due to the presence of the blood-brain barrier. Mathematical modeling and simulation are essential tools for the deeper understanding of transport processes in the blood, across the blood-brain barrier and within the tissue. Here we present a mathematical model for drug delivery through capillary networks with increasingly complex topologies with the goal to understand the scaling behavior of model predictions on a coarse-to-fine sequence of grids. We apply our model to the delivery of L-Dopa, the primary drug used in the therapy of Parkinson’s Disease. Our model replicates observed blood flow rates and ratios between plasma and tissue concentrations. We propose an optimal network grain size for the simulation of tissue volumes of 1 cm3 that allows to make reliable predictions with reasonable computational costs.
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Affiliation(s)
- William Langhoff
- Department of Mathematical Sciences, University of Wisconsin - Milwaukee, Milwaukee, WI 53201-0413, United States of America
| | - Alexander Riggs
- Department of Mathematical Sciences, University of Wisconsin - Milwaukee, Milwaukee, WI 53201-0413, United States of America
| | - Peter Hinow
- Department of Mathematical Sciences, University of Wisconsin - Milwaukee, Milwaukee, WI 53201-0413, United States of America
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47
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How does blood regulate cerebral temperatures during hypothermia? Sci Rep 2018; 8:7877. [PMID: 29777174 PMCID: PMC5959945 DOI: 10.1038/s41598-018-26063-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2017] [Accepted: 04/27/2018] [Indexed: 11/30/2022] Open
Abstract
Macro-modeling of cerebral blood flow can help determine the impact of thermal intervention during instances of head trauma to mitigate tissue damage. This work presents a bioheat model using a 3D fluid-porous domain coupled with intersecting 1D arterial and venous vessel trees. This combined vascular porous (VaPor) model resolves both cerebral blood flow and energy equations, including heat generated by metabolism, using vasculature extracted from MRI data and is extended using a tree generation algorithm. Counter-current flows are expected to increase thermal transfer within the brain and are enforced using either the vascular structure or flow reversal, represented by a flow reversal constant, CR. These methods exhibit larger average brain cooling (from 0.56 °C ± <0.01 °C to 0.58 °C ± <0.01 °C) compared with previous models (0.39 °C) when scalp temperature is reduced. An greater reduction in core brain temperature is observed (from 0.29 °C ± <0.01 °C to 0.45 °C ± <0.01 °C) compared to previous models (0.11 °C) due to the inclusion of counter-current cooling effects. The VaPor model also predicts that a hypothermic average temperature (<36 °C) can be reached in core regions of neonatal models using scalp cooling alone.
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48
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Koeppl T, Santin G, Haasdonk B, Helmig R. Numerical modelling of a peripheral arterial stenosis using dimensionally reduced models and kernel methods. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e3095. [PMID: 29732723 DOI: 10.1002/cnm.3095] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2017] [Revised: 02/22/2018] [Accepted: 04/15/2018] [Indexed: 06/08/2023]
Abstract
In this work, we consider 2 kinds of model reduction techniques to simulate blood flow through the largest systemic arteries, where a stenosis is located in a peripheral artery, i.e., in an artery that is located far away from the heart. For our simulations, we place the stenosis in one of the tibial arteries belonging to the right lower leg (right posterior tibial artery). The model reduction techniques that are used are on the one hand dimensionally reduced models (1-D and 0-D models, the so-called mixed-dimension model) and on the other hand surrogate models produced by kernel methods. Both methods are combined in such a way that the mixed-dimension models yield training data for the surrogate model, where the surrogate model is parametrised by the degree of narrowing of the peripheral stenosis. By means of a well-trained surrogate model, we show that simulation data can be reproduced with a satisfactory accuracy and that parameter optimisation or state estimation problems can be solved in a very efficient way. Furthermore, it is demonstrated that a surrogate model enables us to present after a very short simulation time the impact of a varying degree of stenosis on blood flow, obtaining a speedup of several orders over the full model.
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Affiliation(s)
- Tobias Koeppl
- Department of Hydromechanics and Modelling of Hydrosystems, University of Stuttgart, Pfaffenwaldring 61, D-70569, Stuttgart, Germany
| | - Gabriele Santin
- Institute of Applied Analysis and Numerical Simulation, University of Stuttgart, Pfaffenwaldring 57, D-70569, Stuttgart, Germany
| | - Bernard Haasdonk
- Institute of Applied Analysis and Numerical Simulation, University of Stuttgart, Pfaffenwaldring 57, D-70569, Stuttgart, Germany
| | - Rainer Helmig
- Department of Hydromechanics and Modelling of Hydrosystems, University of Stuttgart, Pfaffenwaldring 61, D-70569, Stuttgart, Germany
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49
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Tang Y, He Y. Numerical modeling of fluid and oxygen exchanges through microcirculation for the assessment of microcirculation alterations caused by type 2 diabetes. Microvasc Res 2018; 117:61-73. [DOI: 10.1016/j.mvr.2018.01.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2017] [Revised: 01/13/2018] [Accepted: 01/14/2018] [Indexed: 12/30/2022]
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50
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Linking brain vascular physiology to hemodynamic response in ultra-high field MRI. Neuroimage 2018; 168:279-295. [DOI: 10.1016/j.neuroimage.2017.02.063] [Citation(s) in RCA: 101] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2016] [Revised: 02/20/2017] [Accepted: 02/21/2017] [Indexed: 01/05/2023] Open
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