Simulationsgestützte Bewertung von Spenderorganen vor Lebertransplantation (SimLivA) – kontinuums-biomechanische Modellierung für die Beurteilung von Ischämie-Reperfusionsschäden

PIs: Prof. Uta Dahmen, Prof. Tim Ricken, PD Hans-Michael Tautenhahn, Dr. Matthias König

@article{Gerh\"{a}usser2024,

title = {Simulation of zonation-function relationships in the liver using coupled multiscale models: Application to drug-induced liver injury},

author = {Steffen Gerh\"{a}usser and Lena Lambers and Luis Mandl and Julian Franquinet and Tim Ricken and Matthias K\"{o}nig },

editor = {bioRxiv},

url = {https://doi.org/10.1101/2024.03.26.586870},

doi = {https://doi.org/10.1101/2024.03.26.586870 },

year  = {2024},

date = {2024-03-29},

urldate = {2024-03-29},

journal = {[PrePrint], bioRxiv},

abstract = {Multiscale modeling requires the coupling of models on different scales, often based on different mathematical approaches and developed by different research teams. This poses many challenges, such as defining interfaces for coupling, reproducible exchange of submodels, efficient simulation of the models, or reproducibility of results. Here, we present a multiscale digital twin of the liver that couples a partial differential equation (PDE)-based porous media approach for the hepatic lobule with cellular-scale ordinary differential equation (ODE)-based models. The models based on the theory of porous media describe transport, tissue mechanical properties, and deformations at the lobular scale, while the cellular models describe hepatic metabolism in terms of drug metabolism and damage in terms of necrosis. The resulting multiscale model of the liver was used to simulate perfusion-zonation-function relationships in the liver spanning scales from single cell to the lobulus. The model was applied to study the effects of (i) protein zonation patterns (metabolic zonation) and (ii) drug concentration dependence on spatially heterogeneous liver damage in the form of necrosis. Depending on the zonation pattern, different liver damage patterns could be reproduced, including periportal and pericentral necrosis as seen in drug-induced liver injury (DILI). Increasing the drug concentration led to an increase in the observed damage pattern. A key point for the success was the integration of domain-specific simulators based on standard exchange formats, i.e., libroadrunner for the high-performance simulation of ODE-based systems and FEBio for the simulation of the continuum-biomechanical part. This allows a standardized and reproducible exchange of cellular scale models in the Systems Biology Markup Language (SBML) between research groups.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lambers2024,

title = {Quantifying Fat Zonation in Liver Lobules: An Integrated Multiscale In-silico Model Combining Disturbed Microperfusion and Fat Metabolism via a Continuum-Biomechanical Bi-scale, Tri-phasic Approach},

author = {Lena Lambers and Navina Waschinsky and Jana Schleicher and Matthias K\"{o}nig and Hans-Michael Tautenhahn and Mohamed Albadry and Uta Dahmen and Tim Ricken},

editor = {Springer Link},

url = {https://link.springer.com/article/10.1007/s10237-023-01797-0#citeas},

doi = {https://doi.org/10.1007/s10237-023-01797-0},

year  = {2024},

date = {2024-02-25},

urldate = {2024-02-25},

journal = {Biomechanics and Modeling in Mechanobiology},

abstract = {Metabolic zonation refers to the spatial separation of metabolic functions along the sinusoidal axes of the liver. This phenomenon forms the foundation for adjusting hepatic metabolism to physiological requirements in health and disease (e.g., metabolic dysfunction-associated steatotic liver disease/MASLD). Zonated metabolic functions are influenced by zonal morphological abnormalities in the liver, such as periportal fibrosis and pericentral steatosis. We aim to analyze the interplay between microperfusion, oxygen gradient, fat metabolism and resulting zonated fat accumulation in a liver lobule. Therefore we developed a continuum biomechanical, tri-phasic, bi-scale, and multicomponent in silico model, which allows to numerically simulate coupled perfusion-function-growth interactions two-dimensionally in liver lobules. The developed homogenized model has the following specifications: (i) thermodynamically consistent, (ii) tri-phase model (tissue, fat, blood), (iii) penta-substances (glycogen, glucose, lactate, FFA, and oxygen), and (iv) bi-scale approach (lobule, cell). Our presented in silico model accounts for the mutual coupling between spatial and time-dependent liver perfusion, metabolic pathways and fat accumulation. The model thus allows the prediction of fat development in the liver lobule, depending on perfusion, oxygen and plasma concentration of free fatty acids (FFA), oxidative processes, the synthesis and the secretion of triglycerides (TGs). The use of a bi-scale approach allows in addition to focus on scale bridging processes. Thus, we will investigate how changes at the cellular scale affect perfusion at the lobular scale and vice versa. This allows to predict the zonation of fat distribution (periportal or pericentral) depending on initial conditions, as well as external and internal boundary value conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Tautenhahn2024,

title = {SimLivA\textendashModeling ischemia-reperfusion injury in the liver: A first step towards a clinical decision support tool},

author = {Hans-Michael Tautenhahn and Tim Ricken and Uta Dahmen and Luis Mandl and Laura B\"{u}tow and Steffen Gerh\"{a}usser and Lena Lambers and Xinpei Chen and Elina Lehmann and Olaf Dirsch and Matthias K\"{o}nig},

editor = {Wiley Online Library},

url = {https://onlinelibrary.wiley.com/doi/10.1002/gamm.202370003},

doi = {https://doi.org/10.1002/gamm.202370003},

year  = {2024},

date = {2024-01-23},

journal = {GAMM-Mitteilungen e202370003},

abstract = {The SIMulation supported LIVer Assessment for donor organs (SimLivA) project aims to develop a mathematical model to accurately simulate the influence of mechanical alterations in marginal liver grafts (specifically steatotic ones) and cold ischemia on early ischemia-reperfusion injury (IRI) during liver transplantation. Our project tackles significant research challenges, including the co-development of computational methodologies, experimental studies, clinical processes, and technical workflows. We aim to refine a continuum-biomechanical model for enhanced IRI prediction, collect pivotal experimental and clinical data, and assess the clinical applicability of our model. Our efforts involve augmenting and tailoring a coupled continuum-biomechanical, multiphase, and multi-scale partial differential equation-ordinary differential equation (PDE-ODE) model of the liver lobule, allowing us to numerically simulate IRI depending on the degree of steatosis and the duration of ischemia. The envisaged model will intertwine the structure, perfusion, and function of the liver, serving as a crucial aid in clinical decision-making processes. We view this as the initial step towards an in-silico clinical decision support tool aimed at enhancing the outcomes of liver transplantation. In this paper, we provide an overview of the SimLivA project and our preliminary findings, which include: a cellular model that delineates critical processes in the context of IRI during transplantation; and the integration of this model into a multi-scale PDE-ODE model using a homogenized, multi-scale, multi-component approach within the Theory of Porous Media (TPM) framework. The model has successfully simulated the interconnected relationship between structure, perfusion, and function\textemdashall of which are integral to IRI. Initial results show simulations at the cellular scale that describe critical processes related to IRI during transplantation. After integrating this model into a multiscale PDE-ODE model, first simulations were performed on the spatial distribution of key functions during warm and cold ischaemia. In addition, we were able to study the effect of tissue perfusion and temperature, two critical parameters in the context of liver transplantation and IRI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albadry2023,

title = {Cross-Species Variability in Lobular Geometry and Cytochrome P450 Hepatic Zonation: Insights into CYP1A2, CYP2E1, CYP2D6 and CYP3A4},

author = {Mohamed Albadry and Jonas Kuettner and Jan Grzegorzewski and Olaf Dirsch and Eva Kindler and Robert Klopfleisch and Vaclav Liska and Vladimira Moulisova and Sandra Nickel and Richard Palek and Jachym Rosendorf and Sylvia Saalfeld and Utz Settmacher and Hans-Michael Tautenhahn and Matthias K\"{o}nig and Uta Dahmen},

editor = {bioRxiv},

url = {https://www.biorxiv.org/content/10.1101/2023.12.28.573567v1},

doi = {https://doi.org/10.1101/2023.12.28.573567},

year  = {2023},

date = {2023-12-28},

journal = {[PrePrint], bioRxiv},

abstract = {This study explores the critical interplay between lobular geometry and the zonated distribution of cytochrome P450 (CYP) enzymes across species. We present an innovative approach to assess lobular geometry and zonation patterns using whole slide imaging (WSI). This method allows a detailed, systematic comparison of lobular structures and spatial distribution of key CYP450 enzymes and glutamine synthetase in four different species (mouse, rat, pig, and human). Our results shed light on species differences in lobular geometry and enzymatic zonation, providing critical insights for drug metabolism research. Based on our approach we could determine the minimum number of lobules required for a statistically representative analysis, an important piece of information when evaluating liver biopsies and deriving information from WSI.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Azhdari2023,

title = {Non-local three phase lag bio thermal modeling of skin tissue and experimental evaluation},

author = {Mohammad Azhdari and Seyed Morteza Seyedpour and Lena Lambers and Hans-Michael Tautenhahn and Franziska Tautenhahn and Tim Ricken and Ghader Rezazadeh},

editor = {Elsevier},

url = {https://www.sciencedirect.com/science/article/pii/S0735193323005353?via%3Dihub},

doi = {https://doi.org/10.1016/j.icheatmasstransfer.2023.107146},

year  = {2023},

date = {2023-11-10},

journal = {Heat and Mass Transfer (149)},

abstract = {In this paper, the thermal behavior of living tissue has been modeled using a non-local three-phase lag approach. The simulation results of this model- ing have been compared with experimental results of alternating radiation with different periods on human skin, yielding satisfactory alignments. Ad- ditionally, it has been investigated that the TPL model, which is an equation with an integral term, can simulate energy accumulation within the dermal tissue. Moreover, the non-local nature of the modeling has been explored to alter the influence of phase lag terms. Furthermore, apart from numer- ically solving the equation, an analytical solution has been derived for the frequency equation, demonstrating the effects of simulation parameters on the frequency equation and simulation results. The obtained results indi cate that these parameters not only independently affect the outcomes but also interact with other parameters, leading to variations beyond their direct impacts.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mandl2023,

title = {Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem},

author = {Luis Mandl and Andr\'{e} Mielke and Seyed Morteza Seyedpour and Tim Ricken},

editor = {Scientific Reports},

url = {https://www.nature.com/articles/s41598-023-42141-x},

doi = {https://doi.org/10.1038/s41598-023-42141-x},

year  = {2023},

date = {2023-09-20},

urldate = {2023-09-20},

journal = {Nature Scientific Reports},

abstract = {Physics-informed neural networks (PINNs) leverage data and knowledge about a problem. They provide a nonnumerical pathway to solving partial differential equations by expressing the field solution as an artificial neural network. This approach has been applied successfully to various types of differential equations. A major area of research on PINNs is the application to coupled partial differential equations in particular, and a general breakthrough is still lacking. In coupled equations, the optimization operates in a critical conflict between boundary conditions and the underlying equations, which often requires either many iterations or complex schemes to avoid trivial solutions and to achieve convergence. We provide empirical evidence for the mitigation of bad initial conditioning in PINNs for solving one-dimensional consolidation problems of porous media through the introduction of affine transformations after the classical output layer of artificial neural network architectures, effectively accelerating the training process. These affine physics-informed neural networks (AfPINNs) then produce nontrivial and accurate field solutions even in parameter spaces with diverging orders of magnitude. On average, AfPINNs show the ability to improve the L_2 relative error by 64.84% after 25,000 epochs for a one-dimensional consolidation problem based on Biot’s theory, and an average improvement by 58.80% with a transfer approach to the theory of porous media.



},

keywords = {},

pubstate = {published},

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}

@article{Maheshvare2023,

title = {A pathway model of glucose-stimulated insulin secretion in the pancreatic β-cell},

author = {M. Deepa Maheshvare and Soumyendu Raha and Matthias K\"{o}nig and Debnath Pal},

editor = {Frontiers in Endocrinology},

url = {https://www.frontiersin.org/journals/endocrinology/articles/10.3389/fendo.2023.1185656/full},

doi = {https://doi.org/10.3389/fendo.2023.1185656 },

year  = {2023},

date = {2023-08-02},

journal = {Frontiers in Endocrinology},

abstract = {The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic β-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct a novel data-driven kinetic model of GSIS in the pancreatic β-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and β-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and phenomenological equations for insulin secretion coupled to cellular energy state, ATP dynamics and (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the β-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and biphasic insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic β-cell.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{K\"{o}nig2023,

title = {Specifications of standards in systems and synthetic biology: status and developments in 2022 and the COMBINE meeting 2022},

author = {Matthias K\"{o}nig and Padraig Gleeson and Martin Golebiewski and Thomas E. Gorochowski and Michael Hucka and Sarah M. Keating and Chris J. Myers and David P. Nickerson and Bj\"{o}rn Sommer and Dagmar Waltemath and Falk Schreiber},

editor = {De Gruyter},

url = {https://www.degruyter.com/document/doi/10.1515/jib-2023-0004/html},

doi = {https://doi.org/10.1515/jib-2023-0004},

year  = {2023},

date = {2023-03-29},

journal = {Journal of Integrative Bioinformatics},

abstract = {This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COM-BINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards:CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Lan-guage (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINEstandards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rauchfu\ss2023,

title = {Critical Evaluation of Discarded Donor Livers in the Eurotransplant Region: Potential Implications for Machine Perfusion},

author = {Falk Rauchfu\ss and Hans-Michael Tautenhahn and Felix Dondorf and Aladdin Ali-Deeb and Utz Settmacher },

editor = {Annals of Transplantation},

url = {https://annalsoftransplantation.com/abstract/full/idArt/938132},

doi = {10.12659/AOT.938132},

year  = {2023},

date = {2023-03-17},

journal = {Annals of Transplantation},

abstract = { BACKGROUND: There are still many offered donor livers that are declined during the allocation process. Machine perfusion offers the option to evaluate (especially marginal) donor organs and to better decide whether a graft has the potential of being transplanted or not. There is a lack of clear detailed data on why organs are declined and how many donor livers would have the potential of being evaluated in the machine.



MATERIAL AND METHODS: We retrospectively reviewed 1356 donor livers between 2016 and 2018, which were offered by Eurotransplant and were declined during the allocation process; 284 grafts were from donor after cardiac death (DCD) and 1072 donations were from after brain death (DBD). The analysis was performed independently and blinded by senior transplant surgeons.



RESULTS: There were 904 (66.6%) donor livers with potential to be evaluated as suitable grafts in machine perfusion, whereas 417 (30.8%) organs were definitely not-transplantable, mainly due to liver cirrhosis, (untreated) donor malignancy, cardiac diseases of the donor leading to a hepatic congestion, and/or systemic infections in the donor. Donors in blood group “AB” were disproportionally often rejected. Due to missing data, 35 (2.6%) organs could not be sufficiently evaluated.



CONCLUSIONS: Our data suggest that many declined donor livers have potential of being evaluated by machine perfusion. Comprehensive use of machine perfusion is necessary and useful to improve the current organ shortage. },

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Albadry2022,

title = {Periportal steatosis in mice affects distinct parameters of pericentral drug metabolism},

author = {Mohamed Albadry and Sebastian H\"{o}pfl and Nadia Ehteshamzad and Matthias K\"{o}nig and Michael B\"{o}ttcher and Jasna Neumann and Amelie Lupp and Olaf Dirsch and Nicole Radde and Bruno Christ and Madlen Christ and Lars Ole Schwen and Hendrik Laue and Robert Klopfleisch and Uta Dahmen},

editor = {Scientific Reports},

url = {https://www.nature.com/articles/s41598-022-26483-6#citeas},

doi = {https://doi.org/10.1038/s41598-022-26483-6},

year  = {2022},

date = {2022-12-17},

journal = {Nature Scientific Reports},

abstract = {Little is known about the impact of morphological disorders in distinct zones on metabolic zonation. It was described recently that periportal fibrosis did affect the expression of CYP proteins, a set of pericentrally located drug-metabolizing enzymes. Here, we investigated whether periportal steatosis might have a similar effect. Periportal steatosis was induced in C57BL6/J mice by feeding a high-fat diet with low methionine/choline content for either two or four weeks. Steatosis severity was quantified using image analysis. Triglycerides and CYP activity were quantified in photometric or fluorometric assay. The distribution of CYP3A4, CYP1A2, CYP2D6, and CYP2E1 was visualized by immunohistochemistry. Pharmacokinetic parameters of test drugs were determined after injecting a drug cocktail (caffeine, codeine, and midazolam). The dietary model resulted in moderate to severe mixed steatosis confined to periportal and midzonal areas. Periportal steatosis did not affect the zonal distribution of CYP expression but the activity of selected CYPs was associated with steatosis severity. Caffeine elimination was accelerated by microvesicular steatosis, whereas midazolam elimination was delayed in macrovesicular steatosis. In summary, periportal steatosis affected parameters of pericentrally located drug metabolism. This observation calls for further investigations of the highly complex interrelationship between steatosis and drug metabolism and underlying signaling mechanisms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Welsh2022,

title = {libRoadRunner 2.0: a high performance SBML simulation and analysis library},

author = {Ciaran Welsh and Jin Xu and Lucian Smith and Matthias K\"{o}nig and Kiri Choi and Herbert M Sauro},

editor = {Oxford Academic},

url = {https://academic.oup.com/bioinformatics/article/39/1/btac770/6883908},

doi = {https://doi.org/10.1093/bioinformatics/btac770},

year  = {2022},

date = {2022-12-08},

journal = {Bioinformatics},

volume = {39},

issue = {1},

abstract = {Motivation



This article presents libRoadRunner 2.0, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using the systems biology markup language (SBML).

Results



libRoadRunner is a self-contained library, able to run either as a component inside other tools via its C++, C and Python APIs, or interactively through its Python or Julia interface. libRoadRunner uses a custom just-in-time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a large variety of processors, making it fast enough to simulate extremely large models or repeated runs in reasonable timeframes. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) as well as several SBML extensions such as hierarchical composition and probability distributions. It offers multiple deterministic and stochastic integrators, as well as tools for steady-state, sensitivity, stability and structural analyses.

Availability and implementation



libRoadRunner binary distributions for Windows, Mac OS and Linux, Julia and Python bindings, source code and documentation are all available at https://github.com/sys-bio/roadrunner, and Python bindings are also available via pip. The source code can be compiled for the supported systems as well as in principle any system supported by LLVM-13, such as ARM-based computers like the Raspberry Pi. The library is licensed under the Apache License Version 2.0.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Grzegorzewski2022,

title = {Physiologically based pharmacokinetic (PBPK) modeling of the role of CYP2D6 polymorphism for metabolic phenotyping with dextromethorphan},

author = {Jan Grzegorzewski and Janosch Brandhorst and Matthias K\"{o}nig},

editor = {Frontiers in Pharmacology, Sec. Pharmacogenetics and Pharmacogenomics},

url = {https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.1029073/full},

doi = {https://doi.org/10.3389/fphar.2022.1029073 },

year  = {2022},

date = {2022-10-24},

journal = {Frontiers in Pharmacology},

abstract = {The cytochrome P450 2D6 (CYP2D6) is a key xenobiotic-metabolizing enzyme involved in the clearance of many drugs. Genetic polymorphisms in CYP2D6 contribute to the large inter-individual variability in drug metabolism and could affect metabolic phenotyping of CYP2D6 probe substances such as dextromethorphan (DXM). To study this question, we (i) established an extensive pharmacokinetics dataset for DXM; and (ii) developed and validated a physiologically based pharmacokinetic (PBPK) model of DXM and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) based on the data. Drug-gene interactions (DGI) were introduced by accounting for changes in CYP2D6 enzyme kinetics depending on activity score (AS), which in combination with AS for individual polymorphisms allowed us to model CYP2D6 gene variants. Variability in CYP3A4 and CYP2D6 activity was modeled based on in vitro data from human liver microsomes. Model predictions are in very good agreement with pharmacokinetics data for CYP2D6 polymorphisms, CYP2D6 activity as described by the AS system, and CYP2D6 metabolic phenotypes (UM, EM, IM, PM). The model was applied to investigate the genotype-phenotype association and the role of CYP2D6 polymorphisms for metabolic phenotyping using the urinary cumulative metabolic ratio (UCMR), DXM/(DXO + DXO-Glu). The effect of parameters on UCMR was studied via sensitivity analysis. Model predictions indicate very good robustness against the intervention protocol (i.e. application form, dosing amount, dissolution rate, and sampling time) and good robustness against physiological variation. The model is capable of estimating the UCMR dispersion within and across populations depending on activity scores. Moreover, the distribution of UCMR and the risk of genotype-phenotype mismatch could be estimated for populations with known CYP2D6 genotype frequencies. The model can be applied for individual prediction of UCMR and metabolic phenotype based on CYP2D6 genotype. Both, model and database are freely available for reuse.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Bertrand2022,

title = {On robust discretization methods for poroelastic problems: Numerical examples and counter-examples},

author = {Fleurianne Bertrand and Maximilian Brodbeck and Tim Ricken},

editor = {Elsevier },

url = {https://www.sciencedirect.com/science/article/pii/S2666657X22000209?via%3Dihub},

doi = {https://doi.org/10.1016/j.exco.2022.100087},

year  = {2022},

date = {2022-09-24},

journal = {Examples and Counterexamples (2)},

abstract = {Finite element approximations of poroelastic materials are nowadays used within multiple applications. Due to wide variation of possible material parameters, robustness of the considered discretization is important. Within this contribution robust of discretization schemes, initially developed for Biot’s theory, will be applied within the Theory of Porous Media. Selected numerical test-cases, special attention will be paid to incompressible and impermeable regimes, are conducted.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ricken2022,

title = {Theoretical formulation and computational aspects of a two-scale homogenization scheme combining the TPM and FE² method for poro-elastic fuid-saturated porous media},

author = {Tim Ricken and J\"{o}rg Schr\"{o}der and Joachim Bluhm and Florian Bartel},

editor = {Elsevier },

url = {https://www.sciencedirect.com/science/article/pii/S0020768321004674?via%3Dihub},

doi = {https://doi.org/10.1016/j.ijsolstr.2021.111412},

year  = {2022},

date = {2022-02-28},

journal = {International Journal of Solids and Structures, 2022},

abstract = {The focus of this investigation lies on the development of a two-scale homogenization scheme for poro-elastic fluid-saturated porous media. For this purpose, the general concepts of the Theory of Porous Media (TPM) are combined with the FE method. After an introduction of the basics of TPM, the weak forms for the macroscopic and the microscopic scale will be formulated and the averaged macroscopic tangent moduli considering the microscale will be derived. Additionally, the formulation of lower level boundary conditions, which refer to the quantities that will be transmitted from the macro- to the microscale, in strict compliance with the Hill\textendashMandel homogeneity condition, is derived. Finally, a numerical example will be presented, pointing out the gained features of the methodology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christ2021,

title = {Hepatectomy-induced alterations in hepatic perfusion and function \textendash Towards multi-scale modeling for a better risk assessment in liver surgery},

author = {Bruno Christ, Maximilian Collatz, Uta Dahmen, Karl-Heinz Herrmann, Sebastian H\"{o}pfl and Matthias K\"{o}nig and Lena Lambers and Manja Marz and Daria Meyer and Nicole Radde and J\"{u}rgen R. Reichenbach and Tim Ricken and Hans-Michael Tautenhahn},

editor = {Frontiers in Physiology, Sec. Computational Physiology and Medicine},

url = {https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.733868/full},

doi = {https://doi.org/10.3389/fphys.2021.733868},

year  = {2021},

date = {2021-11-18},

journal = {Frontiers in Physiology (12)},

abstract = {Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Seyedpour2021,

title = {Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review},

author = {Seyed M. Seyedpour and Mehdi Nabati and Lena Lambers and Sara Nafisi and Hans-Michael Tautenhahn and Ingolf Sack and J\"{u}rgen R. Reichenbach and Tim Ricken},

editor = {Frontiers in Physiology, Sec. Computational Physiology and Medicine},

url = {https://www.frontiersin.org/journals/physiology/articles/10.3389/fphys.2021.733393/full},

doi = {https://doi.org/10.3389/fphys.2021.733393 },

year  = {2021},

date = {2021-09-22},

urldate = {2021-09-22},

journal = {Frontiers in Physiology (12)},

abstract = {MRI-based biomechanical studies can provide a deep understanding of the mechanisms governing liver function, its mechanical performance but also liver diseases. In addition, comprehensive modeling of the liver can help improve liver disease treatment. Furthermore, such studies demonstrate the beginning of an engineering-level approach to how the liver disease affects material properties and liver function. Aimed at researchers in the field of MRI-based liver simulation, research articles pertinent to MRI-based liver modeling were identified, reviewed, and summarized systematically. Various MRI applications for liver biomechanics are highlighted, and the limitations of different viscoelastic models used in magnetic resonance elastography are addressed. The clinical application of the simulations and the diseases studied are also discussed. Based on the developed questionnaire, the papers' quality was assessed, and of the 46 reviewed papers, 32 papers were determined to be of high-quality. Due to the lack of the suitable material models for different liver diseases studied by magnetic resonance elastography, researchers may consider the effect of liver diseases on constitutive models. In the future, research groups may incorporate various aspects of machine learning (ML) into constitutive models and MRI data extraction to further refine the study methodology. Moreover, researchers should strive for further reproducibility and rigorous model validation and verification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}