SimLivA

SIMulation-supported LIVer Assessment for donor organs (SimLivA) - Continuum-biomechanical modeling for staging of ischemia reperfusion injury during liver transplantation

As part of the Priority Programme SPP 2311:  Robust coupling of continuum-biomechanical in silico models to establish active biological system models for later use in clinical applications - Co-design of modeling, numerics and usability, SimLivA (Grant number 465194077) aims to mathematically model the impact of mechanical alterations due to steatosis and cold ischemia on early ischemia reperfusion injury in liver transplantation. Experimental and clinical data will be used to validate the coupled multiphase and multiscale PDE-ODE model of the liver lobule.

The project addresses the following research questions:

  1. How to co-design computational methods, experimental studies, clinical processes, and technical workflows?
  2. How to improve the multiscale continuum-biomechanical model for prediction of IRI?
  3. How to obtain experimental and clinical data that are essential to quantify the relationship between steatosis, ischemia and reperfusion injury?
  4. How to evaluate the clinical usability of the model?

For further information, click here.

Publications

  1. 2026

    1. Azhdari, M., Kamrava, M., Rezazadeh, G., Pathak, R., Schulze-Späte, U., Ricken, T., & Seyedpour, S. M. (2026). From mechanical models to clinical reality: A systematic review of finite element advances in dental implant design, biomechanics, and optimization. Materials Today Communications, 50, 114314. https://doi.org/10.1016/j.mtcomm.2025.114314
    2. Mandl, L., Nayak, D., Ricken, T., & Goswami, S. (2026). Physics-informed time-integrated DeepONet: Temporal tangent space operator learning for high-accuracy inference. Computer Methods in Applied Mechanics and Engineering, 455, 118917. https://doi.org/10.1016/j.cma.2026.118917
    3. Bafna, M., König, M., Saalfeld, S., Moulisova, V., Liska, V., Dahmen, U., & Albadry, M. (2026). Automated segmentation of hepatic vessels and lobules in whole-slide images using U-net models. Frontiers in Bioinformatics, Volume 6 - 2026. https://doi.org/10.3389/fbinf.2026.1713736
    4. Myshkina, M., Elias, M., Tensil, E., & König, M. (2026). Reproducibility of a Digital Twin of the Angiotensin II Receptor Blocker Losartan. https://doi.org/10.36903/physiome.31359823
    5. Elias, M., Myshkina, M., Nemitz, N., & König, M. (2026). Reproducibility of a Physiologically Based Pharmacokinetic and Pharmacodynamic (PBPK/PD) Model of Dapagliflozin. https://doi.org/10.36903/physiome.31368556
    6. Pathak, R., Seyedpour, S. M., Kutschan, B., Thom, A., Thoms, S., & Ricken, T. (2026). Computational modeling of sea ice freezing dynamics across scales. International Journal of Mechanical Sciences, 309, 111010. https://doi.org/10.1016/j.ijmecsci.2025.111010
    7. Nemitz, N., Elias, M., & König, M. (2026). A Physiologically Based Pharmacokinetic and Pharmacodynamic (PBPK/PD) Model of Dapagliflozin in Type 2 Diabetes Mellitus: The Effect of Dosing, Hepatorenal Impairment, and Food. Pharmaceutics, 18, Article 3. https://doi.org/10.3390/pharmaceutics18030287
    8. Araz, F., Seyedpour, S. M., Ricken, T., & Armiti-Juber, A. (2026). Asymptotic reduction modelling for partially saturated soil based on the Theory of Porous Media. Computational Mechanics. https://doi.org/10.1007/s00466-026-02761-2
    9. Azhdari, M., Rezazadeh, G., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., Ricken, T., & Seyedpour, S. M. (2026). A critical review of non-Fourier heat transfer theories with phase lag in bio-heating: Explaining the variations in reported phase lag coefficients. International Journal of Thermal Sciences, 220, 110376. https://doi.org/10.1016/j.ijthermalsci.2025.110376
    10. Tensil, E., Myshkina, M., & König, M. (2026). A Digital Twin of the Angiotensin II Receptor Blocker Losartan: Physiologically Based Modeling of Blood Pressure Regulation. Pharmaceutics, 18, Article 2. https://doi.org/10.3390/pharmaceutics18020262

  2. 2025

    1. Pathak, R., Seyedpour, S. M., Kutschan, B., Thoms, S., & Ricken, T. (2025). A coupled multiscale description of seasonal Physical--BioGeoChemical dynamics in Southern Ocean Marginal Ice Zone. Environmental Modelling & Software, 185, 106270. https://doi.org/10.1016/j.envsoft.2024.106270
    2. Azhdari, M., Rezazadeh, G., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., Ricken, T., & Seyedpour, S. M. (2025). Non-Fourier bioheat transfer modeling: An extensive critical review of state of the art, caveats, and future directions. International Communications in Heat and Mass Transfer, 169, 109509. https://doi.org/10.1016/j.icheatmasstransfer.2025.109509
    3. Suditsch, M., Egli, F. S., Lambers, L., & Ricken, T. (2025). Growth in biphasic tissue. International Journal of Engineering Science, 208, 104183. https://doi.org/10.1016/j.ijengsci.2024.104183
    4. Pathak, R., Seyedpour, S. M., Kutschan, B., Thom, A., Thoms, S., & Ricken, T. (2025). Simulating sea ice freezing using a continuum mechanical multi-phase and multi-component homogenization framework. Cold Regions Science and Technology, 239, 104591. https://doi.org/10.1016/j.coldregions.2025.104591
    5. Ali Mirza, Z., Azhdari, M., Kolomenskiy, D., Rezazadeh, G., Ricken, T., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2025). Enhancing laser therapy procedure through surface temperature control in multi-layered skin tissue. Journal of Thermal Biology, 129, 104106. https://doi.org/10.1016/j.jtherbio.2025.104106
    6. Azhdari, M., Rezazadeh, G., Ricken, T., Pathak, R., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2025). Temperature distribution in multi-layered skin tissue during laser irradiation considering epidermis sublayers: Virtual Element Method approach. Thermal Science and Engineering Progress, 59, 103297. https://doi.org/10.1016/j.tsep.2025.103297
    7. Tahouni, S., Azhdari, M., Rezazadeh, G., Fathalilou, M., Pathak, R., Ricken, T., & Seyedpour, S. M. (2025). Experimental and numerical analysis of heat transfer in polymer composites with metallic inclusions using virtual element method. Materials & Design, 255, 114172. https://doi.org/10.1016/j.matdes.2025.114172
    8. Mandl, L., Goswami, S., Lambers, L., & Ricken, T. (2025). Separable physics-informed DeepONet : Breaking the curse of dimensionality in physics-informed machine learning. Computer Methods in Applied Mechanics and Engineering, 434, 117586.
    9. Almasi, A., Ricken, T., & Pierce, D. M. (2025). Finite elements of multiscale mixtures (FE2M) in three dimensions: theory, numerical implementation, and analyses. Computational Mechanics. https://doi.org/10.1007/s00466-025-02669-3

  3. 2024

    1. Tautenhahn, H.-M., Ricken, T., Dahmen, U., Mandl, L., Bütow, L., Gerhäusser, S., Lambers, L., Chen, X., Lehmann, E., Dirsch, O., & König, M. (2024). SimLivA–Modeling ischemia‐reperfusion injury in the liver: A first step towards a clinical decision support tool. GAMM-Mitteilungen. https://doi.org/10.1002/gamm.202370003
    2. Pathak, R., Seyedpour, S. M., Kutschan, B., Thom, A., Thoms, S., & Ricken, T. (2024). Modeling freezing and BioGeoChemical processes in Antarctic sea ice. Pamm, 24, Article 2. https://doi.org/10.1002/pamm.202400047
    3. Brodbeck, M., Egli, F. S., Suditsch, M., Seyedpour, S. M., & Ricken, T. (2024). On the influence of non-linearity within two-phase poro-elasticity: Numerical examples and counterexamples. Examples and Counterexamples, 6, 100167. https://doi.org/10.1016/j.exco.2024.100167
    4. Smith, L. P., Bergmann, F. T., Garny, A., Helikar, T., Karr, J., Nickerson, D., Sauro, H., Waltemath, D., & König, M. (2024). The simulation experiment description markup language (SED-ML): language specification for level 1 version 5. Journal of Integrative Bioinformatics. https://doi.org/10.1515/jib-2024-0008
    5. Azhdari, M., Rezazadeh, G., Lambers, L., Ricken, T., Tautenhahn, H.-M., Tautenhahn, F., & Seyedpour, S. M. (2024). Refining thermal therapy: Temperature distribution modeling with distinct absorption in multi-layered skin tissue during infrared laser exposure. International Communications in Heat and Mass Transfer, 157, 107818. https://doi.org/10.1016/j.icheatmasstransfer.2024.107818
    6. Albadry, M., Küttner, J., Grzegorzewski, J., Dirsch, O., Kindler, E., Klopfleisch, R., Liska, V., Moulisova, V., Nickel, S., Palek, R., Rosendorf, J., Saalfeld, S., Settmacher, U., Tautenhahn, H.-M., König, M., & Dahmen, U. (2024). Cross-species variability in lobular geometry and cytochrome P450 hepatic zonation: insights into CYP1A2, CYP2D6, CYP2E1 and CYP3A4. Frontiers in Pharmacology, 15. https://doi.org/10.3389/fphar.2024.1404938
    7. Tautenhahn, H.-M., Ricken, T., Dahmen, U., Mandl, L., Bütow, L., Gerhäusser, S., Lambers, L., Chen, X., Lehmann, E., Dirsch, O., & König, M. (2024). SimLivA-Modeling ischemia-reperfusion injury in the liver: A first step towards a clinical decision support tool. GAMM-Mitteilungen. https://doi.org/10.1002/gamm.202370003
    8. Arasteh-Khoshbin, O., Seyedpour, S. M., Mandl, L., Lambers, L., & Ricken, T. (2024). Comparing durability and compressive strength predictions of hyperoptimized random forests and artificial neural networks on a small dataset of concrete containing nano SiO2 and RHA. European Journal of Environmental and Civil Engineering, 1–20. https://doi.org/10.1080/19648189.2024.2393881

  4. 2023

    1. Lambers, L., Waschinsky, N., Schleicher, J., König, M., Tautenhahn, H.-M., Albadry, M., Dahmen, U., & Ricken, T. (2023). Quantifying Fat Zonation in Liver Lobules: An IntegratedMultiscale In-silico Model Combining DisturbedMicroperfusion and Fat Metabolism via aContinuum-Biomechanical Bi-scale, Tri-phasic Approach. https://doi.org/10.21203/rs.3.rs-3348101/v1
    2. Azhdari, M., Seyedpour, S. M., Lambers, L., Tautenhahn, H.-M., Tautenhahn, F., Ricken, T., & Rezazadeh, G. (2023). Non-local three phase lag bio thermal modeling of skin tissue and experimental evaluation. International Communications in Heat and Mass Transfer, 149, 107146. https://doi.org/10.1016/j.icheatmasstransfer.2023.107146
    3. Mandl, L., Mielke, A., Seyedpour, S. M., & Ricken, T. (2023). Affine transformations accelerate the training of physics-informed neural networks of a one-dimensional consolidation problem. Scientific Reports, 13, Article 1. https://doi.org/10.1038/s41598-023-42141-x

  5. 2021

    1. Seyedpour, S. M., Nabati, M., Lambers, L., Nafisi, S., Tautenhahn, H.-M., Sack, I., Reichenbach, J. R., & Ricken, T. (2021). Application of Magnetic Resonance Imaging in Liver Biomechanics: A Systematic Review. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.733393
    2. Christ, B., Collatz, M., Dahmen, U., Herrmann, K.-H., Höpfl, S., König, M., Lambers, L., Marz, M., Meyer, D., Radde, N., Reichenbach, J. R., Ricken, T., & Tautenhahn, H.-M. (2021). Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function. Frontiers in Physiology, 12. https://doi.org/10.3389/fphys.2021.733868
This image showsLuis Mandl

Luis Mandl

M.Sc.

Acting Head of Machine Learning Group, Research Assistant

This image showsTim Ricken

Tim Ricken

Univ.-Prof. Dr.-Ing.

Head of Department

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