The K.G. Jebsen Centre for Brain Fluid Research, led by the University of Oslo and Oslo University Hospital with Simula as a major partner, aims to develop imaging- and blood-based biomarkers for dementia diagnosis, create precision treatment tools for brain cancer, and understand brain solute transport and clearance mechanisms, utilizing advanced computational mathematics, simulation technology, and artificial intelligence.
This project aims to simulate heart activity and heart tissue behavior during severe hemorrhagic shock, with an emphasis on speedy testing. We’ll be using entirely computer-based models for this. The initial outcomes of this project will be two linked models running on a supercomputer: one model will represent the overall heart and blood vessel changes during hemorrhagic shock, and the other will represent heart tissue, for example, a group of cell models in tissue reacting to the body-wide stress caused by these conditions
Recent breakthroughs in hiPSC research have led to the development of ‘heart-on-chip’ models, offering potential for transformative drug development, but the integration of these models into pipelines remains a challenge; the IdentiPhy project aims to address this by creating technology that enhances compound safety risk prediction using optical measurements and computational analysis, with the goal of improving the efficiency and reducing costs and time in bringing safe drugs to market.
Simulation of Cardiac Devices and Drugs for In-Silico Testing and Certification (SimCardioTest)
Published in Institutt for matematiske fag, NTNU, 2014
In this thesis we will study wavelet techniques for image classification in ultrasound(US) images. The aim is to develop a method for classifying the degree of inflammation in finger-joints.We develop and apply the techniques of the windowed scattering transform. This is a wavelet-based technique which is proven to be very efficient in image classification problems. Both theoretical and numerical sides have been considered. We also discuss other possible techniques for classification of US images, in particular a method based on the area of inflammation.
https://brage.bibsys.no/xmlui/bitstream/handle/11250/259333/733307_FULLTEXT01.pdf
Published in International Journal for Numerical Methods in Biomedical Engineering, 2017
This paper discusses the limitations of current data assimilation procedures for personalizing computational models of cardiac mechanics and proposes a new adjoint gradient-based method that can efficiently handle high-dimensional parameters. The method is tested on synthetic and clinical data, demonstrating its ability to produce accurate personalized models of cardiac mechanics.
Published in Journal of Computational Science, 2018
Cardiac computational models, individually personalized, can provide clinicians with useful diagnostic information and aid in treatment planning. A major bottleneck in this process can be determining model parameters to fit created models to individual patient data. However, adjoint-based data assimilation techniques can now rapidly estimate high dimensional parameter sets. This method is used on a cohort of heart failure patients, capturing cardiac mechanical information and comparing it with a healthy control group. Excellent fit (R2 ≥ 0.95) to systolic strains is obtained, and analysis shows a significant difference in estimated contractility between the two groups.
Published in Patient-Specific Computational Modeling, 2018
In this thesis we have developed a framework to effectively build a virtual heart of the individual patient, so that measurements made in the clinic can be incorporated into the underlying mathematical model. Such virtual hearts have been used to study the mechanics of the heart in different patient groups. Furthermore, we evaluated different biomarkers that may have potential clinical value, and evaluated the performance of the method. These simulations can be performed on a regular laptop in just a few hours, which means that this framework can potentially be included as a diagnostic toolbox in the clinic.
https://www.duo.uio.no/bitstream/handle/10852/62015/PhD-Finsberg-2018.pdf
Published in International Journal for Numerical Methods in Biomedical Engineering, 2018
This study presents a novel and efficient framework for creating personalized computational models of biventricular heart mechanics. The models, based on data assimilation and patient-specific parameters, accurately estimate important physiological quantities and provide insights into the role of fiber angles on heart function. The framework is highly efficient and may have diagnostic applications for patient-specific cardiac mechanics modeling.
Published in Biomechanics and Modeling in Mechanobiology, 2018
This study introduces a data assimilation technique to estimate personalized models of cardiac mechanics with heterogeneous elastic material properties, specifically in the context of myocardial infarction. The method is tested using clinical data, demonstrating good matches to regional strains and providing insights into stress-strain relationships. This is the first application of adjoint-based data assimilation to estimate cardiac elastic heterogeneities in 3D from medical images.
Published in Journal of Open Source Software, 2019
pulse is a python package based on FEniCS for solving problems in cardiac mechanics. The user can pick any of the built-in meshes or choose a custom user-defined mesh. A collection of different demos showing how to use the pulse library is found in the repository.
Published in American Journal of Physiology-Heart and Circulatory Physiology, 2019
This study examines the mechanical changes associated with pulmonary arterial hypertension (PAH) by analyzing clinical data and using computational modeling. The findings suggest that the ratio of right ventricle (RV) to left ventricle (LV) end-diastolic volume can be used as a clinical index for assessing disease severity and estimating RV contractility in PAH patients.
https://journals.physiology.org/doi/full/10.1152/ajpheart.00094.2019
Published in Frontiers in Pharmacology, 2020
This study aims to improve the usefulness of human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) for drug screening applications by addressing their relative immaturity compared to adult cardiomyocytes. By utilizing an updated computational procedure, the methodology can more efficiently identify drug-induced changes and quantitate important metrics, ultimately enhancing the potential for employing stem cell-derived experimental tissues in elucidating drug effects in adult cardiomyocytes
Published in Clinical and Translational Science, 2021
This study presents a chronic preclinical drug screening platform, a cardiac microphysiological system, to assess the cardiotoxicity associated with repurposed hydroxychloroquine (HCQ) and azithromycin (AZM) polytherapy in the context of a mock phase I safety clinical trial. The platform accurately predicted clinical outcomes and identified biomarkers for negative effects on tissue function, morphology, and antioxidant protection, providing valuable insights for clinicians in designing trials and accelerating access to safe COVID-19 therapeutics.
https://ascpt.onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cts.13038
Published in Frontiers in Pharmacology, 2021
This study highlights the challenges faced in finding effective treatments for COVID-19 and the need for rapid evaluation of potential therapeutics. The researchers developed a cardiac microphysiological system (MPS) that accurately predicted cardiac liabilities associated with hydroxychloroquine (HCQ) and azithromycin (AZM), including arrhythmias and QT interval prolongation. The MPS provides a high-content screening platform for assessing the cardiac safety of potential therapeutics, allowing for faster and safer access to effective treatments for COVID-19.
Published in ACS Pharmacology & Translational Science, 2022
This study emphasizes the importance of evaluating arrhythmogenic drugs before market approval and highlights the limitations of current in vitro models using two-dimensional (2D) culture formats. The researchers present a three-dimensional (3D) cardiac microphysiological system (MPS) using human-induced pluripotent stem cell-derived cardiomyocytes, which successfully predicted drug cardiotoxicity risks based on changes in action potential duration, beat waveform, and occurrence of proarrhythmic events. The cardiac MPS outperformed existing 2D models and provides a promising platform for rapid and reliable screening of proarrhythmic drug risk.
Published in Computing in Cardiology Conference (CinC), 2022
This study presents a novel 3D electromechanical (EM) model to simulate the effects of inotropic drugs, specifically Omecamtiv Mecarbil (OM), on human cardiac tissue. The model successfully replicated concentration-dependent drug effects, such as increased active tension, but indicated the need for further development to capture the characteristic delay in time to peak contraction observed in experimental data.
Published in Biomechanics and Modeling in Mechanobiology, 2023
This study introduces a mathematical and numerical framework for investigating tissue-level cardiac mechanics on a microscale by considering explicit three-dimensional geometrical representations of cells within a matrix. The model explores mechanical differences between the extracellular and intracellular spaces, and sensitivity analysis reveals the significance of extracellular matrix stiffness for intracellular stress under contraction. This work expands upon existing models and offers a new framework to explore complex cell-cell and cell-matrix interactions in cardiac mechanics.
Recommended citation: Telle, Åshild, et al. "A cell-based framework for modeling cardiac mechanics." Biomechanics and Modeling in Mechanobiology 22.2 (2023): 515-539. https://link.springer.com/article/10.1007/s10237-022-01660-8
Published in Journal of Open Source Software, 2023
This paper presents a fully coupled electromechanical model to study the effects of cardioactive drugs on the heart. The model combines a human cell electromechanical model with a monodomain partial differential equation representation of the electrical substrate and an incompressible, anisotropic, hyperelastic continuum model. The model is implemented in the FEniCS framework and incorporates iterative conjugate gradient and sparse direct solvers to solve the equations.
Published in Annals of Biomedical Engineering, 2023
This study explores a novel measure, the standard deviation of regional wall stress at the time of mitral valve closure (SD_MVC), for assessing response to cardiac resynchronization therapy (CRT) in heart failure patients. Using a computational modeling framework, the researchers found that patients with lower SD_MVC responded better to CRT, with SD_MVC correlating with long-term response based on end-diastolic volume reduction. These findings suggest that SD_MVC could potentially improve patient selection criteria for CRT implantation. However, further studies with a larger patient cohort are needed to validate these results.
Published in Journal of Open Source Software, 2023
This work presents SMART, a high-performance simulation package based on the FEniCS finite element library, for modeling and simulating spatially-varying reaction-transport processes in cellular systems. SMART allows for the specification of reaction pathways and supports complex cell geometries obtained from advanced microscopy and reconstruction methods. By addressing the challenges of high dimensionality, non-linearities, and coupling, SMART enables the detailed modeling of cell signaling pathways and the prediction of cellular function.
Published in Computational Physiology: Simula Summer School 2023− Student Reports, 2024
Mechano-electric feedback (MEF) is thought to be an important factor in the increased arrhythmic risk observed clinically in heart failure and chronic infarct patients
Published in Frontiers in Physiology, 2024
Pulmonary arterial hypertension (PAH) presents a significant challenge to right ventricular (RV) function due to progressive pressure overload, necessitating adaptive remodeling in the form of increased wall thickness, enhanced myocardial contractility and stiffness to maintain cardiac performance
https://www.frontiersin.org/articles/10.3389/fphys.2024.1360389/full
Published in Nature Computational Science, 2024
Spatial Modeling Algorithms for Reactions and Transport (SMART) is a software package that uses advanced finite element analysis to efficiently and accurately simulate cell signaling networks and molecular transport in realistic cellular geometries, demonstrating its versatility and effectiveness across various biological systems.
Published in Biomedical Physics & Engineering Express, 2024
Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are an effective tool for studying cardiac function and disease, and hold promise for screening drug effects on human tissue
https://iopscience.iop.org/article/10.1088/2057-1976/ad7268/pdf
Published in Computer Methods in Applied Mechanics and Engineering, 2025
In cardiovascular mechanics, achieving consensus in simulation results is crucial for reproducibility, and to address gaps in existing benchmarks, we propose new cardiac benchmark problems and solutions that include assessments of passive and active material behavior, viscous effects, and pericardial boundary conditions, with simplified analytical fiber definitions and active stress models for monoventricular and biventricular domains.
https://www.sciencedirect.com/science/article/pii/S0045782524007394
Package to compute features of traces from action potential models
Cardiac electrophysiology solver
Tools for working with mps files
Library for tracking motion in cardiac mps data
Simula Cardiac ElectroMechanics Solver
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This seminar aims to elevate the level of software development for scientific computing for PhDs, postdocs, and researchers. Participants will engage with expert-led sessions on best practices, covering topics such as code quality, reproducibility, scalability, and performance optimization. The session ends with an interactive workshop providing hands-on experience. By bridging the gap between scientific inquiry and software development, we aspire to enhance the robustness, efficiency, and accuracy of computational research.
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Several researchers here in Oslo are working on projects related to myocardial work who may have several common issues and topics to discuss. We therefore organize this regional work seminar so they can present their current projects and to stimulate networking.
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This seminar are targeted PhD students that want learn about how to make their computational work more reproducible.
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A beginner’s guide to cardiac modeling: In this talk I will present different ways we usually model the heart with the focus on developing new drugs. One example is by looking at how to model a single cell, and how a single cell is affected by a drug. Then I will try to show how this can be translated to the whole organ an see how such models can be used to study safety and efficacy of drugs at the level of the individual.
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A beginner’s guide to cardiac modeling: In this talk I will present different ways we usually model the heart with the focus on developing new drugs. One example is by looking at how to model a single cell, and how a single cell is affected by a drug. Then I will try to show how this can be translated to the whole organ an see how such models can be used to study safety and efficacy of drugs at the level of the individual.
Undergraduate course, University of Oslo, Department of informatics, 2019
The course is a continuation of the course IN1900, and provides an introduction to more advanced concepts in programming and software development. The central goal of the subject is to introduce new tools and concepts for scientific programming. For more info see https://www.uio.no/studier/emner/matnat/ifi/IN1910/h19/index.html
Undergraduate course, University of Oslo, Department of informatics, 2020
The course is a continuation of the course IN1900, and provides an introduction to more advanced concepts in programming and software development. The central goal of the subject is to introduce new tools and concepts for scientific programming. For more info see https://www.uio.no/studier/emner/matnat/ifi/IN1910/h20/index.html
Undergraduate course, University of Oslo, Department of informatics, 2021
The course is a continuation of the course IN1900, and provides an introduction to more advanced concepts in programming and software development. The central goal of the subject is to introduce new tools and concepts for scientific programming. For more info see https://www.uio.no/studier/emner/matnat/ifi/IN1910/h21/index.html
Undergraduate course, University of Oslo, Department of informatics, 2022
The course is a continuation of the course IN1900, and provides an introduction to more advanced concepts in programming and software development. The central goal of the subject is to introduce new tools and concepts for scientific programming. For more info see https://www.uio.no/studier/emner/matnat/ifi/IN1910/h22/index.html
Undergraduate course, University of Oslo, Department of informatics, 2023
The course is a continuation of the course IN1900, and provides an introduction to more advanced concepts in programming and software development. The central goal of the subject is to introduce new tools and concepts for scientific programming. For more info see https://www.uio.no/studier/emner/matnat/ifi/IN1910/h23/index.html