Henrik Finsberg

Henrik Finsberg

Senior Research Engineer @ Simula Research Laboratory

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

projects

Advanced in silico cardiovascular modeling in hemorrhagic shock

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

IdentiPhy

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.

SimcardioTest

Simulation of Cardiac Devices and Drugs for In-Silico Testing and Certification (SimCardioTest)

publications

Wavelet Techniques in Medical Imaging: Classification of UltraSound Images using the Windowed Scattering Transform

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

High‐resolution data assimilation of cardiac mechanics applied to a dyssynchronous ventricle

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.

http://dx.doi.org/10.1002/cnm.2863

Estimating cardiac contraction through high resolution data assimilation of a personalized mechanical model

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.

http://dx.doi.org/10.1016/j.jocs.2017.07.013

Patient-specific computational modeling of cardiac mechanics

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

Efficient estimation of personalized biventricular mechanical function employing gradient‐based optimization

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.

http://dx.doi.org/10.1002/cnm.2982

In vivo estimation of elastic heterogeneity in an infarcted human heart

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.

http://dx.doi.org/10.1007/s10237-018-1028-5

Computational quantification of patient-specific changes in ventricular dynamics associated with pulmonary hypertension

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

Improved computational identification of drug response using optical measurements of human stem cell derived cardiomyocytes in microphysiological systems

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

http://dx.doi.org/10.3389/fphar.2019.01648

In vitro safety “clinical trial” of the cardiac liability of hydroxychloroquine and azithromycin as COVID19 polytherapy

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

Heart muscle microphysiological system for cardiac liability prediction of repurposed COVID-19 therapeutics

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.

http://dx.doi.org/10.3389/fphar.2021.684252

Validating the Arrhythmogenic Potential of High-, Intermediate-, and Low-Risk Drugs in a Human-Induced Pluripotent Stem Cell-Derived Cardiac Microphysiological System

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.

http://dx.doi.org/10.1021/acsptsci.2c00088

Omecamtiv Mecarbil Improves Contraction Behaviour in a 3D Electromechanical Tissue Model of Heart Failure

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.

http://dx.doi.org/10.22489/cinc.2022.033

A cell-based framework for modeling cardiac mechanics

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

simcardems: A FEniCS-based cardiac electro-mechanics solver

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.

http://dx.doi.org/10.21105/joss.04753

Regional Left Ventricular Fiber Stress Analysis for Cardiac Resynchronization Therapy Response

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.

http://dx.doi.org/10.22541/au.160865713.30751611/v1

SMART: Spatial Modeling Algorithms for Reaction and Transport

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.

https://joss.theoj.org/papers/10.21105/joss.05580

Published in , 1900

A computational study of right ventricular mechanics in a rat model of pulmonary arterial hypertension

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

softwares

talks

Seminar: Elevating Scientific Computing at Simula: Best Practices in Modern Software Development

Published:

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.

From the Law of Laplace to FEM-based stress estimation

Published:

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.

A beginner’s guide to cardiac modelling

Published:

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.

A beginner’s guide to cardiac modelling

Published:

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.

teaching