Multiscale Simulations of Tissue and Cell deformations

Cells of the musculoskeletal system are known to have a biological response to deformation. Deformations, when abnormal in magnitude, duration, and/or frequency content, can lead to cell damage and possible disruption in homeostasis of the extracellular matrix. These mechanisms can be studied in an isolated fashion but connecting mechanical cellular response to organ level mechanics and human movement requires a multiscale approach. At the organ level, physicians perform surgical procedures, investigators try to understand risk of injury, and clinicians prescribe preventive and therapeutic interventions. Many of these operations are aimed at management and prevention of cell damage, and to associate joint level mechanical markers of failure to cell level failure mechanisms. Through human movement, one explores neuromuscular control mechanisms and the influence of physical activity on musculoskeletal tissue properties. At a lower level, mechanical sensation of cell deformations regulate movement control. Physical rehabilitation and exercise regimens are prescribed to promote tissue healing and/or strengthening through cellular regeneration. The knowledge of the mechanical pathway, through which the body level loads are distributed between organs, then within the tissues and further along the extracellular matrix and the cells, is critical for the success of various interventions. However, this information is not established. The goal of this research program is to portray that prediction of cell deformations from loads acting on the human body, therefore a clear depiction of the mechanical pathway, is possible, if a multiscale simulation approach is used. To realize this goal, multiresolution models of the knee joint, representative of joint, tissue and cell structure and mechanics are under development. The knee endures high rates of traumatic injury to its soft tissue structures and it is predominantly affected by osteoarthritis, chronically induced by abnormalities in mechanical loading or how it is transferred to the cartilage. Through multiscale mechanical coupling of these models, a map of cellular deformation in cartilage, ligaments and menisci under a variety of tibiofemoral joint loads can be obtained. In future, this platform has to potential to establish the relationship between the structural and loading state of the knee and chondrocyte stresses to explore potential mechanisms of cartilage degeneration. For more details, please refer to

Multiscale simulations to predict cell deformations from joint loads can be conducted through concurrent analysis, during which the microstructural response is coupled to macroscopic mechanical behavior on-the-fly.

Micromechanical models of the cells and extracellular matrix, incorporating the geometry and spatial distribution of cells and the mechanical properties of the microstructural components can predict cell deformations.

Multidomain Coupling of Musculoskeletal Movements and Tissue Deformations

In computational biomechanics, there are two well-developed but separate modeling domains: multibody dynamics for body movements, and finite element modeling for tissue deformations. Many clinical problems, however, span both domains. Whole body anatomy, mass distribution, and gait pattern are not typically represented in finite element models, yet these are important real-world factors that affect tissue stresses in the musculoskeletal system, which may contribute to clinical problems such as osteoarthritis and diabetic foot ulceration. Movement simulations, on the other hand, lack a representation of tissue deformations, which are indicators of mechanically induced pain and other sensory feedback (or the lack thereof) and will cause observable changes in gait. Exploration of these neuromusculoskeletal integrative mechanisms can only be accomplished by multidomain simulations. Current techniques for multidomain modeling are insufficient because forward dynamic movement simulations typically proceed along a sequence of many small steps in time. Finite element models are too slow to allow a solution at each of these steps. One may painstakingly produce a single movement simulation, but not the thousands of simulations that are required for predictive movement optimizations that are the state of the art in musculoskeletal dynamics. This has become a bottleneck for our own research, as well as for others. To resolve this issue, we have implemented a generic, self-refining, surrogate modeling scheme, which reproduces an underlying physics-based finite element model within a given error tolerance, but at a far lower computational cost. The self-refining feature is the key to reproduce the multi-dimensional input-output space of a typical finite element model of a joint or joint complex. We recently demonstrated the utility of these tools by connecting a finite element model of the foot to a complete musculoskeletal gait simulation, which tested the hypothesis that internal foot strains can be lowered by selecting a specific optimal muscle coordination pattern during gait. For more details please refer to

Modeling approaches in biomechanics commonly utilize two distinctive domains: musculoskeletal movement simulations and finite element analysis. Concurrent coupling can help the exploration of biomechanical function relying on feedback mechanisms across these domains.

Multidomain simulations, coupling musculoskeletal movements with tissue deformations is possible, i.e. foot stresses can be calculated simultaneously during solving for maximal height jumping using a lower extremity musculoskeletal model.

Biomechanics of Synovial Joints

Computational models of the synovial joint, in particular of the knee, are important tools to explore joint and tissue function, to understand injury mechanisms, to study pathological joint mechanics and to evaluate surgical performance. Our aim is to develop a knee joint model to describe and predict the passive kinematics/kinetics of the knee, and to provide an initial platform to investigate more detailed mechanics of joint substructures following modifications to address specific research questions. The development and related dissemination is conducted in an open fashion to promote reusability and crowd-sourcing of model improvement. Our short term goal is to provide an accessible model to the research community, supported by joint level mechanical testing. In the long term, we are interested in expanding our modeling and experimental investigations to explore biomechanical function of the capsule and the synovial fluid for joint stabilization and cartilage loading. While our current focus is on the knee, similar procedures can be applied for other synovial joints. For more details, please refer to

Simulation of passive knee flexion using a finite element representation of the tibiofemoral joint; von Mises stress distribution within the menisci can be observed on the left.

Musculoskeletal Biomechanics in Aging and Osteoarthritis

Cartilage endures continuous mechanical loading during activities of daily living. Its degeneration is a major cause of loss of quality of life as seen in aging populations and in osteoarthritis. Cartilage stresses are mechanical markers of its healthy biological response and establish the failure risk for this tissue structure. Aging changes neuromuscular control strategies, musculoskeletal properties, and anatomical reconstruction of the tissues. As a result, the loads at the knee joint and their distribution to joint's tissue structures are different. The cartilage's and chondrocytes' mechanical environment therefore changes, which may initiate age related tissue degeneration. Such damage can be caused by increased mechanical stress or counter-intuitively, it may be associated with decreased loading, which may influence the signal transduction that is responsible from tissue maintenance. Unfortunately, how age related adaptations alter the actual stress levels in the cartilage and the cells within is not known. Some of these, when investigated in an isolated fashion, may provide an intuitive understanding of how cartilage loading may change by age. Nonetheless, their combined and potentially offsetting effects in real life conditions were not quantified. This information has significant value as age related markers of early cartilage degeneration can be established. Our long term goal is to provide the capacity to identify subject-specific cartilage and chondrocyte loading during daily activities. For this purpose, a multiscale computer modeling and simulation platform, driven by subject-specific data, is planned as a potential clinical tool. Predictive nature of this platform will also facilitate design of management strategies for subject populations at risk of cartilage degeneration and chondrocyte damage.

Comprehensive data collection schemes supported by subject-specific musculoskeletal model of the lower extremity and finite element representation of the knee joint are likely to quantify the influence of neuromuscular, musculoskeletal and movement related changes on cartilage stress in aging and osteoarthritic populations.

Aging effects the biomechanical function of the knee joint and cartilage over the full spatial spectrum. Multiscale simulations can identify the individual influence of age related mechanical changes on chondrocyte and extracellular deformations.

Simulation-Based Medicine

Our translational research program to support simulation based medicine is conducted through the operations of Computational Biomodeling (CoBi) Core. For more details, please refer to

Snehal K. Chokhandre
Snehal K. Chokhandre
Principal Research Engineer
Phone:(216) 445-3555
Sean  Doherty
Sean Doherty
Research Engineer
Phone:(216) 444-1256
Ellen  Klonowski
Ellen Klonowski
Research Engineer
Phone:(216) 444-5857
Benjamin   Landis
Benjamin Landis
Senior Research Engineer
Phone:(216) 444-1256

View publications for Ahmet Erdemir, Ph.D.

Noble C, Carlson KD, Neumann E, Dragomir-Daescu D, Erdemir A, Lerman A, Young M. Patient specific characterization of artery and plaque material properties in peripheral artery disease. J Mech Behav Biomed Mater. 2020 Jan;101:103453. doi: 10.1016/j.jmbbm.2019.103453. Epub 2019 Sep 27.

Schimmoeller T, Neumann EE, Nagle TF, Erdemir A. Reference tool kinematics-kinetics and tissue surface strain data during fundamental surgical acts.  Sci Data. 2020 Jan 15;7(1):21. doi: 10.1038/s41597-020-0359-0. PMCID: PMC6962378

Schimmoeller T, Neumann EE, Owings TM, Nagle TF, Colbrunn RW, Landis B, Jelovsek JE, Hing T, Ku JP, Erdemir A. Reference data on in vitro anatomy and indentation response of tissue layers of musculoskeletal extremities. Sci Data. 2020 Jan 15;7(1):20. doi: 10.1038/s41597-020-0358-1. PMCID: PMC6962198

Sibole, S. C. and Erdemir, A. (2012) Chondrocyte deformations as a function of tibiofemoral joint loading predicted by a generalized high-throughput pipeline of multi-scale simulations, PLoS ONE, 7, e37538. PMCID: PMC3359292

Halloran, J. P., van Donkelaar, C. C., Sibole, S., van Turnhout, M. C., Oomens, C. W. J., Weiss, J., Guilak, F. and Erdemir, A. (2012) Multiscale mechanics of cartilage: potentials and challenges of coupling musculoskeletal, joint, and microscale computational models, Annals of Biomedical Engineering, 40, 2456-2474. PMCID: PMC3469753

Young, M., Erdemir, A., Stucke, S., Klatte, R., Davis, B. and Navia, J. (2012) Simulation based design and evaluation of a transcatheter mitral heart valve frame, Journal of Medical Devices, 6, 031005. PMCID: PMC3557846

Erdemir, A., Guess, T. M., Halloran, J. P., Tadepalli, S. C. and Morrison, T. M. (2012) Considerations for reporting finite element analysis studies in biomechanics, Journal of Biomechanics, 45, 625-633. PMCID: PMC3278509

Predicting Cell Deformation from Body Level Mechanical Loads

  • R01EB009643 (PI: Erdemir) - 08/01/2009 - 07/31/2013
  • National Institute of Biomedical Imaging and Bioengineering
    National Institutes of Health

Efficient Methods for Multi-Domain Biomechanical Simulations

  • R01EB006735 (PI: van den Bogert; Co-I: Erdemir) - 09/11/2006 - 08/31/2009
  • National Institute of Biomedical Imaging and Bioengineering
    National Institutes of Health
images/nibib_logo.gif images/nih_logo.jpg

Faculty Start-up Funds

  • 06/01/2010 – 05/31/2013
  • Department of Biomedical Engineering Lerner Research Institute

For a detailed overview of our past, current and prospective research program, please refer to research_overview.pdf.

For data/software/models/reprints relevant to our research program, please check project-specific websites:

For information on our activities in the multiscale modeling community, please check:

Ahmet  Erdemir,  Ph.D.

Ahmet Erdemir, Ph.D.

Associate Staff

Lerner Research Institute, 9500 Euclid Avenue, Cleveland, Ohio 44195
Location: ND2-27

Phone: (216) 445-9523
Fax: (216) 444-9198