Multiscale modelling of hematologic disorders

  • Dmitry Fedosov
  • Igor Pivkin
  • Wenxiao Pan
  • Ming Dao
  • Bruce Caswell
  • George E. Karniadakis
Part of the MS&A — Modeling, Simulation and Applications book series (MS&A, volume 5)


Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain per-fusion, as in the case of cerebral malaria. Modelling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangian method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behaviour of whole healthy blood and compare with experimental results. The same procedure is applied to modelling malaria, and results for infected single RBCs and whole blood are presented.


Wall Shear Stress Dissipative Particle Dynamics High Wall Shear Stress Membrane Viscosity Dissipative Particle Dynamics Simulation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by NIH and NSF. Simulations were performed at the NSF supercomputing center NICS, at the BG/P at ANL via an INCITE DOE award, and at the Jülich supercomputing center.


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Copyright information

© Springer-Verlag Italia 2012

Authors and Affiliations

  • Dmitry Fedosov
    • 1
  • Igor Pivkin
    • 2
  • Wenxiao Pan
    • 3
  • Ming Dao
    • 2
  • Bruce Caswell
    • 4
  • George E. Karniadakis
    • 4
  1. 1.Forschungszentrum JülichJülichGermany
  2. 2.Massachusetts Institute of TechnologyCambridgeUSA
  3. 3.Pacific Northwest National LaboratoryRichlandUSA
  4. 4.Brown UniversityProvidenceUSA

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