Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

433
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
433

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

From PINNs to PIKANs: recent advances in physics-informed machine learning.

Machine learning for computational science and engineering·2026
Same author

Automatic selection of the best neural architecture for time series forecasting.

Nature communications·2026
Same author

MR-AIV reveals in vivo brain-wide fluid flow with physics-informed AI.

Science advances·2026
Same author

An AI-enabled tool for quantifying overlapping red blood cell sickling dynamics in microfluidic assays.

Lab on a chip·2026
Same author

A Multiscale Signaling-Biophysical Framework Reveals Mechanisms of Macrophage-Mediated RBC Clearance in Sickle Cell and Gaucher Disease.

bioRxiv : the preprint server for biology·2026
Same author

Physics-Informed Machine Learning in Biomedical Science and Engineering.

Annual review of biomedical engineering·2026

Related Experiment Video

Updated: Mar 25, 2026

Paired Cisterna Magna Nanoinjection and Laser Speckle Contrast Imaging Assay to Study Cerebral Blood Flow Regulation In Vivo
06:24

Paired Cisterna Magna Nanoinjection and Laser Speckle Contrast Imaging Assay to Study Cerebral Blood Flow Regulation In Vivo

Published on: July 8, 2025

1.2K

Multiscale modeling and simulation of brain blood flow.

Paris Perdikaris1, Leopold Grinberg2, George Em Karniadakis3

  • 1Department of Mechanical Engineering, Massachusetts Institute of Technology , Cambridge, Massachusetts 02139, USA.

Physics of Fluids (Woodbury, N.Y. : 1994)
|February 25, 2016
PubMed
Summary

This study introduces advanced multi-scale modeling for brain blood flow, enabling in silico analysis of complex vascular phenomena. The research offers insights into thrombus formation and future directions for cerebral blood flow research.

More Related Videos

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging
07:06

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

Published on: May 7, 2017

8.2K
Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
05:23

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders

Published on: May 31, 2024

934

Related Experiment Videos

Last Updated: Mar 25, 2026

Paired Cisterna Magna Nanoinjection and Laser Speckle Contrast Imaging Assay to Study Cerebral Blood Flow Regulation In Vivo
06:24

Paired Cisterna Magna Nanoinjection and Laser Speckle Contrast Imaging Assay to Study Cerebral Blood Flow Regulation In Vivo

Published on: July 8, 2025

1.2K
Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging
07:06

Simultaneous Evaluation of Cerebral Hemodynamics and Light Scattering Properties of the In Vivo Rat Brain Using Multispectral Diffuse Reflectance Imaging

Published on: May 7, 2017

8.2K
Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders
05:23

Author Spotlight: Noninvasive Cerebral Blood Flow Determination in Human Functional Brain Region for Diagnosis of Neurological Disorders

Published on: May 31, 2024

934

Area of Science:

  • Computational fluid dynamics
  • Biophysics
  • Medical imaging

Background:

  • Cerebral blood flow is crucial for brain health.
  • Understanding complex vascular phenomena requires advanced modeling techniques.
  • Existing models often struggle to capture multi-scale and multi-physics aspects of blood flow.

Purpose of the Study:

  • To provide an overview of recent advances in multi-scale modeling of brain blood flow.
  • To present a framework for in silico study of multi-scale and multi-physics phenomena in cerebral vasculature.
  • To demonstrate the framework's effectiveness in modeling thrombus formation in a patient-specific cerebral aneurysm.

Main Methods:

  • Formulation of continuum and atomistic modeling approaches.
  • Development of a consistent framework for concurrent coupling of heterogeneous numerical solvers.
  • Application of the framework to model thrombus formation in a cerebral aneurysm.

Main Results:

  • Demonstration of a unified framework for multi-scale modeling of brain blood flow.
  • Successful simulation of thrombus formation, highlighting the ability to resolve multi-scale biophysical processes.
  • Identification of challenges and future research directions in seamless integration of numerical solvers.

Conclusions:

  • Multi-scale modeling offers powerful tools for understanding brain blood flow in health and disease.
  • The proposed framework enables in silico investigation of complex vascular dynamics.
  • Further research is needed to address challenges in scalable and seamless integration of heterogeneous solvers.