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Related Concept Videos

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

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

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...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Three-Compartment Open Model01:06

Three-Compartment Open Model

The three-compartment open model is a pharmacokinetic model used to describe the distribution and elimination of drugs following extravascular administration. It comprises a central compartment representing the plasma and two peripheral compartments. The highly perfused peripheral compartment represents organs and tissues with a rich blood supply, such as the liver, kidneys, and lungs. The scarcely perfused peripheral compartment represents tissues with lower blood supply, such as adipose...
Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.

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Updated: Jun 18, 2026

A Computational Modeling Approach to Investigate the Influence of Hyperthermia on the Tumor Microenvironment
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A stochastic model for propagation through tissue.

Bernard Lacaze1

  • 1Telecommun. Spatiales et Aeronautiques (TeSA), Toulouse, France. Bernard.Lacaze@tesa.prd.fr

IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
|November 28, 2009
PubMed
Summary

This study introduces a new model for ultrasound wave attenuation in biological tissues, using a Cauchy distribution to explain energy loss and signal deterioration, improving upon existing models.

Area of Science:

  • Acoustics
  • Biophysics
  • Signal Processing

Background:

  • Ultrasonic wave attenuation is typically linear with frequency in biological applications.
  • In contrast, atmospheric and water propagation exhibit quadratic frequency-dependent attenuation.
  • Previous models utilized Gaussian propagation duration to explain attenuation in non-biological media.

Purpose of the Study:

  • To develop a novel model for ultrasonic wave propagation and attenuation in biological tissues.
  • To account for signal deterioration and energy loss during ultrasound transmission through tissue.
  • To provide a more accurate representation of ultrasound behavior in biomedical contexts.

Main Methods:

  • Defined an equivalent random propagation duration using a Cauchy distribution for ultrasound in tissue.

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  • Incorporated an unobserved noise component to model signal deterioration.
  • Analyzed the model's agreement with observed phenomena like mode downshift in narrowband signals.

    • Main Results:

    • The Cauchy distribution model effectively describes ultrasound attenuation in biological tissues.
    • The model quantifies energy loss by representing propagation duration as a random variable.
    • The proposed model aligns with the mode downshift phenomenon observed in narrowband ultrasound signals.

    Conclusions:

    • The Cauchy distribution provides a suitable framework for modeling ultrasound attenuation in biological tissues.
    • The model offers insights into signal deterioration mechanisms.
    • This approach enhances the understanding of ultrasonic wave behavior in biomedical applications.