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相关概念视频

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

110
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...
110
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

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

144
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...
144
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

101
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
101
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

286
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
286
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

712
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

149
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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相关实验视频

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Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
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从标准的托夫特模型中快速计算生理参数的解代算法.

Shu Chang1, Xiaobing Fan2, Ying Ma1

  • 1College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China.

Medical physics
|August 14, 2025
PubMed
概括

一种新的预测校正方法 (PCM) 从3D动态对比增强MRI (DCE-MRI) 数据快速计算药理学参数. 这种更快的方法保持了与标准托夫特模型 (STM) 相似的准确性,有助于癌症诊断.

关键词:
动态对比增强磁共振成像 (DCE-MRI) 技术药物动力学模型 药物动力学模型生理学参数 生理学参数标准的托夫特斯模型模型

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科学领域:

  • 医疗成像医学成像
  • 生物物理学的生物物理.
  • 药理动力学 药理动力学

背景情况:

  • 标准Tofts模型 (STM) 对于分析动态对比增强磁共振成像 (DCE-MRI) 数据至关重要.
  • 使用STM对3DDCE-MRI数据进行像素对像素的分析是计算密集且耗时的.

研究的目的:

  • 开发一个快速的,代算法,预测校正方法 (PCM),用于在STM框架内计算生理参数.
  • 显著减少DCE-MRI数据分析所需的时间.

主要方法:

  • PCM通过使用对比剂度-时间曲线的早期和晚期部分来代地估计体积转移常数 (Ktrans) 和细胞外体积分数 (ve),避免完整的曲线拟合.
  • 验证使用定量成像生物标志物联盟 (QIBA) 数据进行,然后应用于公共前列腺和乳腺DCE-MRI数据集.
  • 通过将PCM结果与传统的STM和重复扫描之间进行比较来评估可重复性.

主要成果:

  • 该PCM与QIBA数据的传统STM表现出极好的一致性.
  • 对于临床数据集,PCM显示Ktrans和ve计算中的小百分比错误 (<10%) 与STM和扫描之间相比.
  • 与STM相比,PCM实现了每像素速度的十倍增长,具有类似的重复性.

结论:

  • PCM显著加快了Ktrans和ve的计算,达到接近传统STM的准确性.
  • 这种使用PCM的3D DCE-MRI数据快速计算生理参数,可以帮助癌症诊断.