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首页> 外文学位 >The diffusion-drift algorithm for modeling the biopotential signals of breast cancer tumors.
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The diffusion-drift algorithm for modeling the biopotential signals of breast cancer tumors.

机译：用于模拟乳腺癌肿瘤生物潜能信号的扩散漂移算法。

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摘要

A two dimensional model is developed to calculate the electric current densities and the biopotentials generated from single and multiple breast cancerous cells at different cell division stages. Three cell division stages are considered: depolarization which occurs at the beginning of the Gap 1 (G1) stage; hyperpolarization which occurs between the G1 and Synthesis (S) stage; and quiescence where the cell neither depolarizes nor hyperpolarizes. The goal is to understand the electrophysiology of the breast cancer cell line termed Michigan Cancer Foundation-7 (MCF-7). The proposed model is based on the semiconductor diffusion--drift analysis. For a single MCF-7 cell, the shorter the duration of the G1/S transition, and the higher the diffusivity and mobility at the cell boundary, the higher the magnitude of the generated electric signals.;The model is extended to include multiple MCF-7 cells. Nonuniform finite-difference discretization is implemented to accommodate the contrast in size between the intercellular spacing and the cell dimension. The results show that the biopotentials increase proportionally with the number of cells, especially when all cells are in the hyperpolarization stage.;In order to increase the number of cells, the diffusion-drift algorithm is parallelized using the Message Passing Interface (MPI) technique. The computational bottleneck of the model involves the solutions of systems of equations, based on the Nernst-Plank, the Poisson and the Continuity equations, to calculate the biopotentials and the ion concentrations. The Portable, Extensible Toolkit for Scientific Computation library is adopted herein. A maximum overall speedup of 15 is achieved using 56 processors on the Star of Arkansas supercomputer.;As known, early stage tumor growth, cancerous cells are prone to forces and interactions which generate highly complex tumor shapes. The generated electric signals of the most common tumor shape patterns, i.e. Papillary, Compact, and Comedo, are investigated in this work. The highest biopotential signal is observed from the compact tumor while the lowest biopotential signal is observed from the papillary pattern. Interestingly, the spatial distribution of the biopotential signals shows a shift in the maximum biopotential amplitude. These observations can have important implications when using the biopotential signals for breast cancer detection.
机译：建立了二维模型，以计算在不同细胞分裂阶段从单个和多个乳腺癌细胞产生的电流密度和生物电势。考虑了三个细胞分裂阶段：在Gap 1（G1）阶段开始时发生的去极化；在G1和合成（S）阶段之间发生超极化；细胞不去极化也不超极化的静止状态。目的是了解被称为密歇根州癌症基金会7（MCF-7）的乳腺癌细胞系的电生理。建议的模型基于半导体扩散-漂移分析。对于单个MCF-7电池，G1 / S跃迁的持续时间越短，并且在细胞边界处的扩散率和迁移率越高，则生成的电信号的强度就越高。;该模型被扩展为包括多个MCF -7个细胞。实现非均匀有限差分离散化以适应细胞间距和细胞尺寸之间的大小差异。结果表明，生物电势随细胞数成比例增加，特别是当所有细胞处于超极化阶段时。为了增加细胞数，使用消息传递接口（MPI）技术并行化了扩散漂移算法。 。该模型的计算瓶颈涉及基于能斯特-普朗克方程，泊松方程和连续性方程的方程组的解，以计算生物势和离子浓度。本文采用了用于科学计算的可移植，可扩展工具包。使用阿肯色州之星超级计算机上的56个处理器，最高总加速速度为15。众所周知，早期肿瘤生长，癌细胞易于受力和相互作用，产生高度复杂的肿瘤形状。在这项工作中，研究了最常见的肿瘤形状模式（即乳头状，紧密型和粉刺状）的电信号。从致密肿瘤观察到最高的生物电势信号，而从乳头状模式观察到最低的生物电势信号。有趣的是，生物电势信号的空间分布表明最大生物电势振幅发生了变化。当使用生物电势信号进行乳腺癌检测时，这些观察结果可能具有重要意义。

著录项

  • 作者

    Hassan, Ahmed.;

  • 作者单位

    University of Arkansas.;

  • 授予单位 University of Arkansas.;
  • 学科 Engineering Biomedical.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 169 p.
  • 总页数 169
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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