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Biomodeling of Pancreatic Tumor Mass.

机译:胰腺肿瘤块的生物模型。

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摘要

Pancreatic adenocarcinoma is the fourth leading cause of cancer death in the United States. It is identified by its rapid, invasive progression with a profound resistance to treatments such as chemotherapy. Unfortunately, there is a lack of information on how to effectively inhibit and control the rapid growth of pancreatic tumors, as well as limited information for diagnostics. With current methods, pancreatic cancer will continue to prevail as a leading cause of cancer death. We propose to study the complexity of pancreatic tumors with a systematic and analytical approach. Cancer is an abnormal growth of tissue caused by uncontrolled cell division. Observing the growth of these cells would prove to have a good basis to monitor the growth of a tumor. Here we create a 3-D simulation of tumor growth through mathematical modeling, using data from pancreatic cells grown in vitro. Using 3-D models will help to understand pancreatic tumors at cellular and molecular levels.;The project aims to observe realistic growth of the tumor, accomplished from growing tumor cells on a monolayer in order to find parameters for our 3D mathematical model. This method will prove more beneficial than testing only on a monolayer cell line. Although cell death and the toxicity of drug dosage can be tested using a cell monolayer alone, it does not meet the demands of testing drug delivery in a realistic tumor environment that the mathematical model would provide. The monolayer lacks the dimensions that the drug would have to travel if it were delivered to a real in vivo tumor. A possible continuation of this project in the future could be to utilize the mathematical based approach to predict optimal therapy for the pancreatic tumor in order to develop models that can better test patient care for tumors. Computer modeling, another stepping stone through mathematical modeling, will possibly lead to testing the toxic effects of drugs on a 3-D model through computer modeling will aid in understanding the delivery of drugs throughout the tumor in vivo..
机译:胰腺腺癌是美国癌症死亡的第四大主要原因。它的快速,侵袭性发展对化学疗法等治疗产生了深远的抵抗力。不幸的是,缺乏有关如何有效抑制和控制胰腺肿瘤快速生长的信息,以及用于诊断的信息有限。用当前的方法,胰腺癌将继续占癌症死亡的主要原因。我们建议使用系统和分析的方法来研究胰腺肿瘤的复杂性。癌症是由不受控制的细胞分裂引起的组织异常生长。观察这些细胞的生长将被证明具有良好的基础来监测肿瘤的生长。在这里,我们使用体外培养的胰腺细胞的数据,通过数学建模创建了肿瘤生长的3-D模拟。使用3-D模型将有助于在细胞和分子水平上了解胰腺肿瘤。该项目旨在观察肿瘤的实际生长情况,该过程是通过在单层上生长肿瘤细胞来完成的,以便为我们的3D数学模型找到参数。与仅在单层细胞系上进行测试相比,该方法将被证明更有益。尽管可以单独使用细胞单层来测试细胞死亡和药物剂量的毒性,但它不能满足数学模型所提供的在实际肿瘤环境中测试药物递送的要求。如果将单层药物递送到真实的体内肿瘤中,其缺乏药物必须行进的尺寸。将来该项目的可能延续可能是利用基于数学的方法来预测胰腺肿瘤的最佳治疗方法,从而开发出可以更好地测试患者对肿瘤治疗的模型。计算机建模是数学建模的又一个垫脚石,可能会导致通过计算机建模测试药物对3-D模型的毒性作用,这将有助于理解体内整个肿瘤中药物的递送。

著录项

  • 作者

    Howell, Justin Lee.;

  • 作者单位

    University of Louisville.;

  • 授予单位 University of Louisville.;
  • 学科 Engineering Biomedical.
  • 学位 M.Eng.
  • 年度 2013
  • 页码 29 p.
  • 总页数 29
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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