0
Research Papers

Effects of Nonuniform Tissue Properties on Temperature Prediction in Magnetic Nanohyperthermia

[+] Author and Article Information
Qian Wang

Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, P. R. China

Zhong-Shan Deng

Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. China

Jing Liu1

Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, P. R. China; Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Beijing 100190, P. R. Chinajliubme@tsinghua.edu.cn

1

Corresponding author.

J. Nanotechnol. Eng. Med 2(2), 021012 (May 17, 2011) (7 pages) doi:10.1115/1.4003563 History: Received January 18, 2011; Revised January 27, 2011; Published May 17, 2011; Online May 17, 2011

In tumor hyperthermia, effectively planning in advance and thus controlling in situ the heating dosage within the target region are rather critical for the success of a therapy. Many studies have simulated the temperature distribution during hyperthermia. However, most of them are based on fixed and known heat source distributions, which are generally very complex to compute. Besides, there is little information concerned the numerical analysis of temperature during magnetic hyperthermia loading with magnetic nanoparticles (MNPs), which has its specific heat source distribution features. Particularly, the parameters for different human tissues varied very much, which will cause a serious impact on the heat source and temperature distribution. This paper is aimed at investigating the effects of nonuniform tissue properties to the temperature prediction in magnetic nanohyperthermia and other possible effect factors including external EM field, MNP properties, tumor size and depth, surface cooling conditions, etc. It was found that the spatial heat source generated in the nonuniform model appears smaller than that in the uniform model. This is mainly resulted from the energy reflection when transmitting from fat to tumor and muscle under the same condition, while the temperature is higher on account of overall contribution of different parameters including tissue thermal conductivity, blood perfusion, density, heat capacity, and metabolic heat production rate, which also affect the temperature distribution apart from the heat source. Controlling the properties of the external EM field, MNPs and cooling water can acquire different temperature distributions. Tumors with different depths and sizes need specific plannings, which require as accurate as possible temperature prediction. The nonuniform model can be further improved to be applied in magnetic nanohyperthermia treatment planning and thus help optimize the surgical procedures.

FIGURES IN THIS ARTICLE
<>
Copyright © 2011 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Figure 1

Three-layer nonuniform model for magnetic nanohyperthermia

Grahic Jump Location
Figure 2

The convergence of the algorithm

Grahic Jump Location
Figure 3

Steady-state heat source distribution at section z=0.04 m for (a) uniform and (b) nonuniform models

Grahic Jump Location
Figure 11

Comparisons between ((a) and (c)) uniform and ((b) and (d)) nonuniform models about ((a) and (b)) heat source and ((c) and (d)) temperature distribution under different tumor sizes

Grahic Jump Location
Figure 12

Comparisons between ((a) and (c)) uniform and ((b) and (d)) nonuniform models about ((a) and (b)) heat source and ((c) and (d)) temperature distribution under different tumor depths

Grahic Jump Location
Figure 13

Comparisons between (a) uniform and (b) nonuniform models about temperature distribution along the central axis for cooling water with different temperatures

Grahic Jump Location
Figure 10

Comparisons between (a) uniform and (b) nonuniform models about temperature distribution along the central axis under different radii

Grahic Jump Location
Figure 9

Comparisons between (a) uniform and (b) nonuniform models about temperature distribution along the central axis under different concentrations

Grahic Jump Location
Figure 7

Comparisons between uniform (solid line) and nonuniform (dashed line) models about transient temperature distribution: (a) spatial distribution along the central axis for different times and (b) transient temperature distribution at three specific positions

Grahic Jump Location
Figure 6

Transient temperature distribution at section z=0.04 m for (a) uniform and (b) nonuniform models

Grahic Jump Location
Figure 5

Comparisons between uniform (solid line) and nonuniform (dashed line) models about (a) steady-state heat source and (b) temperature distribution along the central axis

Grahic Jump Location
Figure 8

Comparisons between (a) uniform and (b) nonuniform models about temperature distribution along the central axis under different frequencies

Grahic Jump Location
Figure 4

Steady-state temperature distribution at section z=0.04 m for (a) uniform and (b) nonuniform models

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In