Nonlinear Modelling of Heat Transfer in Regional Hyperthermia

Responsible:

Bodo Erdmann, Jens Lang, Martin Seebass

Cooperation:

J. Gellermann, P. Wust,
Rudolf-Virchow-Hospital, Berlin

Literature:

B. Erdmann, J. Lang, M. Seebass, Adaptive Solutions of Nonlinear Parabolic Equations with Application to Hyperthermia Treatments, in Graham de Vahl Davis, Eddie Leonardi (eds.), CHT'97: Advances in Computational Heat Transfer, Proc. Int. Symp. on Advances in Comp. Heat Transfer (1997), pp. 103-110.

B. Erdmann, J. Lang, M. Seebass, Optimization of Temperature Distributions for Regional Hyperthermia based on a Nonlinear Heat Transfer Model, in Ken Diller (ed.), Biotransport: Heat and Mass Transfer in Living Systems, Annals of the New York Academy of Sciences, Vol. 858 (1998), pp. 36-46.

J. Lang, B. Erdmann, M. Seebass, The Impact of a Nonlinear Heat Transfer Model for Temperature Control in Regional Hyperthermia, IEEE Transactions on Biomedical Engineering, Vol. 46, No. 9 (1999), pp. 1129-1138.

Links:

This activity is part of the development of an medical planning system for regional hyperthermia therapy

Hyperthermia, i.e., heating tissue to 42 ^oC, is a method of cancer therapy. It is normally applied as an additive therapy to enhance the effect of conventional radio- or chemotherapy. The standard way to produce local heating in the human body is the use of electromagnetic waves. We are mainly interested in regional hyperthermia of deep-seated tumors. For this type of treatment usually a phased array of antennas surrounding the patient is used, see Figure 1. The distribution of absorbed power within the patient's body can be steered by selecting the amplitudes and phases of the antennas' driving voltages. The space between the body and the antennas is filled by a so-called water bolus to avoid excessive heating of the skin.
patient

Patient model (torso) and hyperthermia applicator. The patient is surrounded by eight antennas emitting radio waves. A water-filled bolus is placed between patient and antennas.
Studies that predict temperatures in tissue models usually assume a constant-rate blood perfusion within each tissue. However, several experiments have shown that the response of vasculature in tissues to heat stress is strongly temperature-dependent (Song et al., 1984). So the main intention of this work was to develop new nonlinear heat transfer models in order to reflect this important observation, see Figure 2.

Nonlinear models of temperature-dependent blood perfusion for muscle tissue, fat tissue, and tumor.
There are significant qualitative differences between the temperature distribution predicted by the standard (linear) and the nonlinear heat transfer model. Generally, the self-regulation of healthy tissue is better reflected by the nonlinear model which is now used in practical computations.