Paper
14 April 2005 Design of optimal hyperthermia protocols for prostate cancer by controlling HSP expression through computer modeling (Invited Paper)
Marissa Nichole Rylander, Yusheng Feng, Kenneth Diller, J. Bass
Author Affiliations +
Abstract
Heat shock proteins (HSP) are critical components of a complex defense mechanism essential for preserving cell survival under adverse environmental conditions. It is inevitable that hyperthermia will enhance tumor tissue viability, due to HSP expression in regions where temperatures are insufficient to coagulate proteins, and would likely increase the probability of cancer recurrence. Although hyperthermia therapy is commonly used in conjunction with radiotherapy, chemotherapy, and gene therapy to increase therapeutic effectiveness, the efficacy of these therapies can be substantially hindered due to HSP expression when hyperthermia is applied prior to these procedures. Therefore, in planning hyperthermia protocols, prediction of the HSP response of the tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of overall tissue response. In this paper, we present a highly accurate, adaptive, finite element tumor model capable of predicting the HSP expression distribution and tissue damage region based on measured cellular data when hyperthermia protocols are specified. Cubic spline representations of HSP27 and HSP70, and Arrhenius damage models were integrated into the finite element model to enable prediction of the HSP expression and damage distribution in the tissue following laser heating. Application of the model can enable optimized treatment planning by controlling of the tissue response to therapy based on accurate prediction of the HSP expression and cell damage distribution.
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Marissa Nichole Rylander, Yusheng Feng, Kenneth Diller, and J. Bass "Design of optimal hyperthermia protocols for prostate cancer by controlling HSP expression through computer modeling (Invited Paper)", Proc. SPIE 5698, Thermal Treatment of Tissue: Energy Delivery and Assessment III, (14 April 2005); https://doi.org/10.1117/12.584678
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KEYWORDS
Tumors

Proteins

Data modeling

Tissues

Prostate cancer

Prostate

Finite element methods

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