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Clinical use of the hyperthermia treatment planning system HyperPlan to predict effectiveness and toxicity

Item Type:Article
Title:Clinical use of the hyperthermia treatment planning system HyperPlan to predict effectiveness and toxicity
Creators Name:Sreenivasa, G. and Gellermann, J. and Rau, B. and Nadobny, J. and Schlag, P.M. and Deuflhard, P. and Felix, R. and Wust, P.
Abstract:PURPOSE: The main aim is to prove the clinical practicability of the hyperthermia treatment planning system HyperPlan on a beta-test level. Data and observations obtained from clinical hyperthermia are compared with the numeric methods FE (finite element) and FDTD (finite difference time domain), respectively. METHODS AND MATERIALS: The planning system HyperPlan is built on top of the modular, object-oriented platform for visualization and model generation AMIRA. This system already contains powerful algorithms for image processing, geometric modeling, and three-dimensional graphics display. A number of hyperthermia-specific modules are provided, enabling the creation of three-dimensional tetrahedral patient models suitable for treatment planning. Two numeric methods, FE and FDTD, are implemented in HyperPlan for solving Maxwell's equations. Both methods base their calculations on segmented (contour based) CT or MR image data. A tetrahedral grid is generated from the segmented tissue boundaries, consisting of approximately 80,000 tetrahedrons per patient. The FE method necessitates, primarily, this tetrahedral grid for the calculation of the E-field. The FDTD method, on the other hand, calculates the E-field on a cubical grid, but also requires a tetrahedral grid for correction at electrical interfaces. In both methods, temperature distributions are calculated on the tetrahedral grid by solving the bioheat transfer equation with the FE method. Segmentation, grid generation, E-field, and temperature calculation can be carried out in clinical practice at an acceptable time expenditure of about 1-2 days. RESULTS: All 30 patients we analyzed with cervical, rectal, and prostate carcinoma exhibit a good correlation between the model calculations and the attained clinical data regarding acute toxicity (hot spots), prediction of easy-to-heat or difficult-to-heat patients, and the dependency on various other individual parameters. We could show sufficient agreement between the calculations and measurements for power density (specific absorption rate) within the range of assessed precision. Tumor temperatures can only be estimated, because of the rather variable perfusion conditions. The results of the FE and FDTD methods are comparable, although slight differences exist resulting from the differences in the underlying models. There are also statistically provable differences among the tumor entities regarding the attained specific absorption rate, temperatures, and volume loads in normal tissue. However, gross fluctuations exist from patient to patient. CONCLUSION: The hyperthermia planning system HyperPlan could be validated for a number of the 30 patients. Further improvements in the implemented models, FE and FDTD, are required. Even at its present state of development, hyperthermia planning for regional hyperthermia delivers valuable information, not only for clinical practice, but also for further technologic improvements.
Keywords:Hyperthermia Treatment Planning, Regional Hyperthermia, Patient Models, Pelvic Tumors
Source:International Journal of Radiation Oncology, Biology, Physics
Publisher:Elsevier (U.S.A.)
Page Range:407-419
Date:1 February 2003
Official Publication:https://doi.org/10.1016/S0360-3016(02)04144-5
PubMed:View item in PubMed

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