Abstract
The success of hyperthermia treatments is dependent on thermal dose distribution. However, the three-dimensional temperature distribution remains largely unknown. Without this knowledge, the relationship between thermal dose and outcome is noisy, and therapy cannot be optimized. Accurate computations of thermal distribution can contribute to an optimized therapy. The hyperthermia modeling group in the Department of Radiotherapy, University Medical Center Utrecht devised a Discrete Vasculature [Kotte et al., Phys. Med. Biol. 41, 865-884 (1996)] model that accounts for the presence of vessel trees in the computational domain. The vessel tree geometry is tracked using magnetic resonance (MR) angiograms to a minimum diameter between 0.6 and 1 mm. However, smaller vessels (0.2-0.6 mm) are known to account for significant heat transfer. The hyperthermia group at Duke University Medical Center has proposed using perfusion maps derived from dynamic-enhanced magnetic resonance imaging to account for the tissue perfusion heterogeneity [Craciunescu et al., Int. J. Hyperthermia 17, 221-239 (2001)]. In addition, techniques for noninvasive temperature measurements have been devised to measure temperatures in vivo [Samulski et al., Int. J. Hypertherminal, 819-829 (1992)]. In this work, a patient with high-grade sarcoma has been retrospectively modeled to determine the temperature distribution achieved during a hyperthermia treatment. Available for this model were MR depicted geometry, angiograms, perfusion maps, as necessary for accurate thermal modeling, as well as MR thermometry data for validation purposes. The vasculature assembly through modifiable potential program [Van Leeuwen et al., IEEE Trans. Biomed. Eng. 45, 596-604 (1998)] was used in order to incorporate the traceable large vessels. Temperature simulations were made using different approaches to describe perfusion. The simulated cases were the bioheat equation with constant perfusion rates per tissue type, perfusion maps alone, tracked vessel tree and perfusion maps, and generated vessel tree. The results were compared with MR thermometry data for a single patient data set, concluding that a combination between large traceable vessels and perfusion map yields the best results for this particular patient. The technique has to be repeated on several patients, first with the same type of malignancy, and after that, on patients having malignancies at other different sites.
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