Abstract
Thermal properties of biological tissues play a critical role in the study of tumor angiogenesis and the design and monitoring of thermal therapies. To map thermal parameters noninvasively, we propose temperature-change-based thermal tomography (TTT) that relies on relative temperature mapping using magnetic resonance imaging (MRI). Our approach is unique in two aspects: (1) the steady-state body temperature in thermal equilibrium is not restricted to be spatially invariant, and (2) absolute temperature mapping is not required. These two features are physiologically realistic and technically convenient. Our numerical simulation indicates that a (9 mm)3 tumor inside a breast phantom can be reliably depicted, assuming moderate temperature mapping accuracy of 0.5°C.
Highlights
Traditional thermal tomography is based on using an infrared camera to measure the surface temperature of a tissue and solving the inverse heat transfer problem to reconstruct the interior tissue thermal parameters [1]
Since 2002, a few papers [2,3,4] have discussed the possibility of using magnetic resonance imaging (MRI) to obtain the temperature distribution within the tissue and reconstruct the temperature coefficients therein
Most of the MRI-based temperature-mapping techniques, such as those based on proton resonance frequency (PRF), can only provide relative-temperature-change [6]
Summary
Thermal properties of biological tissues play a critical role in the study of tumor angiogenesis and the design and monitoring of thermal therapies. Clinical studies have suggested that the local skin temperature over a breast tumor can increase significantly (by 1–3◦C) over the normal breast skin temperature [7] This effect is often ignored in current analyses, which assume that the steady-state temperature within the ROI is uniform. To address these deficiencies, we formulate a temperature-change-based thermal tomography (TTT) method and demonstrate that TTT can potentially lead to new and noninvasive medical modalities for breast cancer imaging and other important biomedical applications. Performing an additional set of MRI temperature measurements with a different initial temperature, we have 2N linear equations and can uniquely determine the values of α1 and α2 over the entire numerical grid Such a direct approach for TTT is significantly simpler than other thermal reconstruction methods in literature [2–. The thermal diffusivity α1 is 0.13 mm2 · s−1 throughout
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