Abstract #0916

Extremely Rapid Temperature Predictions Considering Numerous Physiological Phenomena

Giuseppe Carluccio^1,2 and Christopher Michael Collins^1,2

¹Radiology, Center for Advanced Imaging Innovation and Research (CAI2R), New York, NY, United States, ²Radiology, Bernard and Irene Schwartz Center for Biomedical Imaging, New York, NY, United States

In a patient exam, SAR may cause temperature increase potentially leading to tissue damage or thermoregulatory distress. Hence, development of fast and accurate temperature computation methods could be useful for safety assurance. We propose a method considering more factors than ever before (including SAR, respiration, perspiration, convection, conduction, and local perfusion rates), where the temperature over an entire MRI exam is rapidly estimated exploiting the linearity of the bioheat equation. Nonlinear effects due to thermoregulatory mechanisms of the human body, such as the variation of local blood perfusion rate, are approximated with a fast spatial filter.

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