Predicting long-term temperature increase for time-dependent SAR levels with a single short-term temperature response.

Abstract

Present a novel method for rapid prediction of temperature in vivo for a series of pulse sequences with differing levels and distributions of specific energy absorption rate (SAR). After the temperature response to a brief period of heating is characterized, a rapid estimate of temperature during a series of periods at different heating levels is made using a linear heat equation and impulse-response (IR) concepts. Here the initial characterization and long-term prediction for a complete spine exam are made with the Pennes' bioheat equation where, at first, core body temperature is allowed to increase and local perfusion is not. Then corrections through time allowing variation in local perfusion are introduced. The fast IR-based method predicted maximum temperature increase within 1% of that with a full finite difference simulation, but required less than 3.5% of the computation time. Even higher accelerations are possible depending on the time step size chosen, with loss in temporal resolution. Correction for temperature-dependent perfusion requires negligible additional time and can be adjusted to be more or less conservative than the corresponding finite difference simulation. With appropriate methods, it is possible to rapidly predict temperature increase throughout the body for actual MR examinations.