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This study evaluates the sensitivity of two magnetic resonance-guided focused ultrasound (MRgFUS) thermal property estimation methods to errors in required inputs and different data inclusion criteria. Using ex vivo pork muscle MRgFUS data, sensitivities to required inputs are determined by introducing errors to ultrasound beam locations (r error  =  -2 to 2 mm) and time vectors (t error  =  -2.2 to 2.2 s). In addition, the sensitivity to user-defined data inclusion criteria is evaluated by choosing different spatial (r fit  =  1-10 mm) and temporal (t fit  =  8.8-61.6 s) regions for fitting. Beam location errors resulted in up to 50% change in property estimates with local minima occurring at r error  =  0 and estimate errors less than 10% when r error  &lt;  0.5 mm. Errors in the time vector led to property estimate errors up to 40% and without local minimum, indicating the need to trigger ultrasound sonications with the MR image acquisition. Regarding the selection of data inclusion criteria, property estimates reached stable values (less than 5% change) when r fit  &gt;  2.5  ×  FWHM, and were most accurate with the least variability for longer t fit. Guidelines provided by this study highlight the importance of identifying required inputs and choosing appropriate data inclusion criteria for robust and accurate thermal property estimation. Applying these guidelines will prevent the introduction of biases and avoidable errors when utilizing these property estimation techniques for MRgFUS thermal modeling applications.

physics in medicine and biology/physics in medicine and biology

Sensitivity of tissue properties derived from MRgFUS temperature data to input errors and data inclusion criteria:<i>ex vivo</i>study in porcine muscle

Sensitivity of tissue properties derived from MRgFUS temperature data to input errors and data inclusion criteria:ex vivostudy in porcine muscle