Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/13897
Title: Evaluation of Accuracy of a Theoretical Model for Predicting the Necrosed Tissue Volume during Focused Ultrasound Surgery
Authors: Hynynen, Kullervo 
Fan, Xiaobing 
Damianou, Christakis A. 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Necrosed tissue volume;Sommerfield integral techniques;Ultrasound surgery
Issue Date: 1-Jan-1995
Source: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 1995, vol. 42, no. 2, pp. 182-187
Volume: 42
Issue: 2
Journal: IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control 
Abstract: The concept of thermal dose as a predictor for the size of the necrosed tissue volume during high-intensity focussed ultrasound surgery was tested. The sensitivity of the predicted lesion size to the uncertainties in the iso-dose constant, attenuation coefficient, and thermal dose threshold of necrosis was studied. The predicted lesion size appears to be independent of attenuation at some high attenuation values and certain depth in tissue. Thus, for a given target depth, a proper selection of frequency could minimize the lesion size variability due to uncertainty in the tissue attenuation. The predicted lesion size was less dependent on the uncertainties in the iso-dose constant and thermal dose of necrosis. The predictions of the model were compared with experimental data in rabbit muscle, and experimental data in cat and rat brain measured by others. The agreement was found to be good in most of the experiments. Similarly, the model was found to predict well the trends of increasing power and pulse duration. 0885-3010/95$04.00 © 1995 IEEE
URI: https://hdl.handle.net/20.500.14279/13897
ISSN: 08853010
DOI: 10.1109/58.365232
Rights: © IEEE
Type: Article
Affiliation : Indiana University 
Harvard University 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

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