Nonlinear model predictive thermal dose control of thermal therapies: experimental validation with phantoms

Author(s):  
D. Arora ◽  
M. Skliar ◽  
D. Cooley ◽  
A. Blankespoor ◽  
J. Moellmer ◽  
...  
2005 ◽  
Vol 52 (2) ◽  
pp. 191-200 ◽  
Author(s):  
D. Arora ◽  
M. Skliar ◽  
R.B. Roemer

Author(s):  
Kung-Shan Cheng ◽  
Robert B. Roemer

This study derives the first analytic solution for evaluating the optimal treatment parameters needed for delivering a desired thermal dose during thermal therapies consisting of a single heating pulse. Each treatment is divided into four time periods (two power-on and two power-off), and the thermal dose delivered during each of those periods is evaluated using the non-linear Sapareto and Dewey equation relating thermal dose to temperature and time. The results reveal that the thermal dose delivered during the second power-on period when T>43C (TD2) and the initial power-off period when T>43C (TD3) contribute the major portions of the total thermal dose needed for a successful treatment (taken as 240 CEM43°C), and that TD3 dominates for treatments with higher peak temperatures. For a fixed perfusion value, the analytical results show that once the maximum treatment temperature and the total thermal dose (e.g., 240 CEM43°C) are specified, then the required heating time and the applied power magnitude are uniquely determined. These are the optimal heating parameters since lower/higher values result in under-dosing/over-dosing of the treated region. It is also shown that higher maximum treatment temperatures result in shorter treatment times, and for each patient blood flow there is a maximum allowable temperature that can be used to reach the desired thermal dose. In addition, since TD2 and TD3 contribute most of the total thermal dose, and they are both significantly affected by the blood flow present for high treatment temperatures, these results show that perfusion effects must be considered when attempting to optimize high temperature thermal therapy treatments (no excess thermal dose delivered, minimum power applied and shortest treatment time attained).


2016 ◽  
Vol 139 (4) ◽  
pp. 2175-2175
Author(s):  
Amin Jafari Sojahrood ◽  
Qian Li ◽  
Mark Burgess ◽  
Raffi Karshafian ◽  
Tyrone Porter ◽  
...  

2007 ◽  
Vol 15 (6) ◽  
pp. 1030-1037 ◽  
Author(s):  
Dhiraj Arora ◽  
Mikhail Skliar ◽  
Daniel Cooley ◽  
Robert B. Roemer

2017 ◽  
Vol 12 (4) ◽  
Author(s):  
Yousheng Chen ◽  
Andreas Linderholt ◽  
Thomas J. S. Abrahamsson

Correlation and calibration using test data are natural ingredients in the process of validating computational models. Model calibration for the important subclass of nonlinear systems which consists of structures dominated by linear behavior with the presence of local nonlinear effects is studied in this work. The experimental validation of a nonlinear model calibration method is conducted using a replica of the École Centrale de Lyon (ECL) nonlinear benchmark test setup. The calibration method is based on the selection of uncertain model parameters and the data that form the calibration metric together with an efficient optimization routine. The parameterization is chosen so that the expected covariances of the parameter estimates are made small. To obtain informative data, the excitation force is designed to be multisinusoidal and the resulting steady-state multiharmonic frequency response data are measured. To shorten the optimization time, plausible starting seed candidates are selected using the Latin hypercube sampling method. The candidate parameter set giving the smallest deviation to the test data is used as a starting point for an iterative search for a calibration solution. The model calibration is conducted by minimizing the deviations between the measured steady-state multiharmonic frequency response data and the analytical counterparts that are calculated using the multiharmonic balance method. The resulting calibrated model's output corresponds well with the measured responses.


2005 ◽  
Vol 50 (8) ◽  
pp. 1919-1935 ◽  
Author(s):  
Dhiraj Arora ◽  
Daniel Cooley ◽  
Trent Perry ◽  
Mikhail Skliar ◽  
Robert B Roemer

2005 ◽  
Author(s):  
Dhiraj Arora ◽  
Trent Perry ◽  
Daniel Cooley ◽  
Junyu Guo ◽  
Rock Hadley ◽  
...  

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