Online estimation and control of minimum temperatures during conductive interstitial hyperthermia of brain tumors
Abstract
The dynamic nature of blood flow during hyperthermia therapy has made the control of minimum tumor temperature a difficult task. This report presents initial studies of a novel approach to closed loop control of local minimum tissue temperatures utilizing a newly developed estimation algorithm for use with conductive interstitial heating systems. The local minimum tumor temperature is explicitly estimated from the power required to maintain each member of an array of electrically heated catheters at a known temperature, in conjunction with a new bio-heat equation-based algorithm to predict the "droop" or fractional decline in tissue temperature between heated catheters. A closed loop proportional-integral (PI) controller utilizes estimated minimum temperature near each catheter as a feedback parameter, which reflects variations in local blood flow. In response, the controller alters delivered power to each catheter to compensate for changes in blood flow. The validity and stability of this estimation/control scheme were tested in computer simulations and in closed loop control of nine patient treatments. The average estimation error from patient data analysis of 21 sites at which temperature was independently measured (three per patient) was 0.0$\sp\circ$C, with a standard deviation of 0.8$\sp\circ$C. These results suggest that estimation of local minimum temperature and feedback control of power delivery can be employed effectively during conductive interstitial heat therapy of intracranial tumors in man.
Degree
Ph.D.
Advisors
Geddes, Purdue University.
Subject Area
Biomedical research|Electrical engineering|Mechanical engineering
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