Reduced-order modeling for hyperthermia: an extended balanced-realization-based approach

• Published in: IEEE transactions on biomedical engineering Vol. 45; no. 9; pp. 1154 - 1162
• Main Authors: Mattingly, M., Bailey, E.A., Dutton, A.W., Roemer, R.B., Devasia, S.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.09.1998; Institute of Electrical and Electronics Engineers
• Subjects: Actuators; Algorithms; Animals; Biological and medical sciences; Biological system modeling; Biomedical engineering; Biophysical Phenomena; Biophysics; Cancer; Computer Simulation; Dogs; Feedback; Finite Element Analysis; Humans; Hyperthermia; Hyperthermia, Induced; Induced hyperthermia. Cryotherapy; Mathematical models; Medical sciences; Models, Biological; Neoplasms - therapy; Parameter estimation; Reduced order systems; Temperature; Temperature control; Temperature sensors; Thermal Conductivity; Thermal sensors; Treatment with physical agents; Treatment. General aspects; Tumors; Temperature distribution; Positioning; Parameter estimation; Simulation; Technique; Malignant tumor; Hyperthermia; Modeling; Treatment planning
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/10.709559

Accurate thermal models are needed in hyperthermia cancer treatments for such tasks as actuator and sensor placement design, parameter estimation, and feedback temperature control. The complexity of the human body produces full-order models which are too large for effective execution of these tasks, making use of reduced-order models necessary. However, standard balanced-realization (SBR)-based model reduction techniques require a priori knowledge of the particular placement of actuators and sensors for model reduction. Since placement design is intractable (computationally) on the full-order models, SBR techniques must use ad hoc placements. To alleviate this problem, an extended balanced-realization (EBR)-based model-order reduction approach is presented. The new technique allows model order reduction to be performed over all possible placement designs and does not require ad hoc placement designs. It is shown that models obtained using the EBR method are more robust to intratreatment changes in the placement of the applied power field than those models obtained using the SBR method.