Biomedical subjects

A W Dutton

Publications and source records attributed to A W Dutton.

6 recordsLinked to original sources

PubMed1998

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

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.

Algorithms↗

PubMed1998

A generic tissue convective energy balance equation: Part I--theory and derivation.

A new equation for calculating temperatures in living tissues, the tissue convective energy balance equation (TCEBE), is derived using only a few assumptions. The resulting equation is basic, general and applicable to any tissue. The (unsolved) TCEBE is used: (a) to relate both Pennes' BHTE perfusion-related parameter (W) and the effective thermal conductivity equation's perfusion-related parameter (keff) to the true capillary perfusion Pcap, and (b) to show that both W and keff are defined, nonphysiological variables, which are only related to Pcap in a problem-dependent manner. Finally, the derivation of the relationship between W and Pcap provides a complete derivation of Pennes' BHTE, something that has not been previously done.

Body Temperature↗

PubMed1994

The simulation of discrete vessel effects in experimental hyperthermia.

The ability of two simple thermal models to predict experimentally measured in vivo temperature profiles was compared. These comparisons were done both with and without the inclusion of separate, discrete blood vessels. The two tissue models were: 1) Pennes' Bio-Heat Transfer equation (BHTE), and 2) an effective thermal conductivity equation (ETCE). The experimental temperature data were measured (Moros, 1990; Moros et al., 1993) in the thighs of anesthetized greyhound dogs under hyperthermic conditions generated by scanned focused ultrasound. Blood vessels were added to the thermal models in counter-current pairs transiting the model domain. The blood vessels in both models were assumed to have a constant heat transfer coefficient, and an axially varying mixed mean temperature. The vessel locations were determined a posteriori, via inspection of the experimental temperature data. Least square error fits of the predicted model temperatures to the experimental temperature data were obtained by adjusting both (a) the mass flow rate within and (b) the position of each blood vessel, and (c) the value of either the perfusion parameter (W) in the BHTE or the effective thermal conductivity parameter (Keff) in the ETCE. When small numbers (3-4) of blood vessel pairs were included, both of the models showed significant improvement in their ability to predict the experimental temperatures. Although both models performed well in terms of predicting temperatures near large vessels, the BHTE had a statistically significant better ability to predict the complete set of measured temperatures at all locations.

Angiography, Digital Subtraction↗

PubMedDate not supplied

An accurate, convective energy equation based automated meshing technique for analysis of blood vessels and tissues.

An automated three-element meshing method for generating finite element based models for the accurate thermal analysis of blood vessels imbedded in tissue has been developed and evaluated. The meshing method places eight noded hexahedral elements inside the vessels where advective flows exist, and four noded tetrahedral elements in the surrounding tissue. The higher order hexahedrals are used where advective flow fields occur, since high accuracy is required and effective upwinding algorithms exist. Tetrahedral elements are placed in the remaining tissue region, since they are computationally more efficient and existing automatic tetrahedral mesh generators can be used. Five noded pyramid elements connect the hexahedrals and tetrahedrals. A convective energy equation (CEE) based finite element algorithm solves for the temperature distributions in the flowing blood, while a finite element formulation of a generalized conduction equation is used in the surrounding tissue. Use of the CEE allows accurate solutions to be obtained without the necessity of assuming ad hoc values for heat transfer coefficients. Comparisons of the predictions of the three-element model to analytical solutions show that the three-element model accurately simulates temperature fields. Energy balance checks show that the three-element model has small, acceptable errors. In summary, this method provides an accurate, automatic finite element gridding procedure for thermal analysis of irregularly shaped tissue regions that contain important blood vessels. At present, the models so generated are relatively large (in order to obtain accurate results) and are, thus, best used for providing accurate reference values for checking other approximate formulations to complicated, conjugated blood heat transfer problems.

Automation↗

PubMedDate not supplied

Experimental evaluation of two simple thermal models using hyperthermia in muscle in vivo.

The predictions from two simple field equation models for calculating temperature distributions in tissue, namely, the Pennes' bioheat transfer equation (BHTE) and an effective thermal conductivity equation (ETCE), were compared to in vivo experimental temperature measurements made under hyperthermic conditions generated by scanned focused ultrasound. The models were kept simple (i.e. homogenous isotropic properties, no separate blood vessels included) in order to concentrate attention on the predictive abilities of these field equations using a minimum number of free parameters. Simulated results were fitted to the experimental data (multiple, linear temperature profiles in the thigh muscles of greyhound dogs) by minimizing a performance index using a golden section searth. This search determined a value for the single free parameter in each model (blood perfusion in the BHTE, and effective thermal conductivity in the ETCE) which minimized the square error difference between the experimental and simulated temperatures. The results showed that (a) the simple BHTE model could qualitatively reproduce the major features of the temperature patterns seen experimentally better than the ETCE model could, and (b) the simple BHTE model produced better quantitative fits to the experimental data than did the simple ETCE model. In addition, blood perfusion predictions from the BHTE model compared well to measurements done with coloured microspheres. Finally, the experimental results showed that individual, large blood vessels appeared to have a major influence in producing asymmetries in the experimental data in 21% of the measured temperature profiles.

Animals↗

PubMedDate not supplied

A comparison of reduced-order modelling techniques for application in hyperthermia control and estimation.

Reduced-order modelling techniques can make important contributions in the control and state estimation of large systems. In hyperthermia, reduced-order modelling can provide a useful tool by which a large thermal model can be reduced to the most significant subset of its full-order modes, making real-time control and estimation possible. Two such reduction methods, one based on modal decomposition and the other on balanced realization, are compared in the context of simulated hyperthermia heat transfer problems. The results show that the modal decomposition reduction method has three significant advantages over that of balanced realization. First, modal decomposition reduced models result in less error, when compared to the full-order model, than balanced realization reduced models of similar order in problems with low or moderate advective heat transfer. Second, because the balanced realization based methods require a priori knowledge of the sensor and actuator placements, the reduced-order model is not robust to changes in sensor or actuator locations, a limitation not present in modal decomposition. Third, the modal decomposition transformation is less demanding computationally. On the other hand, in thermal problems dominated by advective heat transfer, numerical instabilities make modal decomposition based reduction problematic. Modal decomposition methods are therefore recommended for reduction of models in which advection is not dominant and research continues into methods to render balanced realization based reduction more suitable for real-time clinical hyperthermia control and estimation.

Algorithms↗