Early prediction of the adverse outcomes associated with heat stress is critical for effective management and mitigation of injury, which may sometimes lead to extreme undesirable clinical conditions, such as multiorgan dysfunction syndrome and death. Here, we developed a computational model to predict the spatiotemporal temperature distribution in a rat exposed to heat stress in an attempt to understand the correlation between heat load and differential organ dysfunction. The model includes a three-dimensional representation of the rat anatomy obtained from medical imaging and incorporates the key mechanisms of heat transfer during thermoregulation. We formulated a novel approach to estimate blood temperature by accounting for blood mixing from the different organs and to estimate the effects of the circadian rhythm in body temperature by considering day-night variations in metabolic heat generation and blood perfusion. We validated the model using in vivo core temperature measurements in control and heat-stressed rats and other published experimental data. The model predictions were within 1 SD of the measured data. The liver demonstrated the greatest susceptibility to heat stress, with the maximum temperature reaching 2°C higher than the measured core temperature and 95% of its volume exceeding the targeted experimental core temperature. Other organs also attained temperatures greater than the core temperature, illustrating the need to monitor multiple organs during heat stress. The model facilitates the identification of organ-specific risks during heat stress and has the potential to aid in the development of improved clinical strategies for thermal-injury prevention and management.
Keywords: computational modeling; core temperature; finite element method; multiorgan dysfunction syndrome; radiotelemetry.