The dynamic nature of perfusion in living tissues, such as solid tumors during thermal therapy, produces challenging spatiotemporal thermal boundary conditions. Changes in perfusion can manifest as changes in convective heat transfer that influence temperature changes during cyclic heating. Herein, we propose a method to actively monitor changes in local convection (perfusion) in vivo by using a transient thermal pulsing analysis. Syngeneic 4T1 tumor cells were injected subcutaneously into BALB/c mice and followed by caliper measurements. When tumor volumes measured 150–400 mm3, mice were randomly divided into one of two groups to receive intratumor injections of one of two iron oxide nanoparticle formulations for pulsed heating with an alternating magnetic field (AMF). The nanoparticles differed in both heating characteristics and coating. Intratumor temperature near the injection site as well as rectal temperature were measured with an optic fiber temperature probe. Following heating, mice were euthanized and tumors harvested and prepared for histological evaluation of nanoparticle distribution. To ascertain the heat transfer coefficient from heating and cooling pulses, we fit a lumped capacitance, Box-Lucas model to the time-temperature data assuming fixed tumor geometry and constant experimental conditions. For the first particle set, the injected nanoparticles dispersed evenly throughout the tumor with minimal aggregation, and with minimal change in convection. On the other hand, heating with the second particle generated a measurable decline in convective performance and histology analysis showed substantial aggregation near the injection site. We consider it likely that though the second nanoparticle type produced less heating per unit mass, its tendency to aggregate led to more intense local heating and tissue damage. Further analysis and experimentation is warranted to establish quantitative correlations between measured temperature changes, perfusion, and tissue damage responses. Implementing this type of analysis may stimulate development of robust and adaptive temperature controllers for medical device applications.

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