RESUMO
BACKGROUND AND OBJECTIVE: The effectiveness of current microwave ablation (MWA) therapies is limited. Administration of thermosensitive liposomes (TSLs) which release drugs in response to heat has presented a significant potential for enhancing the efficacy of thermal ablation treatment, and the benefits of targeted drug delivery. However, a complete knowledge of the mechanobiological processes underlying the drug release process, especially the intravascular drug release mechanism and its distribution in response to MWA needs to be improved. Multiscale computational-based modeling frameworks, integrating different biophysical phenomena, have recently emerged as promising tools to decipher the mechanobiological events in combo therapies. The present study aims to develop a novel multiscale computational model of TSLs delivery following MWA implantation. METHODS: Due to the complex interplay between the heating procedure and the drug concentration maps, a computational model is developed to determine the intravascular release of doxorubicin from TSL, its transvascular transport into the interstitium, transport in the interstitium, and cell uptake. Computational models can estimate the interplays among liposome and drug properties, tumor perfusion, and heating regimen to examine the impact of essential parameters and to optimize a targeted drug delivery platform. RESULTS: Results indicated that the synergy of TSLs with MWA allows more localized drug delivery with lower side effects. The drug release rate and tumor permeability play crucial roles in the efficacy of TSLs during MWA treatment. The computational model predicted an unencapsulated drug lime around the ablated zone, which can destroy more cancer cells compared to MWA alone by 40%. Administration of TSLs with a high release rate capacity can improve the percentage of killed cancer cells by 24%. Since the heating duration in MWA is less than 15 min, the presented combination therapy showed better performance for highly permeable tumors. CONCLUSION: This study highlights the potential of the proposed computational framework to address complex and realistic scenarios in cancer treatment, which can serve as the future research foundation, including advancements in nanomedicine and optimizing the pair of TSL and MWA for both preclinical and clinical studies. The present model could be as a valuable tool for patient-specific calibration of essential parameters.