Optical-thermal modeling and treatment planning of ICG-enhanced interstitial photothermal therapy using cylindrical diffuser fibers.

Interstitial photothermal therapy (IPTT) enhanced with indocyanine green (ICG) represents a minimally invasive approach with growing interest for localized thermal ablation of deep-seated tumors. In this work, an optical-thermal modeling framework is developed to investigate heat generation, transfer, and thermal damage during ICG-assisted IPTT using cylindrical diffuser fibers (CDFs), with liver tissue considered as the target medium due to its distinct optical and perfusion properties. Finite element simulations were performed to couple optical energy deposition with Pennes' bioheat equation, enabling the prediction of spatiotemporal temperature distributions under near-infrared laser irradiation at 805 nm, near the absorption peak of ICG. The results indicate that the presence of ICG significantly enhances local energy absorption and thermal confinement in hepatic tissue, increasing peak temperatures from approximately 41 °C to about 60 °C under identical irradiation conditions, while maintaining sub-threshold damage levels in surrounding healthy liver regions. Arrhenius-based damage modeling predicted localized thermal damage near the diffuser region, with minimal collateral thermal injury. A volumetric and energy-based treatment-planning strategy was introduced to estimate the effective fiber number and spacing as a function of target volume, based on single-fiber simulations and extrapolated to multi-fiber configurations. The simulation-derived planning estimates suggest that small hepatic lesions would require one to two fibers under the assumed model parameters, whereas larger volumes require staged delivery with approximately six to ten fibers to achieve homogeneous thermal coverage within the therapeutic temperature window while respecting safety constraints. These findings provide preliminary quantitative insight into parameter selection for ICG-enhanced CDF-based IPTT and may support future optimization of treatment-planning strategies. However, phantom, animal, and in vivo validation are required before clinical inference or treatment recommendations can be made.