# Finite Element Implementation of Delta-P1 Model for Simulation of Photothermal Cancer Therapy in Heterogeneous Tissues

## TL;DR

This paper validates a new model for simulating photothermal cancer therapy, showing it can accurately predict temperature changes in tissues.

## Contribution

The study introduces and validates the δP1 model for simulating photothermal therapy in heterogeneous tissues.

## Key findings

- The δP1 model outperforms Beer–Lambert and Standard diffusion models in predicting temperature distributions.
- The model accurately captures the influence of heterogeneous tissue geometries on photothermal therapy.
- Results are validated against analytical, Monte Carlo, and experimental data.

## Abstract

Photothermal therapy (PTT) is an emerging non-invasive treatment for cancer, offering targeted, localized therapy with minimal side effects. Its growing significance lies in its ability to precisely heat and destroy tumor cells while sparing surrounding healthy tissue. This study aimed to validate the δP1 approximation for simulating light propagation and thermal effects in biological tissues, particularly for photothermal therapy (PTT) applications. The model is applied to various scenarios, including homogeneous and heterogeneous tissue geometries with different optical properties and nanoparticle concentrations. The results are compared with analytical solutions, Monte Carlo results and experimental data to assess model accuracy. The δP1 approximation demonstrates superior performance compared to Beer–Lambert and Standard diffusion models, accurately predicting temperature distributions and capturing the influence of heterogeneous geometries. These findings highlight the potential of the δP1 model to significantly advance the field of PTT by providing reliable predictions for treatment planning and optimization.