Numerical Simulation of Laser-Induced Thermal Therapy for Superficial Tumors Using COMSOL Multiphysics

Abstract

Laser irradiation represents a highly precise method for delivering thermal energy to superficial cancer cells while minimizing injury to surrounding healthy tissue. Mathematical modeling of laser–tissue interaction is essential for treatment planning and outcome prediction. This study presents a comprehensive numerical simulation of heat distribution during laser-induced thermal therapy for superficial tumors using COMSOL Multiphysics. The novelty of this work lies in a two-dimensional axisymmetric multilayered skin model with an embedded tumor domain to perform a detailed parametric analysis of critical treatment variables. A 2D cross-sectional skin model consisting of the epidermis, dermis, and subcutaneous layers was constructed, with a circular tumor embedded within the dermis. Heat transfer was modeled using Pennes’ bioheat equation coupled with a laser heat source described by the Beer–Lambert absorption model. A systematic parametric investigation was conducted across five critical variables: laser intensity (1–5 W/cm²), exposure duration (10–100 s), blood perfusion rate (0–0.005 s⁻¹), optical absorption coefficient of the tumor (100–1000 m⁻¹), and tumor geometry (radial dimension and depth). The simulation demonstrates that optimized laser parameters can selectively raise tumor temperature to the therapeutic hyperthermia range (42–45 °C) and induce localized thermal damage. For instance, under an intensity of 3 W/cm² applied for 50 seconds, the tumor center reached a peak temperature of ~48 °C, while surrounding healthy tissue remained below 40 °C. Approximately 87% of the tumor volume reached temperatures above the therapeutic hyperthermia threshold (42 °C), while about 18% exceeded the ablation threshold (>45 °C). The model underscores the critical role of parameter optimization, particularly laser intensity and exposure time, in enhancing the efficacy and safety of laser-based tumor therapy, providing a valuable framework for preclinical treatment planning.