Model Dinamika Interaksi Kanker Squamous Cell Carcinoma Terhadap Radioterapi Kontinu

Abstract

Radioterapi merupakan metode utama dalam pengobatan kanker, termasuk Squamous Cell Carcinoma (SCC). Penelitian ini mengembangkan model interaksi sel kanker dan sel normal selama radioterapi menggunakan Persamaan Diferensial Biasa (PDB) berbasis kerangka Lotka-Volterra dengan pendekatan Linear-Quadratik (LQ) pada persamaan Death Rate. Model diselesaikan secara numerik dengan metode Euler untuk mengevaluasi pengaruh variasi skenario dengan 3 Case pemberian iradiasi, jumlah fraksi dosis, serta dilakukan analisis sensitivitas menggunakan pendekatan one-at-a-time (OAT) dan Morris. Hasil menunjukkan bahwa radioterapi dua sesi per hari lebih efektif dibandingkan terapi tunggal, terutama apabila populasi sel normal lebih besar. Analisis sensitivitas mengidentifikasi parameter radiosensitivitas dan laju pertumbuhan sel kanker sebagai faktor paling berpengaruh terhadap akumulasi populaai sel kanker. Model ini memberikan dasar konseptual bagi pengembangan strategi radioterapi yang lebih adaptif, presisi, dan berbasis karakteristik biologis pasien.

Radiotherapy is a primary modality in cancer treatment, including for Squamous Cell Carcinoma (SCC). This study develops a dynamic model of the interaction between cancer cells and normal cells during radiotherapy using Ordinary Differential Equations (ODEs) based on a Lotka–Volterra framework, with a Linear–Quadratic (LQ) approach applied to the death rate term. The model is solved numerically using the Euler method to evaluate the effects of different irradiation scenarios across three treatment cases, varying dose fractions, and to perform sensitivity analysis using both the one-at-a-time (OAT) and Morris methods. The results show that two-session daily radiotherapy is more effective than single-session treatment, particularly when the normal cell population is relatively large. Sensitivity analysis identifies cancer cell radiosensitivity and proliferation rate as the most influential parameters affecting tumor burden. This model provides a conceptual basis for developing more adaptive, precise radiotherapy strategies tailored to patients’s biological characteristics.