Lung Tumor Growth Modeling in Patients with NSCLC Undergoing Radiotherapy

Abstract This paper proposes two modeling approaches to predict lung tumor dynamics as an effect of radiotherapy. Real clinical information of non-small cell lung cancer (NSCLC) patients undergoing stereotactic body radiation therapy (SBRT) as the primary treatment method has been used for numerical simulations. The classical Gompertz model for tumor volume growth prediction was modified using a fractional parameter and combined with the linear-quadratic model to foresee the effect of SBRT on the targeted tumor. Another approach was implemented by following a pharmacokinetic-pharmacodynamic (PKPD) minimal compartmental model for single therapy with SBRT. Statistical analysis has been carried out to compare the two models. In terms of tumor growth prediction, obtained results indicated a decrease in the total tumor volume for both modeling approaches. A striking observation to emerge from the data comparison is the interesting perspective of fractional tools for further exploration in modeling tumor growth.