Assessment of lung cancer, its treatment with radiotherapy, and its Dose Calculation - Tareg Mohammed H Al Mansour,; Hassan Saleh M Al Khamsan,; Ibrahim Ali M Alsulaiman,; Mohammed Husaain A Alyami,; Mohammed Mahdi Hadi Alajmi,; Abdullah Hussain Salem Alyami,; Masaud Mohammed Alyami,; Saleh Rajeh Alyami, (International Journal of Medical Toxicology and Legal Medicine, 2024)
Background: Lung cancer ranks among the top causes of illness and death globally, highlighting the need for effective treatment approaches. This study aimed to explore the use of radiotherapy in lung cancer treatment, with a focus on dose adjustments for lung inhomogeneity and density variations. Materials and Methods: The study’s methodology was divided into two stages. In the first stage, a computerized treatment planning system was used to set up configurations and procedures. After refining the initial data within this system, the second phase involved gathering experimental results using an ionization chamber as a standard. Treatment planning in this study required advanced techniques for targeting lung cancer, considering shifts in dose variance as lung density fluctuates. The Collapsed Cone Convolution Superposition (CCCS) model was employed to evaluate lung dose calculations in terms of lung density, treatment geometry, and dosage comparisons. Results: Findings from the study suggest that homogeneous dose calculations from CCCS align closely—within 1%—with those from the adaptive convolution (AC) method. This indicates that AC, with its faster processing capability, may serve as a viable alternative to CCCS. Conclusion: Dose absorption calculations derived from the treatment planning system (TPS) based on the CCCS algorithm yield highly accurate results. This accuracy is supported by Monte Carlo calculations, which are effective in modeling heterogeneous media and low-density materials, such as lung tissue.