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Dosimetric Impact of Prescription Point Placement in Heterogeneous Medium for Conformal Radiotherapy Dose Calculation
Bharath Pandu1,2, D Khanna1, Mohandass Palanisamy3
1Department of Applied Physics, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India.
Objective:
The aim of the study is to compare the accuracy of dose calculation for different dose calculation algorithms with different prescription points (air, tissue, air-tissue interface in carcinoma lung patients and bone, tissue, and bone-tissue interface in carcinoma buccal Mucosa tumors).
Materials And Methods:
Forty-one patients with carcinoma lung and buccal mucosa were retrospectively selected for this study. A three-dimensional conformal radiotherapy reference plan was created using the prescription point in the tissue with Monte Carlo (MC) algorithms for both the groups of patients. The reference plan was modified by changing the prescription point and algorithms in the tissue, air, air-tissue interface for lung patients and tissue, bone, and bone-tissue interface for buccal mucosa patients. The dose received by the target volume and other organs at risk (OAR) structures was compared. To find out the statistical difference between different prescription points and algorithms, the statistical tests were performed with repeated measures ANOVA.
Results:
The target volume receiving 95% dose coverage in lung patients decreased to -3.08%, -5.75%, and -1.87% in the dose prescription point at the air-tissue interface with the dose calculation algorithms like MC, collapsed cone (CC), and pencil beam (PB), respectively, compared to that of the MC tissue. Spinal cord dose was increased in the CC and PB algorithms in all prescription points in patients with lung and buccal mucosa. OAR dose calculated by PB in all prescription points showed a significant deviation compared to MC tissue prescription point.
Conclusion:
This study will help demonstrate the accuracy of dose calculation for the different dose prescription points with the different treatment algorithms in radiotherapy treatment planning.
