Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo...

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Dosimetry

Background:

• Accurate dose calculation is crucial for effective radiotherapy planning.
• Clinical cases with large density inhomogeneities pose challenges for dose algorithms.
• Newer algorithms aim to improve accuracy over traditional methods like pencil beam convolution (PBC).

Purpose of the Study:

• To quantify dose distribution differences between modern algorithms and a benchmark Monte Carlo method.
• To evaluate the performance of anisotropic analytic algorithm (AAA) and collapsed cone convolution (CCC) in clinical scenarios.
• To compare dose calculation accuracy in lung and breast cancer cases with density variations.

Main Methods:

• Comparison of dose distributions from AAA, CCC, and Voxel Monte Carlo (VMC++) algorithms.
• Analysis of static field irradiations at 6 MV and 15 MV.
• Study of five clinical cases (3 lung, 2 breast) with large density inhomogeneities.

Main Results:

• CCC demonstrated superior accuracy compared to AAA when benchmarked against VMC++.
• AAA offers a balance of accuracy and speed, making it suitable for routine clinical use.
• Dose differences in the planning target volume (PTV) were small (0.4% in lung, -1.3% in breast).

Conclusions:

• CCC is more accurate than AAA for complex cases, but AAA is a practical choice for routine planning.
• PTV coverage and dose homogeneity are more sensitive to calculation accuracy in lung cases.
• Monte Carlo simulations provide a reliable benchmark for evaluating radiotherapy dose calculation algorithms.