Toward automatic field selection and planning using Monte Carlo-based direct aperture optimization in modulated...

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Biology

Background:

• Modulated electron radiotherapy (MERT) is effective for shallow tumors.
• Few-leaf electron collimator (FLEC)-based MERT requires efficient automated planning.
• Abutting fields in MERT can cause dose inhomogeneities.

Purpose of the Study:

• To investigate automated field determination for FLEC-based MERT.
• To create a phase-space database of pre-calculated beamlets.
• To compare FLEC-based MERT with helical TomoTherapy clinically.

Main Methods:

• Generated a database of pre-calculated beamlets using Monte Carlo (MC) simulations.
• Utilized an overlapping feathered beamlet pattern to mitigate dose inhomogeneities.
• Performed a preliminary clinical comparison of FLEC-MERT and helical TomoTherapy for spinal irradiation.

Main Results:

• FLEC-based MERT planning techniques produced promising results with minimal user input.
• The phase-space database reduced MC calculation time.
• The feathered field pattern improved target dose homogeneity.
• While not conforming as closely to PTV constraints as TomoTherapy for spinal cases, MERT plans reduced the low-dose bath.

Conclusions:

• Automated FLEC-based MERT planning is a promising technique.
• Phase-space databases and feathered beamlet patterns enhance MERT planning efficiency and quality.
• FLEC-based MERT has the potential for a significant clinical role in radiation therapy.