Automated treatment planning for brain and spinal metastases

Area of Science:

• Radiation Oncology
• Medical Physics
• Computational Biology

Background:

• Workflow efficiency in radiation therapy planning is crucial, particularly for urgent cases like spinal and cerebral metastases.
• The Eclipse Scripting API offers potential for automating complex treatment planning processes.

Purpose of the Study:

• To develop and evaluate an automated treatment planning approach for brain and spinal metastases.
• To assess the efficiency and quality of automated plans compared to traditional methods.

Main Methods:

• Retrospective analysis of 82 spinal and 93 brain metastasis patients.
• Algorithm development using Eclipse Scripting API for automated gantry angle optimization and lens dose reduction.
• Dosimetric analysis of planning target volume (PTV) and clinical target volume (CTV) coverage, and lens sparing.

Main Results:

• Automated planning achieved high PTV V99 (95.9%-98.8%) and CTV V99 (99.1%-100%) for both sites.
• Lens dose was effectively reduced through automated fluence modification.
• Treatment plan generation times were significantly reduced: 8 minutes for WBRT and 5-6 minutes for spinal metastases.

Conclusions:

• The developed automated algorithms efficiently generate high-quality treatment plans for brain and spinal metastases.
• This automation offers a substantial time-saving benefit in radiation therapy planning, crucial for urgent cases.