Functional avoidance of lung in plan optimization with an aperture-based inverse planning system.

Area of Science:

• Radiation Oncology
• Medical Imaging
• Computational Biology

Background:

• Anatomical information is traditionally used in inverse planning for thoracic irradiation.
• Lung sparing is crucial to minimize radiation-induced lung damage.
• Functional imaging offers potential for more precise treatment planning.

Purpose of the Study:

• To implement Single Photon Emission Computed Tomography (SPECT)-based optimization in an inverse planning system.
• To achieve functional avoidance of the lung during thoracic irradiation.
• To compare functional versus purely anatomical planning approaches.

Main Methods:

• SPECT data modulated lung importance factors voxel-by-voxel based on perfusion.
• Angle-optimized non-coplanar plans were generated for 15 lung cancer cases.
• Planning target volume coverage and lung sparing were compared between anatomical and functional approaches.

Main Results:

• Functional approach significantly reduced perfusion-weighted lung dose (median 0.9 Gy, p=0.001).
• Perfusion-weighted lung volume receiving 10 Gy was reduced by a median of 2.2% (p=0.022) for similar target coverage.
• Dose redirection occasionally led to target overdosage; no difference noted between hypoperfusion patterns.

Conclusions:

• SPECT-based modulation enables functional lung avoidance while preserving target coverage.
• This technique can be extended to Positron Emission Tomography (PET)-based modulation for safer dose escalation.
• Functional imaging integration enhances precision in thoracic radiation therapy planning.