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Feasibility of function-guided lung treatment planning with parametric response mapping
Charles K Matrosic1, D Rocky Owen1, Daniel Polan1
1Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA.
Journal of Applied Clinical Medical Physics
|October 26, 2021
Summary
Parametric response mapping (PRM) successfully guided lung cancer radiotherapy planning, reducing radiation dose to healthy lung tissue. This functional imaging technique optimizes treatment and minimizes pulmonary complications.
Area of Science:
- Medical Imaging
- Radiation Oncology
- Pulmonary Medicine
Background:
- Functional lung imaging advances improve understanding of pulmonary conditions for tailored treatments.
- Parametric response mapping (PRM), a CT-based method, classifies lung abnormalities and assesses complication risk.
- PRM aids in optimizing radiation therapy to mitigate pulmonary complications.
Purpose of the Study:
- To demonstrate the implementation of PRM guidance in radiotherapy treatment planning.
- To evaluate the effectiveness of PRM in optimizing radiation dose distribution within the lung.
Main Methods:
- Retrospective study of 18 lung cancer patients.
- Paired inspiration/expiration CT scans analyzed using PRM to classify lung voxels.
- Generation of density maps for PRM classifications to contour abnormalities.
- Comparison of conventional VMAT and PRM-guided treatment plans.
Main Results:
- Successful implementation of PRM into radiotherapy planning.
- Statistically significant reduction in V20Gy (average 5.4%) within PRM avoidance contours.
- PRM-guided plans did not compromise organ-at-risk dose or target volume coverage.
- Increased planning complexity observed with PRM-guided plans.
Conclusions:
- PRM guidance effectively integrated into treatment planning for lung cancer.
- PRM enables successful dose redistribution within the lung, improving treatment safety.
- This study provides a framework for clinical implementation of PRM-guided radiotherapy.
