Purpose: Advancements in functional lung imaging have improved the pretreatment understanding of a patient’s pulmonary function and have enabled the development of function-guided radiotherapy (RT) planning. Parametric response mapping (PRM) is a voxel-wise image analysis technique used for CT-based functional imaging that classifies lung abnormality phenotypes and has previously shown utility in the assessment of pulmonary complication risk in a diagnostic setting. The purpose of this work was to implement PRM guidance in a clinical RT planning workflow and examine the potential clinical impact.
Methods: PRM analysis was performed for 18 lung cancer patients using paired pretreatment inspiration/expiration CT scans to classify each voxel as normal, emphysema, small airway disease (SAD), or parenchymal disease (PD). The non-normal PRM data were converted to topological maps and high-density regions of each classification were contoured as avoidance structures for VMAT treatment planning. Treatment plans were optimized to maintain clinical organ-at-risk dose limits to the Lungs-GTV, spinal cord, heart, esophagus, and brachial plexus contours. Dosimetric comparisons were performed between non-function-guided plans and PRM-guided plans which included additional low priority goals reducing the V20Gy of PRM avoidance contours.
Results: The PRM-guided workflow was successfully implemented and the inclusion of PRM guidance resulted in statistically significant (p<0.05) improvements to the V20Gy of the PRM avoidance contours. The average reduction of the V20Gy(%) of all PRM avoidance contours was 5.4%. The inclusion of PRM guidance did not significantly (p>0.05) increase relevant dose metrics for OARs or decrease PTV coverage but did result in increased plan complexity.
Conclusion: PRM guidance in RT treatment planning was found to be effective at redistributing dose away from avoidance structures in the lung while maintaining OAR dose limits and PTV coverage constraints. The presented workflow provides a framework for the potential clinical implementation of PRM-guided treatment planning.
Funding Support, Disclosures, and Conflict of Interest: Craig Galban has a financial interest in Imbio, LLC, which has licensed PRM from the University of Michigan. This work was funded by NCI grant P01-CA059872, and NHLBI grants R01-HL139690 and R01-HL150023.