Functional lung avoidance (FLA) radiation therapy is an evolving field. The aim of FLA planning is to reduce dose to areas of functioning lung, with comparable target coverage and dose to organs at risk. Multi-criteria optimisation (MCO) is a planning tool that may assist with FLA planning. This study assessed the feasibility of using MCO to adapt radiation therapy plans in order to avoid functional regions of lung that were identified using a 68Ga-4D-V/Q PET/CT.Methods A prospective clinical trial [anonymized for review] was performed in which patients had a 68Ga-4D-V/Q PET/CT prior to radiation treatment. Of the 72 patients enrolled in this trial, 38 patients had stage III non-small cell lung cancer and were eligible for selection into this planning study. Functional lung target volumes HF lung (highly-functioning lung) and F lung (functional lung) were defined using the ventilated and perfused lung. Using knowledge-based planning, a baseline anatomical plan was created, and then a functional adapted plan was generated using multi-criteria optimisation. The primary aim was to spare dose to HF lung. Using the MCO tools, a clinician selected the final FLA plan. Dose to functional lung, target volumes, organs at risk and measures of plan quality were compared using standard statistical methods.Results The HF lung volume was successfully spared in all patients. The F lung volume was successfully spared in 36 of the 38 patients. There were no clinically significant differences in dose to anatomically defined organs at risk. There were differences in the planning target volume (PTV) near maximum and minimum doses. Across the entire population, there was a statistically significant reduction in the functional mean lung dose but not in the functional volume receiving 20 Gy. All trade-off decisions were made by the clinician.Conclusion Using MCO for FLA was achievable, but did result in changes to PTV coverage. A distinct advantage in using MCO was that all decisions regarding the cost and benefits of FLA could be made in real time.
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May 1, 2024
Teo Stanescu + 8
