Abstract

Computed tomographic (CT) ventilation imaging is a new modality that uses 4-dimensional (4D) CT information to calculate lung ventilation. Although retrospective studies have reported on the reduction in dose to functional lung, no work to our knowledge has been published in which the dosimetric improvements have been translated to a reduction in the probability of pulmonary toxicity. Our work estimates the reduction in toxicity for CT ventilation-based functional avoidance planning. Seventy previously treated lung cancer patients who underwent 4DCT imaging were used for the study. CT ventilation maps were calculated with 4DCT deformable image registration and a density change-based algorithm. Pneumonitis was graded on the basis of imaging and clinical presentation. Maximum likelihood methods were used to generate normal tissue complication probability (NTCP) models predicting grade 2 or higher (2+) and grade 3+pneumonitis as a function of dose (V5 Gy, V10Gy, V20Gy, V30Gy, and mean dose) to functional lung. For 30 patients a functional plan was generated with the goal of reducing dose to the functional lung while meeting Radiation Therapy Oncology Group 0617 constraints. The NTCP models were applied to the functional plans and the clinically used plans to calculate toxicity reduction. By the use of functional avoidance planning, absolute reductions in grade 2+NTCP of 6.3%, 7.8%, and 4.8% were achieved based on the mean fV20Gy, fV30Gy, and mean dose to functional lung metrics, respectively. Absolute grade 3+NTCP reductions of 3.6%, 4.8%, and 2.4% were achieved with fV20Gy, fV30Gy, and mean dose to functional lung. Maximum absolute reductions of 52.3% and 16.4% were seen for grade 2+and grade 3+pneumonitis for individual patients. Our study quantifies the possible toxicity reduction from CT ventilation-based functional avoidance planning. Reductions in grades 2+and 3+pneumonitis were 7.1% and 4.7% based on mean dose-function metrics, with reductions as high as 52.3% for individual patients. Our work provides seminal data for determining the potential toxicity benefit from incorporating CT ventilation into thoracic treatment planning.

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