Evaluating Which Dose-Function Metrics Are Most Critical for Functional-Guided Radiation Therapy

Abstract

Purpose: Four-dimensional (4D) computed tomography (CT) ventilation imaging is increasingly being used to calculate lung ventilation and implement functional-guided radiation therapy in clinical trials. There has been little exhaustive work evaluating which dose-function metrics should be used for treatment planning and plan evaluation. The purpose of our study was to evaluate which dose-function metrics best predict for radiation pneumonitis (RP).

Methods and materials: Seventy lung cancer patients who underwent 4D CT imaging and pneumonitis grading were assessed. Pretreatment 4D CT scans of each patient were used to calculate ventilation images. We evaluated 3 types of dose-function metrics that combined the patient's 4D CT ventilation image and treatment planning dose distribution: (1) structure-based approaches; (2) image-based approaches using the dose-function histogram; and (3) nonlinear weighting schemes. Log-likelihood methods were used to generate normal tissue complication probability models predicting grade 3 or higher (ie, grade 3+) pneumonitis for all dose-function schemes. The area under the curve (AUC) was used to assess the predictive power of the models. All techniques were compared with normal tissue complication probability models based on traditional, total lung dose metrics.

Results: The most predictive models were structure-based approaches that focused on the volume of functional lung receiving ≥20 Gy (AUC, 0.70). Probabilities of grade 3+ RP of 20% and 10% correspond to V20 (percentage of volume receiving ≥20 Gy) to the functional subvolumes of 26.8% and 9.3%, respectively. Imaging-based analysis with the dose-function histogram and nonlinear weighted ventilation values yielded AUCs of 0.66 and 0.67, respectively, when we evaluated the percentage of functionality receiving ≥20 Gy. All dose-function metrics outperformed the traditional dose metrics (mean lung dose, AUC of 0.55).

Conclusions: A full range of dose-function metrics and functional thresholds was examined. The calculated AUC values for the most predictive functional models occupied a narrow range (0.66-0.70), and all showed notable improvements over AUC from traditional lung dose metrics (0.55). Identifying the combinations most predictive of grade 3+ RP provides valuable data to inform the functional-guided radiation therapy process.

Figure 1

Axial (left), sagittal (center), and coronal (right) planes of the functional sub-volume contour are presented for threshold values of 35^th percentile (top) and 75^th percentile (bottom). The red contour represents the target and blue and green represent the respective functional contours. The choice of threshold in delineating between functional and non-functional lung affects the size of the functional contour used during treatment planning optimization.

Figure 2

A coronal image of the ventilation calculation registered to the CT is presented. The right and left lung are divided into thirds as shown by the overlaid lines on the image. Brighter colors (reds, yellows, and greens) correspond to areas of higher ventilation while the darker colors (blue and purple) correspond to regions of lower ventilation. A clear ventilation defect is present in the right lower lobe of this patient.

Figure 3

A plot of the area under the curve (solid blue) and the p-Value (dashed orange) as a function of the cutoff in determining functional lung sub-volumes demonstrates the trend toward higher predictive power in modeling grade 3+ pneumonitis when evaluating areas of higher functioning lung. The metric of evaluation is the percent of functional lung receiving ≥20Gy.