Department of Radiation Oncology, University of Colorado School of Medicine, Aurora, Colorado, USA.
Int J Radiat Oncol Biol Phys. 2013 Jun 1;86(2):366-71. doi: 10.1016/j.ijrobp.2013.01.004. Epub 2013 Mar 6.
Four-dimensional computed tomography (4DCT)-based ventilation is an emerging imaging modality that can be used in the thoracic treatment planning process. The clinical benefit of using ventilation images in radiation treatment plans remains to be tested. The purpose of the current work was to test the potential benefit of using ventilation in treatment planning by evaluating whether dose to highly ventilated regions of the lung resulted in increased incidence of clinical toxicity.
Pretreatment 4DCT data were used to compute pretreatment ventilation images for 96 lung cancer patients. Ventilation images were calculated using 4DCT data, deformable image registration, and a density-change based algorithm. Dose-volume and ventilation-based dose function metrics were computed for each patient. The ability of the dose-volume and ventilation-based dose-function metrics to predict for severe (grade 3+) radiation pneumonitis was assessed using logistic regression analysis, area under the curve (AUC) metrics, and bootstrap methods.
A specific patient example is presented that demonstrates how incorporating ventilation-based functional information can help separate patients with and without toxicity. The logistic regression significance values were all lower for the dose-function metrics (range P=.093-.250) than for their dose-volume equivalents (range, P=.331-.580). The AUC values were all greater for the dose-function metrics (range, 0.569-0.620) than for their dose-volume equivalents (range, 0.500-0.544). Bootstrap results revealed an improvement in model fit using dose-function metrics compared to dose-volume metrics that approached significance (range, P=.118-.155).
To our knowledge, this is the first study that attempts to correlate lung dose and 4DCT ventilation-based function to thoracic toxicity after radiation therapy. Although the results were not significant at the .05 level, our data suggests that incorporating ventilation-based functional imaging can improve prediction for radiation pneumonitis. We present an important first step toward validating the use of 4DCT-based ventilation imaging in thoracic treatment planning.
基于四维计算机断层扫描(4DCT)的通气是一种新兴的成像方式,可用于胸部治疗计划过程。在放射治疗计划中使用通气图像的临床益处仍有待检验。本研究的目的是通过评估肺高通气区的剂量是否导致临床毒性增加来检验在治疗计划中使用通气的潜在益处。
使用 96 例肺癌患者的预处理 4DCT 数据来计算预处理通气图像。使用 4DCT 数据、变形图像配准和基于密度变化的算法计算通气图像。为每位患者计算剂量-体积和基于通气的剂量函数指标。使用逻辑回归分析、曲线下面积(AUC)指标和自举方法评估剂量-体积和基于通气的剂量函数指标预测严重(3 级以上)放射性肺炎的能力。
呈现了一个特定的患者示例,该示例演示了如何结合基于通气的功能信息来帮助区分有和无毒性的患者。逻辑回归显著性值均低于剂量函数指标(范围 P=.093-.250),高于剂量-体积等效物(范围 P=.331-.580)。剂量函数指标的 AUC 值均大于剂量-体积等效物(范围 0.569-0.620)。自举结果表明,与剂量-体积指标相比,使用剂量函数指标可显著改善模型拟合(范围 P=.118-.155)。
据我们所知,这是第一项尝试将肺剂量和 4DCT 基于通气的功能与放射治疗后胸部毒性相关联的研究。尽管结果在 0.05 水平上不显著,但我们的数据表明,结合基于通气的功能成像可以提高对放射性肺炎的预测。我们提出了验证在胸部治疗计划中使用基于 4DCT 的通气成像的重要的第一步。