Chaikh Abdulhamid, Balosso Jacques
Department of Radiation Oncology and Medical physics, University Hospital of Grenoble, France.
Department of Radiation Oncology and Medical physics, University Hospital of Grenoble, France;; University Grenoble, Alpes, Grenoble, France.
Quant Imaging Med Surg. 2016 Aug;6(4):413-417. doi: 10.21037/qims.2016.08.09.
The risk of toxicity with radiation oncology for lung cancer limits the maximal radiation dose that can be delivered to thoracic tumors. This study aims at investigating the correlation between normal tissue complication probability (NTCP) and physical lung density by analyzing the computed tomography (CT) scan imaging used for radiotherapy dose planning.
Data from CT of lung cancer patients (n=10), treated with three dimensional radiotherapy, were selected for this study. The dose was calculated using analytical anisotropic algorithm (AAA). Dose volume histograms (DVH) for healthy lung (lung excluding targets) were calculated. The NTCP for lung radiation induced pneumonitis was computed using initial radiobiological parameters from Lyman-Kutcher and Burman (LKB) model and readjusted parameters for AAA, with α/β=3. The correlation coefficient "rho" was calculated using Spearman's rank test. The bootstrap method was used to estimate the 95% confidence interval (95% CI). Wilcoxon paired test was used to calculate P values.
Bootstrapping simulation revealed significant difference between NTCP computed with the initial radiobiological parameters and that computed with the parameters readjusted for AAA (P=0.03). The results of simulations based on 1,000 replications showed no correlation for NTCP with density, with "rho" <0.3.
For a given set of patients, we assessed the correlation between NTCP and lung density using bootstrap analysis. The lack of correlation could result either from a very accurate dose calculation, by AAA, whatever the lung density yielding a NTCP result only dependant of the dose and not any more of the density; or to the very limited range of natural variation of relative electronic density (0.15 to 0.20) observed in this small series of patients. Another important parameter is the bootstrap simulation with 1,000 random samplings may have underestimated the correlation, since the initial data (n=10) showed a weak correlation.
肺癌放射肿瘤学中的毒性风险限制了可给予胸部肿瘤的最大辐射剂量。本研究旨在通过分析用于放射治疗剂量规划的计算机断层扫描（CT）扫描成像，探讨正常组织并发症概率（NTCP）与肺物理密度之间的相关性。
本研究选取了10例接受三维放射治疗的肺癌患者的CT数据。使用解析各向异性算法（AAA）计算剂量。计算健康肺组织（不包括靶区的肺）的剂量体积直方图（DVH）。使用来自Lyman-Kutcher和Burman（LKB）模型的初始放射生物学参数以及AAA的调整参数（α/β = 3）计算肺放射性肺炎的NTCP。使用Spearman秩检验计算相关系数“rho”。采用自助法估计95%置信区间（95%CI）。使用Wilcoxon配对检验计算P值。
自助模拟显示，使用初始放射生物学参数计算的NTCP与使用为AAA调整的参数计算的NTCP之间存在显著差异（P = 0.03）。基于1000次重复的模拟结果显示，NTCP与密度无相关性，“rho”<0.3。
对于给定的一组患者，我们使用自助分析评估了NTCP与肺密度之间的相关性。缺乏相关性可能是由于AAA进行的剂量计算非常准确，无论肺密度如何，产生的NTCP结果仅取决于剂量，而不再取决于密度；或者是由于在这一小系列患者中观察到的相对电子密度的自然变化范围非常有限（0.15至0.20）。另一个重要参数是，由于初始数据（n = 10）显示相关性较弱，1000次随机抽样的自助模拟可能低估了相关性。
