Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy

The purpose of this work is to evaluate the predictive strength of the relative seriality, parallel and LKB normal tissue complication probability (NTCP) models regarding the incidence of radiation pneumonitis, in a large group of patients following breast cancer radiotherapy, and furthermore, to illustrate statistical methods for examining whether certain published radiobiological parameters are compatible with a clinical treatment methodology and patient group characteristics. The study is based on 150 consecutive patients who received radiation therapy for breast cancer. For each patient, the 3D dose distribution delivered to lung and the clinical treatment outcome were available. Clinical symptoms and radiological findings, along with a patient questionnaire, were used to assess the manifestation of radiation-induced complications. Using this material, different methods of estimating the likelihood of radiation effects were evaluated. This was attempted by analysing patient data based on their full dose distributions and associating the calculated complication rates with the clinical follow-up records. Additionally, the need for an update of the criteria that are being used in the current clinical practice was also examined. The patient material was selected without any conscious bias regarding the radiotherapy treatment technique used. The treatment data of each patient were applied to the relative seriality, LKB and parallel NTCP models, using published parameter sets. Of the 150 patients, 15 experienced radiation-induced pneumonitis (grade 2) according to the radiation pneumonitis scoring criteria used. Of the NTCP models examined, the relative seriality model was able to predict the incidence of radiation pneumonitis with acceptable accuracy, although radiation pneumonitis was developed by only a few patients. In the case of modern breast radiotherapy, radiobiological modelling appears to be very sensitive to model and parameter selection giving clinically acceptable results in certain cases selectively (relative seriality model with Seppenwoolde et al and Gagliardi et al parameter sets). The use of published parameters should be considered as safe only after their examination using local clinical data. The variation of inter-patient radiosensitivity seems to play a significant role in the prediction of such low incidence rate complications. Scoring grades were combined to give stronger evidence of radiation pneumonitis since their differences could not be strictly associated with dose. This obviously reveals a weakness of the scoring related to this endpoint, and implies that the probability of radiation pneumonitis induction may be too low to be statistically analysed with high accuracy, at least with the latest advances of dose delivery in breast radiotherapy.     

Clinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapy

The choice of the appropriate model and parameter set in determining the relation between the incidence of radiation pneumonitis and dose distribution in the lung is of great importance, especially in the case of breast radiotherapy where the observed incidence is fairly low. From our previous study based on 150 breast cancer patients, where the fits of dose-volume models to clinical data were estimated (Tsougos et al 2005 Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy Phys. Med. Biol. 50 3535-54), one could get the impression that the relative seriality is significantly better than the LKB NTCP model. However, the estimation of the different NTCP models was based on their goodness-of-fit on clinical data, using various sets of published parameters from other groups, and this fact may provisionally justify the results. Hence, we sought to investigate further the LKB model, by applying different published parameter sets for the very same group of patients, in order to be able to compare the results. It was shown that, depending on the parameter set applied, the LKB model is able to predict the incidence of radiation pneumonitis with acceptable accuracy, especially when implemented on a sub-group of patients (120) receiving [see text]|EUD higher than 8 Gy. In conclusion, the goodness-of-fit of a certain radiobiological model on a given clinical case is closely related to the selection of the proper scoring criteria and parameter set as well as to the compatibility of the clinical case from which the data were derived.     

肺癌放射治疗后放射性肺炎与剂量体积直方图相关性分析

目的 分析接受图像引导放射治疗（IGRT）的肺癌患者其剂量体积直方图（DVH）的参数设定与放射性肺炎（RP）发生情况的相关性。方法 选取我科行放射治疗的肺癌患者50例,分析DVH中接受5、10、20、30 Gy照射的肺体积占全肺体积的百分比（V5、V10、V20、V30）和平均照射肺体积（MLD）,以及年龄、性别、吸烟史、化疗史、肺部疾病史、肿瘤位置、病理类型、总剂量、射野个数等临床指标。根据随访结果及临床表现,把患者分为无RP组（0级）和有RP组（1~4级）,比较所有因素与放射性肺炎的相关性。结果 放射性肺炎发生率为58.00%（29/50）,其中无RP组（0级）21例（42.00%）,有RP组（1~4级）中1级 19例,2级8例,3级2例,无4级放射性肺炎发生,分析显示所有剂量学参数以及临床指标中吸烟史和化疗史与放射性肺炎发生有统计学意义（P＜0.05）,而其他临床指标如年龄、性别、肿瘤位置及病理分型,放疗总剂量及射野个数与放射性肺炎发生无明显相关。结论 DVH上所有参数均可以作为评估及预测放射性肺炎发生的指标,同时有化疗史和吸烟史的患者在治疗时尤其需要控制剂量。     

The analysis of prognostic factors affecting post-radiation acute reaction after conformal radiotherapy for non-small cell lung cancer

Introduction

The aim was to evaluate the risk of acute side effects in the lung after 3-dimensional conformal radiotherapy (3D-CRT) in patients treated for non-small cell lung cancer (NSCLC). An attempt was made to single out clinical factors and factors related to treatment technique which may induce acute post-radiation pneumonitis.

Material and methods

The analysis concerned 34 consecutive patients who underwent radical radiation therapy for NSCLC. Intensity of early toxicity was evaluated using modified RTOG/EORTC toxicity score. The endpoint for this analysis was the occurrence of radiation pneumonitis of grade 2 or higher. Factors related to treatment techniques were included in the statistical analysis.

Results

Fifty-three percent of patients included in the study suffered from acute post-radiation pneumonitis. The results of the study revealed the existence of lung tissue sensitivity to low doses of ionizing radiation. The multivariate analysis showed that total lung volume receiving a low dose of 10 Gy increased the risk of post-radiation pneumonitis (p = 0.01).

Conclusions

Acute post-radiation pneumonitis was a relevant clinical problem in patients who underwent radical radiotherapy for non-small cell lung cancer. The lung volume receiving a dose of 10 Gy was the most important dosimetric factor which influenced the post-radiation acute pneumonitis.     

Lyman-Kutcher-Burman NTCP model parameters for radiation pneumonitis and xerostomia based on combined analysis of published clinical data

Knowledge of accurate parameter estimates is essential for incorporating normal tissue complication probability (NTCP) models into biologically based treatment planning. The purpose of this work is to derive parameter estimates for the Lyman-Kutcher-Burman (LKB) NTCP model using a combined analysis of multi-institutional toxicity data for the lung (radiation pneumonitis) and parotid gland (xerostomia). A series of published clinical datasets describing dose response for radiation pneumonitis (RP) and xerostomia were identified for this analysis. The data support the notion of large volume effect for the lung and parotid gland with the estimates of the n parameter being close to unity. Assuming that n = 1, the m and TD(50) parameters of the LKB model were estimated by the maximum likelihood method from plots of complication rate as a function of mean organ dose. Ninety five percent confidence intervals for parameter estimates were obtained by the profile likelihood method. If daily fractions other than 2 Gy had been used in a published report, mean organ doses were converted to 2 Gy/fraction-equivalent doses using the linear-quadratic (LQ) formula with alpha/beta = 3 Gy. The following parameter estimates were obtained for the endpoint of symptomatic RP when the lung is considered a paired organ: m = 0.41 (95% CI 0.38, 0.45) and TD(50) = 29.9 Gy (95% CI 28.2, 31.8). When RP incidence was evaluated as a function of dose to the ipsilateral lung rather than total lung, estimates were m = 0.35 (95% CI 0.29, 0.43) and TD(50) = 37.6 Gy (95% CI 34.6, 41.4). For xerostomia expressed as reduction in stimulated salivary flow below 25% within six months after radiotherapy, the following values were obtained: m = 0.53 (95% CI 0.45, 0.65) and TD(50) = 31.4 Gy (95% CI 29.1, 34.0). Although a large number of parameter estimates for different NTCP models and critical structures exist and continue to appear in the literature, it is hard to justify the use of any single parameter set obtained at a selected institution for the purposes of biologically based treatment planning. Our expectation is that the proposed model parameters based on cumulative experience at various institutions are more representative of the overall practice of radiation therapy than any single-institution data, and could be more readily incorporated into clinical use.     

Sensitivity of NTCP parameter values against a change of dose calculation algorithm

Optimization of radiation treatment planning requires estimations of the normal tissue complication probability (NTCP). A number of models exist that estimate NTCP from a calculated dose distribution. Since different dose calculation algorithms use different approximations the dose distributions predicted for a given treatment will in general depend on the algorithm. The purpose of this work is to test whether the optimal NTCP parameter values change significantly when the dose calculation algorithm is changed. The treatment plans for 17 breast cancer patients have retrospectively been recalculated with a collapsed cone algorithm (CC) to compare the NTCP estimates for radiation pneumonitis with those obtained from the clinically used pencil beam algorithm (PB). For the PB calculations the NTCP parameters were taken from previously published values for three different models. For the CC calculations the parameters were fitted to give the same NTCP as for the PB calculations. This paper demonstrates that significant shifts of the NTCP parameter values are observed for three models, comparable in magnitude to the uncertainties of the published parameter values. Thus, it is important to quote the applied dose calculation algorithm when reporting estimates of NTCP parameters in order to ensure correct use of the models.     

基于自动勾画和快速蒙特卡罗计算的放射治疗全身器官剂量数据库平台的可行性研究

目的:探讨建立一种放射治疗全身器官剂量数据库平台的可行性。方法:使用基于深度学习的自动勾画软件DeepViewer?1例食管癌患者的全身CT上勾画全身器官，然后利用基于GPU加速的蒙特卡罗软件ARCHER计算相应的器官剂量分布，最后利用Lyman-Kutcher-Burman（LKB）模型评估放疗患者正常组织并发症概率（NTCP）。结果:针对该病例，成功建立基于DeepViewer?ARCHER和LKB模型的全身器官剂量数据库，发现距离靶区越近的器官剂量越大，其中心脏与靶区间距离最小，剂量为14.11 Gy，但因其模型参数特殊，通过LKB模型计算的NTCP为0.00%；左、右肺的剂量分别为3.19和1.16 Gy，但是NTCP值却很大，分别为2.13%和1.60%。对于距离靶区较远的头颈部器官（视交叉、视神经和眼）和腹部器官（直肠、膀胱和股骨头）剂量分别约为9和2 mGy，并且NTCP均近似为0.00%。结论:研究结果证明通过自动勾画软件DeepViewer?蒙特卡罗软件ARCHER和LKB模型建立全身器官剂量数据库的可行性。     

Analytical modelling of regional radiotherapy dose response of lung

Knowledge of the dose-response of radiation-induced lung disease (RILD) is necessary for optimization of radiotherapy (RT) treatment plans involving thoracic cavity irradiation. This study models the time-dependent relationship between local radiation dose and post-treatment lung tissue damage measured by computed tomography (CT) imaging. Fifty-eight follow-up diagnostic CT scans from 21 non-small-cell lung cancer patients were examined. The extent of RILD was segmented on the follow-up CT images based on the increase of physical density relative to the pre-treatment CT image. The segmented RILD was locally correlated with dose distribution calculated by analytical anisotropic algorithm and the Monte Carlo method to generate the corresponding dose-response curves. The Lyman-Kutcher-Burman (LKB) model was fit to the dose-response curves at six post-RT time periods, and temporal change in the LKB parameters was recorded. In this study, we observed significant correlation between the probability of lung tissue damage and the local dose for 96% of the follow-up studies. Dose-injury correlation at the first three months after RT was significantly different from later follow-up periods in terms of steepness and threshold dose as estimated from the LKB model. Dependence of dose response on superior-inferior tumour position was also observed. The time-dependent analytical modelling of RILD might provide better understanding of the long-term behaviour of the disease and could potentially be applied to improve inverse treatment planning optimization.     

食管癌患者放射性肺损伤预测因素分析及其与 COPD的相关性研究

目的 分析食管癌患者放射性肺损伤（RILI）预测因素,以及其与慢性阻塞性肺疾病（COPD）的相关性。方法 选取2014年1月~2017年12月我院收治的食管癌患者265例为研究对象,均行立体定向放射治疗（SBRT）治疗,治疗前均行肺功能检查,治疗后均行HRCT检查随访RILI的发生情况,回顾性分析RILI的预测因素及其与COPD是否存在相关性。结果 0、1、2、3、4、5级RP发生率分别为38.49%、38.11%、17.74%、5.28%、0.38%、0,其中12例患有间质性肺疾病的患者,9例（75.00%）发生例3级以上的RILI;发生RILI≥1级的相关因素有年龄、总剂量、V20、GOLD分级;重度及极重度COPD组患者的0级RILI的发生率为54.17%,高于轻中度COPD组（42.31%）及无COPD组（30.22%）。结论 年龄、总剂量、V20、GOLD分级与1级以上（有影像学变化）的RILI有相关性,重度COPD的RILI较正常或轻度COPD患者相对较轻,患有间质性肺疾病的患者多发生3级以上的RILI。     

TCP/NTCP生物模型在胸中上段食管癌调强放疗中的应用

目的:探究TCP/NTCP生物模型在胸中上段食管癌放疗计划优化中的应用及剂量学特点。方法:回顾性分析47例胸中上段食管癌患者,为每位患者制定基于剂量体积（DV）限制的IMRT计划,在DV计划基础上添加对计划靶区（PTV）的TCP（限值90%、95%）生物模型以及危及器官的NTCP（限值10%、5%）模型优化,依次生成[PlanTCP90%]、[PlanTCP95%]、[PlanNTCP10%]、[PlanNTCP5%]4组计划。从剂量学及生物学参数方面评估计划间差异。结果:[PlanTCP90%]、[PlanTCP95%]相比于DV计划,靶区剂量参数均提高（P<0.05）,其中[Dmean]、[D2%]、[D98%]分别提高（2.1%、9.8%）、（1.9%、9.8%）和（1.7%、9.3%）,CI分别降低5%、20%,HI相近,TCP值分别提高2%、7%;危及器官受照剂量均有不同程度提高,[PlanTCP95%]增加更显著（P<0.05）。经TCP优化后的计划仅[PlanTCP90%]满足临床要求;[PlanNTCP5%]与DV计划相比,靶区、心脏相关剂量参数间差异没有统计学意义（P>0.05）,但双肺[Dmean]、[V5 Gy]、[V10 Gy]、[V20 Gy]、NTCP值降低4.4%、1.6%、2.6%、6.2%、0.52%（P<0.05）。[PlanNTCP10%]与DV计划相比,PTV及危及器官相关剂量学参数间差异没有统计学意义（P>0.05）。结论:TCP/NTCP生物学优化可以使靶区及危及器官剂量更符合生物学要求,建议在胸中上段食管癌放疗DV计划优化后引入TCP/NTCP的评估,进而进行选择性的靶向深入优化。     

Using patient data similarities to predict radiation pneumonitis via a self-organizing map

This work investigates the use of the self-organizing map (SOM) technique for predicting lung radiation pneumonitis (RP) risk. SOM is an effective method for projecting and visualizing high-dimensional data in a low-dimensional space (map). By projecting patients with similar data (dose and non-dose factors) onto the same region of the map, commonalities in their outcomes can be visualized and categorized. Once built, the SOM may be used to predict pneumonitis risk by identifying the region of the map that is most similar to a patient's characteristics. Two SOM models were developed from a database of 219 lung cancer patients treated with radiation therapy (34 clinically diagnosed with Grade 2+ pneumonitis). The models were: SOM(all) built from all dose and non-dose factors and, for comparison, SOM(dose) built from dose factors alone. Both models were tested using ten-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Models SOM(all) and SOM(dose) yielded ten-fold cross-validated ROC areas of 0.73 (sensitivity/specificity = 71%/68%) and 0.67 (sensitivity/specificity = 63%/66%), respectively. The significant difference between the cross-validated ROC areas of these two models (p < 0.05) implies that non-dose features add important information toward predicting RP risk. Among the input features selected by model SOM(all), the two with highest impact for increasing RP risk were: (a) higher mean lung dose and (b) chemotherapy prior to radiation therapy. The SOM model developed here may not be extrapolated to treatment techniques outside that used in our database, such as several-field lung intensity modulated radiation therapy or gated radiation therapy.     

正常组织并发症概率模型综述

通过分析肿瘤放疗及并发症随访数据,拟合正常组织并发症概率（NTCP）模型参数,并由此预测并发症发病率、优化放疗方案、揭示正常组织放射生物学特性,是肿瘤放射生物物理学近期的研究热点。综述相关文献中提出的6种NTCP模型,并讨论建模及对比模型预测能力的方法;然后介绍近年来提出的几种改进后的NTCP模型,以及几种新的并发症预测技术。从开展临床应用的角度,对NTCP模型的研究现状、存在的问题和发展趋势做概括和总结,就NTCP模型在个体化放疗中的应用等问题进行讨论和展望。     

非小细胞肺癌三维适形计划和调强计划剂量学比较与分析

目的：通过比较分析非小细胞肺癌（NSCLC）三维适形治疗计划（3DCRT）和调强治疗计划（IMRT）,评价不同计划方案在剂量学上的差异性,确定患者选择合适的放射治疗方式。方法：对20例非小细胞肺癌患者分别制定三维适形治疗计划和调强计划,对它们计划的靶区剂量分布和危及器官的保护进行评估。结果：IMRT治疗计划的以下指标优于相应的3DCRT计划：（1）差异均有统计学意义（P〈0．05）：PTV参数（Dmean、Dmin、Dnex）适形指数（CI）;异质性指数（HI）;平均肺剂量（MLD）、肺V10-V30及肺正常组织并发症发生率（NTCP）;食管Dmean、V55及食管的早晚期正常组织并发症发生概率（NTCP）;心脏V40。（2）差异无统计学意义（P〉0．05）：肺V5;食管V35;心脏的Dmean及NTCP;脊髓的Dmex及NTCP。结论：和三维适形治疗计划相比,调强计划能有效降低危及器官的高剂量区,尤其对靶区形状极不规则的肿瘤有了解决的方案,在保护正常组织器官方面显示出较明显的优势。为靶区剂量提升创造了空间。     

Investigation of the support vector machine algorithm to predict lung radiation-induced pneumonitis

The purpose of this study is to build and test a support vector machine (SVM) model to predict for the occurrence of lung radiation-induced Grade 2+ pneumonitis. SVM is a sophisticated statistical technique capable of separating the two categories of patients (with/without pneumonitis) using a boundary defined by a complex hypersurface. Despite the complexity, the SVM boundary is only minimally influenced by outliers that are difficult to separate. By contrast, the simple hyperplane boundary computed by the more commonly used and related linear discriminant analysis method is heavily influenced by outliers. Two SVM models were built using data from 219 patients with lung cancer treated using radiotherapy (34 diagnosed with pneumonitis). One model (SVM(all)) selected input features from all dose and non-dose factors. For comparison, the other model (SVM(dose)) selected input features only from lung dose-volume factors. Model predictive ability was evaluated using ten-fold cross-validation and receiver operating characteristics (ROC) analysis. For the model SVM(all), the area under the cross-validated ROC curve was 0.76 (sensitivity/specificity = 74%/75%). Compared to the corresponding SVM(dose) area of 0.71 (sensitivity/specificity = 68%/68%), the predictive ability of SVM(all) was improved, indicating that non-dose features are important contributors to separating patients with and without pneumonitis. Among the input features selected by model SVM(all), the two with highest importance for predicting lung pneumonitis were: (a) generalized equivalent uniform doses close to the mean lung dose, and (b) chemotherapy prior to radiotherapy. The model SVM(all) is publicly available via internet access.     

基于CT的影像组学特征同临床物理剂量特征预测肺癌放疗放射性肺炎研究

目的:探讨基于CT的影像组学特征同临床物理剂量特征预测肺癌放疗放射性肺炎研究。方法:回顾性收集2013年1月至2017年1月进行放射治疗的83例肺癌患者的临床物理剂量参数和CT影像以及随访数据。从病例的CT图像中提取107个影像组学特征,结合对应的45个临床物理剂量特征,每例病例共收集152个特征。基于22种特征提取算法和8种分类器构建的176个鉴别模型分析152个特征预测放射性肺炎的准确性以及筛选优势特征的能力。结果:临床物理剂量特征和影像组学特征预测放射性肺炎的鉴别模型中AUC值最高为0.90。前5位的优势特征是:shape_Maximum2DDiameterColumn、shape_Maximum3DDiameter、V20、glcm_Imc1、V45。结论:临床物理剂量特征和影像组学特征通过不同分类器和特征选择算法组合的鉴别模型,可以筛选出理想的鉴别模型以及优势预测特征。     

计划轮照在肺癌三维适形放疗中剂量学的研究

目的：比较肺癌三维适形放疗（3DCRT）两种治疗方案之间的差异,以期减少正常组织损伤。方法：选择9例病理证实的原发性肺癌,为每个病例设计两套治疗计划,计划1、计划2,每套计划均采用5个非等角共面野等中心照射,要求计划1和计划2在靶区（GTV、CTV）内的剂量分布是等同的,但每套计划的射野入射方向彼此不同。通过添加不同楔形角度的楔形板、调整射野人射的方向、权重等,使计划1与计划2满足临床要求。在治疗计划系统（TPS）中模拟,方案1：计划1与计划2独立照射,处方剂量皆为60Gy,每次2Gy;方案2：计划1与计划2每天轮照,处方剂量皆为30Gy,每次2Gy。将方案1与方案2比较。结果：两方案治疗计划GTV的Dmax、Dmin和Dmean的均数没有显著性差异（P〉0．05）;HI、CI值的均数没有显著性差异（P〉0．05）;脊髓Dmax、食管V50心脏V40,两肺V20,V5、Dmean的均数没有显著性差异（P〉0．05）。但是方案2的肺正常组织并发症概率（NTCP）小于方案1。有显著性差异（P〈0．05）。结论：方案2每天轮照,因卷入射野内的正常组织有一天以上的休息和对损伤的修复时间,在肿瘤剂量一定的情况下,可减少正常组织损伤。     

周围型肺癌立体定向放射治疗中采用实体肿瘤靶区推量技术的可行性研究——基于剂量学分析

目的：通过研究周围型肺癌立体定向放射治疗中提高肿瘤靶区最高剂量对剂量限制参数和正常器官剂量的影响，探讨使用实体肿瘤靶区推量技术的可行性，为临床治疗提供剂量学参考依据。方法：收集19例周围型早期肺癌患者的CT图像资料，重新设计放射治疗计划，初始治疗计划在满足放射治疗肿瘤协作组（RTOG）0915号报告关于剂量限制参数的情况下，以2 Gy的剂量爬升梯度分别对肿瘤靶区进行提量，共得到5组治疗计划。结果：5组计划的剂量限制参数均能满足RTOG0915号报告要求。5组计划的剂量限制参数和正常器官剂量无显著差异，但是肿瘤靶区最高剂量存在显著差异（P<0.05），最高和最低剂量组剂量差异可达6.6 Gy。结论：提高肿瘤靶区最高剂量对剂量限制参数和正常器官剂量没有显著影响。由于提高靶区内最高剂量会直接影响肿瘤的局部控制率，因此在满足剂量限制参数的前提下，建议使用实体肿瘤靶区推量技术以提高肿瘤靶区内的最高剂量。     

不同分割剂量同步推量调强放疗治疗肺癌脑转移瘤的安全性分析

目的:分析不同分割剂量同步推量调强放疗治疗肺癌脑转移瘤的安全性及生存情况。方法:选取肺癌脑转移瘤患者75例,随机分为3组,均实施同步推量调强放疗,其中A组放疗方案为全脑40 Gy/20f（2.0 Gy/f）+瘤区同步推量46 Gy/20f（2.3 Gy/f）,B组方案为全脑40 Gy/20f（2.0 Gy/f）+瘤区同步推量52 Gy/20f（2.6 Gy/f）,C组方案为全脑40 Gy/20f（2.0 Gy/f）+瘤区同步推量58 Gy/20f（2.9 Gy/f）。放疗开始后,对3组患者危及器官（眼球、晶体、视神经、脑干）平均剂量及最大剂量和3组患者放疗相关不良反应进行比较。治疗结束后定期复查颅脑MRI评价疗效,观察3组患者1年生存率。结果:A、B、C组危及器官平均剂量及最大剂量差异不显著（P>0.05）;A、B、C组急性放疗不良反应发生率差异不显著（P>0.05）,晚期神经系统不良反应发生率亦差异不显著（P>0.05）,3级放疗不良反应低于5%,无4级放疗不良反应发生。随访1年,C组生存率高于A、B组（P<0.05）。结论:同步推量调强放疗治疗肺癌脑转移瘤是一种安全有效的方法,随着放疗剂量增加,疗效有增加趋势。     

肿瘤精确放疗新进展——图像引导自适应放疗

图像引导自适应放疗(ART)是一种新型的肿瘤精确放疗技术,它是继三维适形放疗(3D-CRT)和三维调强放疗(IM-RT)之后,随着图像引导放疗(IGRT)的普遍应用而发展起来的。ART可以较好地解决放疗分次间的靶区位置和形态变化问题,适用于各种部位的肿瘤。对于鼻咽癌患者和(或)体重明显下降的头颈部肿瘤患者,采用ART可使PTV的边界缩小,减少腮腺等危及器官所受剂量,降低放疗毒副反应。对于胸腹部肿瘤,ART可有效解决分次治疗间的靶区运动问题,在提高肿瘤照射剂量的同时有效降低同侧正常肺组织的受照剂量,使肺毒性降到最低。前列腺癌由于受膀胱和直肠充盈程度的影响,靶区的变形有时会比较大,采用ART可显著降低直肠副反应发生的概率,也可消除直肠扩张对治疗的影响。而对膀胱癌和宫颈癌患者进行分次治疗时,采用在线ART技术更新治疗计划,可明显减少肿瘤靶区周围危及器官的辐射剂量,保护直肠和大肠等危及器官,从而降低放射性直肠炎、放射性膀胱炎等放疗并发症的发生概率。     

不同剂量调强放疗联合同步化疗对局部晚期肺癌患者生存期和毒副反应的影响

目的:探讨不同剂量调强放疗联合同步化疗对局部晚期肺癌患者生存期和毒副反应的影响。方法:选取96例确诊为局部晚期肺癌患者为研究对象,随机分为对照组（n=48）和观察组（n=48）。对照组采用62 Gy调强放疗联合PC同步化疗,观察组调整放疗剂量为50 Gy。记录患者临床一般资料。K-M分析绘制生存曲线,Log Rank [χ2]检验比较生存率,记录两组患者治疗1个月后毒副反应发生情况。结果:观察组和对照组患者缓解率无显著差异（75.00% vs79.17%, P>0.05）;观察组患者总生存率和无进展生存率均高于对照组（P<0.05）,中位生存时间显著长于对照组（P<0.05）。观察组骨髓抑制和放射性肺炎等放疗毒副反应发生率显著低于对照组（P<0.05）。结论:通过降低调强放疗剂量能够减轻患者毒副反应,提高患者生存期,联合同步化疗能够发挥良好的临床缓解效应。