利用DVH图分析鼻咽癌调强放疗中正常器官体积剂量的变化

目的：应用剂量体积直方图（DVH）,研究鼻咽癌患者在放疗过程中正常器官体积及剂量的变化。方法：接受全程调强放疗（IMRT）的20例初治鼻咽癌患者,在治疗20次时,按原固定体位和参考坐标重新CT扫描,设计计划,与原计划进行比较DVH图中正常器官（眼球、晶状体、视神经、腮腺、脊髓及脑干）体积剂量的变化。结果：DVH2上左右腮腺体积明显小于DVH1（P〈0.05）,左右腮腺和脊髓的最大剂量和平均剂量明显增加,脑干最大剂量变化有统计学意义（P=0.011）,其中腮腺的剂量增加与放疗所致的腮腺缩小程度有一定相关性,其余无统计意义。结论：鼻咽癌IMRT过程中正常器官（特别是腮腺）体积剂量会发生一些变化,建议放疗中后期有必要重新勾画靶区,重新计划,减小正常器官的受照量,减少放疗反应。     

利用DVH图分析鼻咽癌调强放疗中正常器官体积剂量的变化

目的:应用剂量体积直方图(DVH),研究鼻咽癌患者在放疗过程中正常器官体积及剂量的变化.方法:接受全程调强放疗(IMRT)的20例初治鼻咽癌患者,在治疗20次时,按原固定体位和参考坐标重新CT扫描,设计计划,与原计划进行比较DVH图中正常器官(眼球、晶状体、视神经、腮腺、脊髓及脑干)体积剂最的变化.结果:DVH2上左右腮腺体积明显小于DVH1(P＜0.05),左右腮腺和脊髓的最大剂量和平均剂量明显增加,脑干最大剂量变化有统计学意义(P=0.011),其中腮腺的剂量增加与放疗所致的腮腺缩小程度有一定相关性,其余无统计意义.结论:鼻咽癌IMRT过程中正常器官(特别是腮腺)体积剂量会发生一些变化,建议放疗中后期有必要重新勾画靶区,重新计划,减小正常器官的受照量,减少放疗反应.     

基于核密度估计的自动计划研究

目的 研究利用患者解剖结构信息预测DVH并实施自动计划的方法,并应用于临床实践。方法 本研究采用了统计学中的核密度估计方法,利用治疗计划数据库中的相关信息可在计划设计之前根据患者解剖结构预测OAR的DVH。将DVH预测结果转化为计划设计时的目标函数,结合Pinnacle TPS的Auto-plan技术高效制定出临床上可接受的治疗计划。Auto-plan和手动计划、预测值与实际值比较行配对t检验。结果 直肠癌、乳腺癌和鼻咽癌各10例患者危及器官DVH的预测结果显示,重要临床剂量点预测值与实际值的平均值的偏差<5%(P>0.05)。对10例乳腺癌患者运用Auto-plan进行计划的重新设计,结果显示心脏剂量降低明显,靶区覆盖率有所提高,与预测结果是一致的。结论 DVH预测方法可以实现患者DVH的准确预测,与Auto-plan技术结合可制定出临床可接受的治疗计划。     

基于EUD的鼻咽癌VMAT计划危及器官DVH预测方法

目的评估通过最小化基于等效均匀剂量(EUD)的损失函数优化放疗计划中危及器官(OAR)剂量体积直方图(DVH)预测方法的实用性。方法随机选取2020—2021年在中国医学科学院肿瘤医院深圳医院完成鼻咽癌容积调强弧形治疗(VMAT)的66例患者的治疗计划, 其中50例用于训练循环神经网络(RNN)模型, 其余16例用于测试模型。研究基于RNN构建了DVH预测模型, 并为66例患者均设计了一个9野等权重的三维适形计划。训练时将OAR每个分野对应的DVH作为模型输入, VMAT计划的DVH为预期输出, 通过最小化基于EUD的损失函数计算的预测误差训练模型。预测准确度用预测值和真实值之间的平均偏差和标准偏差表示。根据DVH预测结果为测试病例重新优化计划, 使用Wilcoxon配对检验和箱线图比较新计划和原计划OAR的EUD和感兴趣DVH参数(如脊髓等串型器官的最大剂量)的一致性和差异性。结果基于EUD的损失函数训练得到的神经网络能够得到更好的DVH预测结果。根据预测DVH得到的新计划与原计划具有很好的一致性:在绝大多数情况下, 两组计划的计划靶区(PTV)的D98%都大于95%处方剂量, 脑干...     

前列腺癌碳离子治疗直肠剂量体积直方图预测模型

目的 基于日本经验建立局部效应模型(LEM)下前列腺癌碳离子治疗直肠剂量体积直方图(DVH)预测模型,为临床降低直肠不良反应发生率提供参考。方法 收集局限期前列腺癌患者计划CT图像 76例,采用微剂量动力模型(MKM)进行治疗计划;然后,基于与MKM计划相同的射野,采用LEM重新计算生物剂量获得LEM计划,并在LEM计划中提取直肠几何特征及DVH参数。采用线性回归法对其中 61例计划信息进行建模,余 15例计划用于验证。结果 61例患者计划靶体积沿左右方向外扩1cm后与直肠交叠部分体积同直肠体积比值可作为预测直肠DVH的特征参数。15例患者预测DVH同LEM计划DVH的拟合度优(R²=0.964),基于预测DVH进一步预测直肠不良反应与基于LEM计划DVH预测直肠不良反应的结果一致。结论 线性回归方法可建立较为准确的前列腺癌碳离子治疗直肠DVH预测模型,可能为临床降低直肠不良反应发生率提供一定参考,还有待于临床大样本数据进一步验证。     

基于危及器官DVH预测模型的前列腺癌自动计划研究

目的 评估利用危及器官DVH预测模型来实现前列腺癌自动计划的可行性。方法 从42例前列腺癌放疗计划数据库随机选择30例作为训练集,根据膀胱、直肠与靶区边界的空间距离将其依次分割成层厚为3 mm的亚体积元(Ai),采用偏正态高斯函数拟合各Ai的微分DVH,优化得微分DVH的精确数学模型;利用嵌入在Pinnacle脚本中的C⁺⁺子程序获取另外12例验证集患者OARs的各Ai体积,基于建立的数学模型预测各OARs的DVH参数,将其作为目标函数生成个性化Pinnacle脚本实现自动计划。配对t检验比较原临床计划、预测值和自动计划的剂量差异。结果 DVH预测结果显示其膀胱、直肠60 Gy以上剂量的体积分数均低于原临床计划;自动计划的膀胱V70、V60、V50以及直肠V70、V60值均比原临床计划明显降低(P<0.05),但靶区的覆盖率和适形度基本不变,均匀性略降低(P>0.05)。结论 基于危及器官DVH预测模型的前列腺癌自动计划降低了OARs照射剂量,提高治疗计划设计效率。     

早期非小细胞肺癌立体定向放疗肺剂量预测研究

目的 研究基于机器学习算法的早期非小细胞肺癌立体定向放疗肺剂量预测方法和应用于计划质量控制的可行性。方法 利用机器学习算法实现剂量预测。首先,建立专家计划库,提取计划库中的几何特征信息、照射野角度和剂量体积直方图(DVH)参数,在几何及照射野特征和DVH之间建立相关模型;其次,提取专家库外10例患者的几何和照射野特征信息,利用模型预测可实现的DVH值,并将其与实际计划结果比较。结果 10例患者肺平均剂量和V20外部验证的均方根误差分别为91.95 cGy和3.12%。对肺受量高于预测剂量的2例计划进行修改,修改后肺剂量均有所降低。结论 对非小细胞肺癌患者制定立体定向放疗计划前,可根据相关数学模型提前预测肺DVH曲线作为计划评估标准,从而保证治疗计划的质量。     

早期非小细胞肺癌立体定向放疗肺剂量预测研究

目的 研究基于机器学习算法的早期非小细胞肺癌立体定向放疗肺剂量预测方法和应用于计划质量控制的可行性。方法 利用机器学习算法实现剂量预测。首先,建立专家计划库,提取计划库中的几何特征信息、照射野角度和剂量体积直方图(DVH)参数,在几何及照射野特征和DVH之间建立相关模型;其次,提取专家库外10例患者的几何和照射野特征信息,利用模型预测可实现的DVH值,并将其与实际计划结果比较。结果 10例患者肺平均剂量和V20外部验证的均方根误差分别为91.95 cGy和3.12%。对肺受量高于预测剂量的2例计划进行修改,修改后肺剂量均有所降低。结论 对非小细胞肺癌患者制定立体定向放疗计划前,可根据相关数学模型提前预测肺DVH曲线作为计划评估标准,从而保证治疗计划的质量。     

应用核密度估计方法预测妇科肿瘤放疗骨髓剂量研究

目的 基于核密度估计方法预测妇科肿瘤患者骶尾骨和盆骨骨髓剂量。方法 选取中国医科大学附属盛京医院治疗的15例妇科肿瘤限制骶尾骨和盆骨骨髓剂量的放疗计划作为机器学习的训练数据,另选取10例该类计划作为模型的验证数据,计算器官内各剂量点与计划靶区边缘的最小有向距离。应用核密度估计方法训练模型,并用均方根差来评估模型预测的准确性。使用该模型预测实际计划的骶尾骨和盆骨骨髓剂量,对预测的剂量体积直方图(DVH)和实际结果进行线性拟合,使用拟合优度R2来评估模型预测效果。结果 在计划要求的DVH参数上,模型预测与验证计划较为接近:盆骨V40Gy差为2.0%,平均剂量差为1.6Gy,骶尾骨V10Gy差为-0.4%。在非计划要求的DVH参数上,模型预测值除盆骨V10Gy外,其余参数值均明显偏高。在实际病例应用中,模型预测的DVH与最终计划的差异很小,骶尾骨和盆骨骨髓的R2分别为0.988和0.995。结论 使用基于核密度估计方法的模型可以较准确预测骶尾骨和盆骨骨髓剂量,通过模型预测剂量也可以作为一种保障计划质量的方法,提高计划的一致性和质量。     

晚期鼻咽癌RapidArc与固定野调强放疗的比较研究

  目的  近年RapidArc的临床应用已引起越来越多的关注, 本研究比较RapidArc与固定野调强放射治疗(IMRT)两种放疗技术在晚期鼻咽癌治疗计划中的差异。  方法  随机选取10例晚期鼻咽癌患者, 采用RapidArc与IMRT两种技术进行计划设计与剂量验证, 比较计划的靶区剂量、危及器官与正常组织剂量、机器跳数、治疗时间与剂量验证结果。  结果  两种计划的剂量分布基本一致, 均能提供足够的靶区剂量。RapidArc的PTVnx最小剂量, PTVnd、PTV60、喉、腮腺的平均剂量低于IMRT, PTV60的HI值高于IMRT, 机器跳数比IMRT减少约58%, 治疗时间减少约70%。以3%/3mm为界, RapidArc验证的γ指数通过率为(98.75±0.50)%, IMRT的通过率为(98.86±0.67)%。  结论  两种放疗技术均能够满足临床治疗需要, 剂量验证结果能够较好的符合计划计算结果。RapidArc比IMRT有着更多的优势, 不仅可以减少机器跳数, 缩短治疗时间, 而且可以减少喉、腮腺的受照剂量。      

Principal component analysis-based pattern analysis of dose-volume histograms and influence on rectal toxicity

PURPOSE: The variability of dose-volume histogram (DVH) shapes in a patient population can be quantified using principal component analysis (PCA). We applied this to rectal DVHs of prostate cancer patients and investigated the correlation of the PCA parameters with late bleeding. METHODS AND MATERIALS: PCA was applied to the rectal wall DVHs of 262 patients, who had been treated with a four-field box, conformal adaptive radiotherapy technique. The correlated changes in the DVH pattern were revealed as "eigenmodes," which were ordered by their importance to represent data set variability. Each DVH is uniquely characterized by its principal components (PCs). The correlation of the first three PCs and chronic rectal bleeding of Grade 2 or greater was investigated with uni- and multivariate logistic regression analyses. RESULTS: Rectal wall DVHs in four-field conformal RT can primarily be represented by the first two or three PCs, which describe approximately 94% or 96% of the DVH shape variability, respectively. The first eigenmode models the total irradiated rectal volume; thus, PC1 correlates to the mean dose. Mode 2 describes the interpatient differences of the relative rectal volume in the two- or four-field overlap region. Mode 3 reveals correlations of volumes with intermediate doses ( approximately 40-45 Gy) and volumes with doses >70 Gy; thus, PC3 is associated with the maximal dose. According to univariate logistic regression analysis, only PC2 correlated significantly with toxicity. However, multivariate logistic regression analysis with the first two or three PCs revealed an increased probability of bleeding for DVHs with more than one large PC. CONCLUSIONS: PCA can reveal the correlation structure of DVHs for a patient population as imposed by the treatment technique and provide information about its relationship to toxicity. It proves useful for augmenting normal tissue complication probability modeling approaches.     

三种智慧放疗计划预测模型的性能评价

目的比较三种智慧放疗计划预测模型的精度与泛化鲁棒性,为模型选择提供依据。方法收集45例前列腺癌和25例鼻咽癌临床放疗计划,运用Z、L、S模型预测前列腺癌中膀胱和直肠、鼻咽癌中左右腮腺的剂量体积直方图(DVH)。应用预测DVH与临床DVH曲线下面积的差别(|DVH预测-DVH临床|)评价预测误差,误差越小则预测精度越高。在单个危及器官(OAR)上比较3种预测模型的精度,并在不同OAR中计算各模型预测精度的标准差以评价和比较模型的泛化鲁棒性。结果对于膀胱和直肠,L模型的预测误差(0.114和0.163)显著大于Z和S模型(≤0.071,P<0.05);对于左腮腺,S模型的预测误差(0.033)与Z和L模型相近(≤0.025,P>0.05);对于右腮腺,S模型的预测误差(0.033)显著大于Z和L模型(≤0.028,P<0.05)。在不同OAR上,S模型的预测精度标准差比Z、L模型小(分别为0.016、0.018和0.060)。结论在前列腺癌膀胱和直肠的DVH预测中Z和S模型的精度较高,而在鼻咽癌左右腮腺中Z和L模型较高,在不同OAR上S模型的泛化鲁棒性相对较好。     

鼻咽癌调强放疗根据CT和MRI勾画腮腺的比较研究

目的 对鼻咽癌调强放疗的患者,在调强放疗的计划设计中,分别以MR及CT作为标准,勾画腮腺,比较其所勾画的腮腺体积差别及其对三维调强适形放疗(IMRT)计划中腮腺DVH的影响.方法 2008年5月至2008年11月间,20例实施根治性调强放疗的鼻咽癌患者,在放射治疗前1周行MR及增强定位CT扫描,并输入OTP治疗计划系统.然后将20例患者的CT影像及MR影像随机分成4组,由4名放疗科医师分别勾画其腮腺范围.之后将同一患者的CT及MR图像进行融合,评价所勾画的腮腺的体积差异,以CT为标准进行调强放疗计划设计,然后对比两种影像所勾画的腮腺的DVH的差别.结果 以CT和MRI为参照标准勾画的腮腺平均体积分别为(24.53±1.96×7.23)、(31.75± 1.96×12.05)cm3 ;V30 分别为(39.29± 1.96×9.30)%、(47.73±1.96×9.54)%;D50分别为(2 716±1.96×220)、(3 000 ±1.96×339)cGy.结论 以MR为标准勾画腮腺范围及体积较为准确,其与CT之差异主要集中在腮腺深叶及腮腺管、副腮腺区.以CT为标准勾画腮腺可能"遗漏"部分腮腺范围,并可能影响IMRT计划中部分腮腺的V30及D50评价的准确性.     

放疗计划自动分析系统的开发研究

目的开发一款放疗计划自动分析系统,通过智能解析Pinnacle3治疗计划系统(TPS)的治疗计划底层数据,实现放疗计划剂量参数的自动化分析。方法将12例接受放射治疗的食管癌患者的治疗计划纳入研究。自动分析系统自动检索Pinnacle3 TPS数据库,获取12例治疗计划原始数据,并自动解析底层原始数据,重建轮廓、射野和剂量参数,并重新计算剂量分布和"剂量-体积"直方图。通过与在线TPS中原始计划输出体积和剂量数据进行对比,来评估新系统重新计算体积和剂量数据的准确性。结果自动分析系统成功解析治疗计划的底层数据,并重建治疗计划参数。新系统计算轮廓的体积与原计划的体积偏差≤0.1%;重新计算GTV、PGTV、CTV和PTV的Dmax、Dmean、D95和D50等参数,与原计划的剂量偏差≤1.0%;重新计算ROIs的Dmax和Dmean,与原计划的剂量偏差<5%。结论自动分析系统可直接分析Pinnacle3 TPS治疗计划的底层数据,重建治疗计划,计算轮廓体积和剂量参数,与原计划的剂量偏差满足临床要求。     

Importance of accurate dose calculations outside segment edges in intensity modulated radiotherapy treatment planning.

BACKGROUND AND PURPOSE: To assess the effect of differences in the calculation of the dose outside segment edges on the overall dose distribution and the optimisation process of intensity modulated radiation therapy (IMRT) treatment plans. PATIENTS AND METHODS: Accuracy of dose calculations of two treatment planning systems (TPS1 and TPS2) was assessed, to ensure that they are both suitable for IMRT treatment planning according to published guidelines. Successively, 10 treatment plans for patients with prostate and head and neck tumours were calculated in both systems. The calculations were compared in selected points as well as in combination with volumetric parameters concerning the planning target volume (PTV) and organs at risk. RESULTS: For both planning systems, the calculations agree within 2.0% or 3 mm with the measurements in the high-dose region for single and multiple segment dose distributions. The accuracy of the dose calculation is within the tolerances proposed by recent recommendations. Below 35% of the prescribed dose, TPS1 overestimates and TPS2 underestimates the measured dose values, TPS2 being closer to the experimental data. The differences between TPS1 and TPS2 in the calculation of the dose outside segments explain the differences (up to 50% of the local value) found in point dose comparisons. For the prostate plans, the discrepancies between the TPS do not translate into differences in PTV coverage, normal tissue complication probability (NTCP) values and results of the plan optimisation process. The dose-volume histograms (DVH) of the rectal wall differ below 60 Gy, thus affecting the plan optimisation if a cost function would operate in this dose region. For the head and neck cases, the two systems give different evaluations of the DVH points for the PTV (up to 22% differences in target coverage) and the parotid mean dose (1.0-3.0 Gy). Also the results of the optimisation are influenced by the choice of the dose calculation algorithm. CONCLUSIONS: In IMRT, the accuracy of the dose calculation outside segment edges is important for the determination of the dose to both organs at risks and target volumes and for a correct outcome of the optimisation process. This aspect should therefore be of major concern in the commissioning of a TPS intended for use in IMRT. Fulfilment of the accuracy criteria valid for conformal radiotherapy is not sufficient. Three-dimensional evaluation of the dose distribution is needed in order to assess the impact of dose calculation accuracy outside the segment edges on the total dose delivered to patients treated with IMRT.     

Dose-Volume Histograms for bladder and rectum

: A careful examination of the foundation upon which the concept of the Dose-Volume Histogram (DVH) is built, and the implications of this set of parameters on the clinical application and interpretation of the DVH concept has not been conducted since the introduction of DVHs as a tool for the quantitative evaluation of treatment plans. The purpose of the work presented herein is to illustrate problems with current methods of implementing and interpreting DVHs when applied to hollow anatomic structures such as the bladder and rectum.

: A typical treatment plan for external beam irradiation of a patient with prostate cancer was chosen to provide a data set from which DVH curves for both the bladder and rectum were calculated. The two organs share the property of being shells with contents that are of no clinical importance. DVHs for both organs were computed using a solid model and using a shell model. Typical treatment plans for prostate cancer were used to generate DVH curves for both models. The Normal Tissue Complication Probability (NTCP) for these organs is discussed in this context.

: For an eight-field conformal treatment plan of the prostate, a bladder DVH curve generated using the shell model is higher than the corresponding curve generated using the solid model. The shell model also has a higher NTCP. A six-field conformal treatment plan slo results in a higher DVH curve for the shell model. A treatment plan consisting of bilateral 120-degree arcs, results in a higher DVH curve for the shell model, as well as a higher NTCP.

: The DVH concept currently used in evaluation of treatment plans is problematic because current practices of defining exactly what constitutes “bladder” and “rectum.” Commonly used methods of tracing the bladder and rectum imply use of a solid structure model for DVHs. In reality, these organs are shells and the critical structure associated with NTCP is obviously and indisputably the shell, as opposed to its contents. Treatment planning algorithms for DVH computation should thus be modified to utilize the shell model for these organs.     

Normal tissue complication probabilities: dependence on choice of biological model and dose-volume histogram reduction scheme

PURPOSE: To evaluate the impact of dose-volume histogram (DVH) reduction schemes and models of normal tissue complication probability (NTCP) on ranking of radiation treatment plans. METHODS AND MATERIALS: Data for liver complications in humans and for spinal cord in rats were used to derive input parameters of four different NTCP models. DVH reduction was performed using two schemes: "effective volume" and "preferred Lyman". DVHs for competing treatment plans were derived from a sample DVH by varying dose uniformity in a high dose region so that the obtained cumulative DVHs intersected. Treatment plans were ranked according to the calculated NTCP values. RESULTS: Whenever the preferred Lyman scheme was used to reduce the DVH, competing plans were indistinguishable as long as the mean dose was constant. The effective volume DVH reduction scheme did allow us to distinguish between these competing treatment plans. However, plan ranking depended on the radiobiological model used and its input parameters. CONCLUSIONS: Dose escalation will be a significant part of radiation treatment planning using new technologies, such as 3-D conformal radiotherapy and tomotherapy. Such dose escalation will depend on how the dose distributions in organs at risk are interpreted in terms of expected complication probabilities. The present study indicates considerable variability in predicted NTCP values because of the methods used for DVH reduction and radiobiological models and their input parameters. Animal studies and collection of standardized clinical data are needed to ascertain the effects of non-uniform dose distributions and to test the validity of the models currently in use.     

基于预测可行性DVH的肝癌VMAT自动计划方法研究

目的 建立基于预测可行性剂量体积直方图(DVH)的肝癌容积调强弧形治疗(VMAT)自动计划方法,并评价其性能。方法 回顾性随机选取10例放疗肝癌病例。采用Pinnacle Auto-Planning设计VMAT自动计划,通过PlanIQ剂量预测得到可行性DVH曲线,并根据其显示的可行性目标区间设置自动计划的初始优化目标。评价计划靶体积、正常肝和其他危及器官的剂量参数以及机器跳数,并与临床手工计划行配对t检验。结果 自动计划和手工计划的计划靶体积D2%、D98%、Dmean和均匀度指数相近[(58.55±2.81) Gy∶(57.98±4.17) Gy、(47.15±1.58) Gy∶(47.82±1.38) Gy、(53.14±0.95) Gy∶(53.44±1.67) Gy和1.15±0.05∶1.14±0.07,P均>0.05],手工计划的计划靶体积适形指数略高于自动计划(0.77±0.08∶0.69±0.06,P<0.05)。自动计划的肝V30Gy、V20Gy、V10Gy、V5Gy和V<5Gy显著优于手工计划[(26.68±11.13)%∶(28.00±10.95)%、(29.96±11.50)%∶(31.89±11.51)%、(34.88±11.51)%∶(38.66±11.67)%、(45.38±12.40)%∶(50.74±13.56)%和(628.52±191.80) cm³∶(563.15±188.39) cm³,P均<0.05],自动计划的小肠、十二指肠、心脏Dmean以及全肺V10Gy低于手工计划[(1.83±2.17) Gy∶(2.37±2.81) Gy、(9.15±9.36) Gy:(11.18±10.49) Gy、(5.44±3.10) Gy∶(6.25±3.26) Gy以及(12.70±7.08)%∶(14.47±8.11)%,P均<0.05]。两种计划的机器跳数相近[(710.67±163.72) MU∶(707.53±155.89) MU,P>0.05]。结论 基于预测可行性DVH的肝癌VMAT自动计划方法能提高计划质量,更好保护正常肝,对小肠、十二指肠、全肺和心脏的保护也有优势。