8. 剂量不确定度的估计和表示

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引用次数: 0

摘要

大多数放射治疗患者的做法仍然是制定治疗计划,因此在整个治疗过程中使用,通常为25-30分。这导致了与制定治疗计划(成像治疗计划、轮廓、剂量计算)相关的许多系统不确定性。即使这种做法随着自适应概念的引入而逐渐改变,上述系统不确定性也适用于使用该计划的分数的数量。第二类不确定度是随机性质的,可分为干涉不确定度和干涉不确定度。大多数这些随机的不确定性在分数的数量上会显示出平均的趋势。所有不确定因素加在一起将不可避免地导致给药剂量与规定吸收剂量之间的偏差。例如,随机设置的不确定性将导致传递剂量的涂抹,但不会导致剂量分布的移位。然而,如果不加以纠正,靶点定义中的系统误差将导致随后所有分数中剂量分布的系统偏移。在离子束治疗中,由于两个原因,不确定性起着更重要的作用。首先,交付的分数数量较少,这可能导致随机不确定性的影响较大。其次,广泛使用的rbe加权剂量计算需要使用输入参数固有较大不确定性的生物模型。因此,离子束治疗的不确定性将在下面更详细地讨论。由于潜在生物过程的性质及其变化,器官或肿瘤对辐射剂量的反应是不能完全预测的。只有从一组患者中,才能从统计上得出影响结果的有意义的参数。除了这些固有的概率效应之外,还有与放射生物学效应所依赖的基本物理和临床参数有关的不确定性。为了从离子束的应用中获得有意义的临床结果,这些参数应该被指定和控制,如果可能的话,保持在合理的精度和不确定度水平。这些参数中的一些原则上可以通过测量来确定,而另一些则很难精确确定。在后者中,有所有的治疗参数,这些参数是通过放射肿瘤学家的经验和专业知识定义的。这些都是:
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8. Estimation and Presentation of Uncertainty in the Delivered Dose
The practice for most patients in radiotherapy is still to generate a treatment plan, which is consequently used over the entire course of therapy, typically for 25–30 fractions. This leads to a number of systematic uncertainties associated with the generation of a treatment plan (imaging for treatment planning, contouring, dose calculation). Even as this practice gradually changes with the introduction of adaptive concepts, the mentioned systematic uncertainties apply to the number of fractions for which the plan is used. A second category of uncertainties is of random nature and can be separated into interfraction and intrafraction uncertainties. Most of these random uncertainties will show a tendency to average out over the number of fractions. All uncertainties taken together will inevitably lead to deviations between the delivered dose and the prescribed absorbed dose. For example, a random setup uncertainty will lead to a smearing out of the delivered dose but not to a shift of the dose distribution. A systematic error in the definition of the target point, however, will lead to a systematic shift of the delivered dose distribution in all subsequent fractions if not corrected. In ion-beam therapy uncertainties play a more important role for two reasons. First, a lower number of fractions is delivered, which may lead to a larger impact of random uncertainties. Second, the calculation of RBE-weighted dose, which is widely used, necessitates the use of biological models with inherently larger uncertainties in the input parameters. Consequently, the uncertainties involved in ion-beam therapy will be discussed below in more detail. Due to the nature of the underlying biological processes and their variations, the response of an organ or tumor to a radiation dose is not completely predictable. Only from a group of patients, meaningful parameters, that affect the outcome, can be derived statistically. In addition to these inherently probabilistic effects, there are also uncertainties connected to the underlying physical and clinical parameters on which the biological effects of radiation are dependent. To derive meaningful clinical results from the application of ion beams, these parameters should be specified, controlled, and if possible, kept to a reasonable accuracy and uncertainty level. Some of these parameters can, in principle, be determined by measurements while others are more difficult to determine precisely. Among the latter, there are all the treatment parameters, which are defined through the experience and expertise of the radiation oncologist. These are:
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ICRU Report 98, Stochastic Nature of Radiation Interactions: Microdosimetry ICRU REPORT 97: MRI-Guided Radiation Therapy Using MRI-Linear Accelerators Dosimetry-Guided Radiopharmaceutical Therapy Glossary of Terms and Definitions of Basic Quantities 5 Practical Consequences of the Introduction of the Recommended Operational Quantities
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