INTEGRATION OF MULTIMODALITY IMAGING DATA FOR RADIOTHERAPY TREATMENT PLANNING
INTEGRATION OF MULTIMODALITY IMAGING DATA FOR RADIOTHERAPY TREATMENT PLANNING
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DOI：
10.1016/0360-3016(91)90345-5
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发表时间：
1991-11-01
影响因子：
7
通讯作者：
CASTRO, JR
中科院分区：
文献类型：
--
作者：
KESSLER, ML;PITLUCK, S;CASTRO, JR
本文描述了允许磁共振 (MR)、正电子发射断层扫描 (PET) 和 X 射线计算机断层扫描 (CT) 成像数据集定量集成的计算技术。 这些方法用于将 PET 和 MR 成像提供的独特诊断信息纳入基于 CT 的颅内肿瘤和血管畸形放射治疗计划中。 来自不同成像方式的信息的整合被视为一个两步过程。 第一步是确定与两个成像数据集的坐标相关的几何参数集。 由于当代成像方法和数据格式的多样性，没有适合确定这些参数的通用方法。 大多数情况可以通过所描述的四种不同技术之一来处理。 这四种方法利用两个数据集中包含的特定几何对象来确定参数。 这些对象是：（a）解剖和/或基准点，（b）附着的线标记，（c）解剖表面，以及（d）解剖结构的轮廓。 第二步涉及使用导出的变换将一个成像研究图像上绘制的治疗体积和/或解剖结构的轮廓传输到另一研究（通常是治疗计划 CT）的图像。 实体建模和图像处理技术已得到进一步调整和发展来完成这项任务。 提出了临床实例和模型研究，验证了这些技术的不同方面并证明了它们应用的准确性。 这些技术在临床上用于治疗计划已经改善了治疗体积和大脑关键结构的定位。 这些改进可以更好地保护正常组织，并将能量更精确地输送到所需的照射体积。 人们相信这些改进将对放射治疗的结果产生积极的影响。
This paper describes computational techniques to permit the quantitative integration of magnetic resonance (MR), positron emission tomography (PET), and x-ray computed tomography (CT) imaging data sets. These methods are used to incorporate unique diagnostic information provided by PET and MR imaging into CT-based treatment planning for radiotherapy of intracranial tumors and vascular malformations. Integration of information from the different imaging modalities is treated as a two-step process. The first step is to determine the set of geometric parameters relating the coordinates of two imaging data sets. No universal method for determining these parameters is appropriate because of the diversity of contemporary imaging methods and data formats. Most situations can be handled by one of the four different techniques described. These four methods make use of specific geometric objects contained in the two data sets to determine the parameters. These objects are: (a) anatomical and/or fiducial points, (b) attached line markers, (c) anatomical surfaces, and (d) outlines of anatomical structures. The second step involves using the derived transformation to transfer outlines of treatment volumes and/or anatomical structures drawn on the images of one imaging study to the images of another study, usually the treatment planning CT. Solid modelling and image processing techniques have been adapted and developed further to accomplish this task. Clinical examples and phantom studies are presented which verify the different aspects of these techniques and demonstrate the accuracy with which they can be applied. Clinical use of these techniques for treatment planning has resulted in improvements in localization of treatment volumes and critical structures in the brain. These improvements have allowed greater sparing of normal tissues and more precise delivery of energy to the desired irradiation volume. It is believed that these improvements will have a positive impact on the outcome of radiation therapy.