首页> 外文期刊>International Journal of Radiation Oncology, Biology, Physics >Validation of a method for automatic image fusion (BrainLAB System) of CT data and 11C-methionine-PET data for stereotactic radiotherapy using a LINAC: first clinical experience.
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Validation of a method for automatic image fusion (BrainLAB System) of CT data and 11C-methionine-PET data for stereotactic radiotherapy using a LINAC: first clinical experience.

机译:验证使用LINAC进行立体定向放射治疗的CT数据和11C-蛋氨酸-PET数据自动图像融合(BrainLAB系统)的方法:首次临床经验。

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PURPOSE: (a) To implement a fully automatic method to integrate (11)C-methionine positron emission tomography (MET-PET) data into stereotactic radiation treatment planning using the commercially available BrainLAB System, by means of CT/MET-PET image fusion. (b) To validate the fully automatic CT/MET-PET image fusion technique with respect to accuracy and robustness. (c) To give a short glance at the clinical consequences for patients with brain tumors. METHODS AND MATERIALS: In 12 patients with brain tumors (9 meningeomas, 3 gliomas), CT, MRI, and MET-PET were performed for stereotactic fractionated radiation treatment planning. The CT and MET-PET investigations were performed using a relocatable mask for head fixation. Fifteen external reference markers (5 on each lateral and 5 on the frontal localizer plate) that could be identified in CT and MET-PET were applied on the stereotactic localizer frame; the marker positions were exactly defined for both investigations. The MRI/CT fusion was done completely automatically. The CT/MET-PET fusion was performed using two different methods: The gold standard was the CT/PET fusion based on the reference markers, and the test method was the automatic, intensity-based CT/PET fusion, independent of the external markers. The markers visible on CT and transmission PET were matched using a point-to-line matching algorithm. To quantify the amount of misregistration, the two fusion methods were compared by calculating the mean value of deviation between corresponding points inside a cubic volume of interest of > or =512 cm(3) defined within the cranial cavity. The gross tumor volume (CT/MRI) outlined on CT and T1-MRI with contrast medium was compared with the gross tumor volume (PET) defined in the reoriented MET-PET data sets. The clinical impact of MET-PET in tumor volume definition for stereotactic radiotherapy will be discussed. RESULTS: The fully automatic integration of MET-PET into stereotactic radiation treatment planning was successfully realized in all patients investigated. Mean deviation of the intensity-based automatic CT/PET fusion compared with the external marker-based gold standard was 2.4 mm; the standard deviation was 0.5. The algorithm's robustness was evaluated, and the discrepancy of fusion results due to different initial image alignments was determined to be below 1 mm inside the test volume of interest. In patients with meningiomas and gliomas, MET-PET was shown to deliver additional information concerning tumor extension. CONCLUSION: The precision of the automatic CT/PET image fusion was high. A mean deviation of 2.4 mm is acceptable, considering that it is approximately equal to the pixel size of the PET data sets. MET-PET improves target volume definition for stereotactic fractionated radiotherapy of meningiomas and gliomas.
机译:目的:(a)利用CT / MET-PET图像融合技术,利用商用的BrainLAB系统,实现一种将(11)C-蛋氨酸正电子发射断层扫描(MET-PET)数据整合到立体定向放射治疗计划中的全自动方法。 (b)在准确性和鲁棒性方面验证全自动CT / MET-PET图像融合技术。 (c)简要了解脑肿瘤患者的临床后果。方法和材料:对12例脑肿瘤(9例脑膜瘤,3例神经胶质瘤)患者进行了CT,MRI和MET-PET立体定向分次放射治疗计划。 CT和MET-PET检查是使用可重定位面罩进行头部固定的。可以在CT和MET-PET中识别的15个外部参考标记(每侧5个,额骨定位板上5个)被应用在立体定位器框架上;标记位置已为两次调查准确定义。 MRI / CT融合是完全自动完成的。 CT / MET-PET融合使用两种不同的方法进行:黄金标准是基于参考标记的CT / PET融合,测试方法是基于强度的自动CT / PET融合,独立于外部标记。使用点对线匹配算法对CT和透射PET上可见的标记进行匹配。为了量化重合失调的数量,比较了两种融合方法,方法是计算颅腔内感兴趣的立方体积内大于或等于512 cm(3)的对应点之间的平均偏差。将CT和T1-MRI上用造影剂勾勒的肿瘤总体积(CT / MRI)与重新定向的MET-PET数据集中定义的肿瘤总体积(PET)进行了比较。将讨论MET-PET在立体定向放疗的肿瘤体积定义中的临床影响。结果:在所有接受调查的患者中,MET-PET完全自动地集成到立体定向放射治疗计划中。基于强度的自动CT / PET融合与基于外部标记的金标准的平均偏差为2.4 mm;标准偏差为0.5。对算法的鲁棒性进行了评估,并确定了由于感兴趣的测试体积之内不同初始图像对齐方式而导致的融合结果差异小于1 mm。在脑膜瘤和神经胶质瘤患者中,MET-PET被证明可提供有关肿瘤扩展的更多信息。结论:CT / PET自动图像融合精度高。考虑到它等于PET数据集的像素大小,平均偏差为2.4 mm是可以接受的。 MET-PET改善了脑膜瘤和神经胶质瘤的立体定向分次放射治疗的目标体积定义。

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