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盆腔 CT 研究中扩张直肠的注册方法。

Methodology for registration of distended rectums in pelvic CT studies.

机构信息

Universidad Politécnica de Madrid, Madrid, Spain.

出版信息

Med Phys. 2012 Oct;39(10):6351-9. doi: 10.1118/1.4754798.

Abstract

PURPOSE

Accurate delineation of the rectum is of high importance in off-line adaptive radiation therapy since it is a major dose-limiting organ in prostate cancer radiotherapy. The intensity-based deformable image registration (DIR) methods cannot create a correct spatial transformation if there is no correspondence between the template and the target images. The variation of rectal filling, gas, or feces, creates a non correspondence in image intensities that becomes a great obstacle for intensity-based DIR.

METHODS

In this study the authors have designed and implemented a semiautomatic method to create a rectum mask in pelvic computed tomography (CT) images. The method, that includes a DIR based on the demons algorithm, has been tested in 13 prostate cancer cases, each comprising of two CT scans, for a total of 26 CT scans.

RESULTS

The use of the manual segmentation in the planning image and the proposed rectum mask method (RMM) method in the daily image leads to an improvement in the DIR performance in pelvic CT images, obtaining a mean value of overlap volume index = 0.89, close to the values obtained using the manual segmentations in both images.

CONCLUSIONS

The application of the RMM method in the daily image and the manual segmentations in the planning image during prostate cancer treatments increases the performance of the registration in presence of rectal fillings, obtaining very good agreement with a physician's manual contours.

摘要

目的

在离线自适应放射治疗中,直肠的精确勾画非常重要,因为它是前列腺癌放射治疗中主要的剂量限制器官。基于强度的变形图像配准(DIR)方法如果模板和目标图像之间没有对应关系,就无法创建正确的空间变换。直肠充盈、气体或粪便的变化会导致图像强度出现不对应,这成为基于强度的 DIR 的一个巨大障碍。

方法

在这项研究中,作者设计并实现了一种半自动方法,用于在骨盆 CT(CT)图像中创建直肠掩模。该方法包括基于 demons 算法的 DIR,已在 13 例前列腺癌病例中进行了测试,每个病例包括两次 CT 扫描,共计 26 次 CT 扫描。

结果

在计划图像中使用手动分割和在日常图像中使用提出的直肠掩模方法(RMM),可提高骨盆 CT 图像中 DIR 的性能,获得的重叠体积指数平均值为 0.89,接近在两幅图像中使用手动分割获得的值。

结论

在前列腺癌治疗中,在日常图像中应用 RMM 方法,并在计划图像中进行手动分割,可以提高配准在直肠充盈情况下的性能,与医生的手动轮廓非常吻合。

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