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Validation of Catheter Segmentation for MR-guided Gynecologic Cancer Brachytherapy

机译:验证MR引导妇科癌症近距离放射治疗的导管分割

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摘要

Segmentation of interstitial catheters from MRI needs to be addressed in order for MRI-based brachytherapy treatment planning to become part of the clinical practice of gynecologic cancer radiotherapy. This paper presents a validation study of a novel image-processing method for catheter segmentation. The method extends the distal catheter tip, interactively provided by the physician, to its proximal end, using knowledge of catheter geometry and appearance in MRI sequences. The validation study consisted of comparison of the algorithm results to expert manual segmentations, first on images of a phantom, and then on patient MRI images obtained during MRI-guided insertion of brachytherapy catheters for the treatment of gynecologic cancer. In the phantom experiment, the maximum disagreement between automatic and manual segmentation of the same MRI image, as computed using the Hausdorf distance, was 1.5 mm, which is of the same order as the MR image spatial resolution, while the disagreement between automatic segmentation of MR images and “ground truth”, manual segmentation of CT images, was 3.5 mm. The segmentation method was applied to an IRB-approved retrospective database of 10 interstitial brachytherapy patients which included a total of 101 catheters. Compared with manual expert segmentations, the automatic method correctly segmented 93 out of 101 catheters, at an average rate of 0.3 seconds per catheter using a 3GHz Intel Core i7 computer with 16 GB RAM and running Mac OS X 10.7. These results suggest that the proposed catheter segmentation is both technically and clinically feasible.
机译:为了解决基于MRI的近距离放射治疗计划成为妇科癌症放射治疗临床实践的一部分,需要解决MRI的间质导管分割问题。本文提出了一种用于导管分割的新型图像处理方法的验证研究。该方法利用对导管几何形状和MRI序列外观的了解,将由医生交互式提供的远端导管尖端延伸到其近端。验证研究包括将算法结果与专家手动分割进行比较,首先是在幻像的图像上,然后是在MRI引导下插入近距离治疗导管以治疗妇科癌症期间获得的患者MRI图像。在幻像实验中,使用Hausdorf距离计算出的同一张MRI图像的自动分割和手动分割之间的最大差异为1.5 mm,与MR图像空间分辨率的顺序相同,而MRI的自动分割之间的差异最大。 MR图像和“地面真相”(CT图像的手动分割)为3.5毫米。分割方法应用于IRB批准的10个间质性近距离放射治疗患者的回顾性数据库中,该数据库总共包括101个导管。与手动专家细分相比,自动方法使用具有16 GB RAM的3GHz Intel Core i7计算机和运行Mac OS X 10.7的设备,以101条导管中的平均0.3秒的平均速率正确地进行了细分。这些结果表明,提出的导管分割在技术和临床上都是可行的。

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