Ryckman Jeffrey M, Shelton Joseph W, Waller Anthony F, Schreibmann Eduard, Latifi Kujtim, Diaz Roberto
Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA; Medical College of Georgia at Augusta University, Augusta, GA.
Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA.
Brachytherapy. 2016 Sep-Oct;15(5):584-92. doi: 10.1016/j.brachy.2016.04.390. Epub 2016 Jun 1.
To examine the impact of anatomic structure-based image sets in deformable image registration (DIR) for cervical cancer patients.
CT examinations of 7 patients previously treated for locally advanced cervical cancer with external beam radiation therapy and from three to five fractions of high-dose-rate brachytherapy (HDR-BT) were used. Structure-based image sets were created from "free" structures already made for planning purposes, with each structure of interest assigned a unique, homogeneous Hounsfield number. Subsequent HDR fractions were registered to the pretreatment external beam radiation therapy and/or the first HDR fraction using commercially available software by rigid alignment (RIG) followed by DIR. Comparison methods included quantification of external contour displacement between source and target images and calculation of mean voxel displacement values. Registration results for structure-based image sets were then compared and contrasted to intensity-based registrations of the original grayscale images.
Utilization of anatomic structure-based image sets resulted in better initial rigid matching (A-RIG) with more importance on applicator positioning and soft tissue structures. Subsequent DIR of anatomic structure-based images allowed for intermodality registrations, whereas all intermodality registrations using original CT images failed to produce anatomically feasible results.
We have investigated the use of structure-based CT image sets for image registrations and have produced anatomically favorable registrations with excellent matching of external contours as compared to registrations of original grayscale images. Commercial software registrations using treatment-planning structures required no manual tweaking on a per-patient basis, suggesting results are reproducible and broadly applicable.
研究基于解剖结构的图像集在宫颈癌患者的可变形图像配准(DIR)中的影响。
使用7例先前接受过外照射放疗及三至五次高剂量率近距离放疗(HDR-BT)治疗的局部晚期宫颈癌患者的CT检查。基于结构的图像集由已经为计划目的而创建的“自由”结构生成,每个感兴趣的结构被赋予一个唯一的、均匀的Hounsfield数。随后使用商用软件通过刚性配准(RIG)然后进行DIR,将后续的HDR分次图像配准到预处理外照射放疗图像和/或第一次HDR分次图像。比较方法包括量化源图像和目标图像之间的外部轮廓位移以及计算平均体素位移值。然后将基于结构的图像集的配准结果与原始灰度图像的基于强度的配准结果进行比较和对比。
使用基于解剖结构的图像集可实现更好的初始刚性匹配(A-RIG),对施源器定位和软组织结构更为重视。基于解剖结构的图像的后续DIR允许进行模态间配准,而使用原始CT图像的所有模态间配准均未能产生解剖学上可行的结果。
我们研究了基于结构的CT图像集在图像配准中的应用,并与原始灰度图像的配准相比,产生了在解剖学上有利的配准,外部轮廓匹配良好。使用治疗计划结构的商用软件配准无需针对每个患者进行手动调整,表明结果具有可重复性且广泛适用。