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使用形变图像配准技术在前列腺癌放射治疗中靶区和危及器官轮廓的传递。

Propagation of target and organ at risk contours in radiotherapy of prostate cancer using deformable image registration.

机构信息

Clinical Institute, Aarhus University, Aarhus, Denmark.

出版信息

Acta Oncol. 2010 Oct;49(7):1023-32. doi: 10.3109/0284186X.2010.503662.

Abstract

BACKGROUND

Successful deformable image registration is an essential component of both dose accumulation and plan adaptation in radiotherapy. The aim of this study was to evaluate the performance of a deformable image registration application for propagation of contours using repeat CT scans of the pelvis, a region where considerable deformations are expected.

MATERIAL AND METHODS

The study involved four prostate cancer patients, each with 9-11 repeat CT scans. An oncologist contoured bladder, rectum, clinical target volume of pelvic lymph nodes (CTV-ln) and prostate (CTV-p) in all CT scans. The reference CT was retrospectively registered to the repeat CT scans with both rigid and deformable registration using a recently released commercial clinical software application. Two different diffusion-based 'demons' deformable registration algorithms were applied, differing in the amount of deformations being allowed, with algorithm A being more generous than algorithm B. The evaluation of the propagated structures included both quantitative measures and qualitative scoring.

RESULTS

We found the differences between the algorithms to be most evident for bladder and rectum. An increase in mean Dice similarity coefficient relative the rigid registrations of 12% and 13% was obtained with algorithm A for bladder and rectum, compared to 2% with algorithm B. For bladder the mean sensitivity and positive predictive value was 0.92 and 0.87 with algorithm A and 0.82 and 0.83 with algorithm B. Corresponding values for rectum was 0.81 and 0.76 with algorithm A and 0.75 and 0.69 with algorithm B. This translated into 57% and 26% passing the clinical evaluation for bladder and rectum, with algorithm A, compared to 17% and 14% with algorithm B. For CTV-ln and CTV-p both algorithms performed well by all measures, e.g. with 86% of the target structures passing the clinical evaluation.

CONCLUSIONS

Deformable image registration improved contour propagation in the pelvis for all organs investigated. Differences in the performance of the algorithms were seen which became more pronounced for the highly deformable organs of bladder and rectum.

摘要

背景

成功的形变图像配准是放疗中剂量累积和计划适应的重要组成部分。本研究的目的是评估一种用于骨盆重复 CT 扫描的形变图像配准应用程序在轮廓传播方面的性能,骨盆是预计会发生大量变形的区域。

材料与方法

本研究涉及 4 名前列腺癌患者,每位患者有 9-11 次重复 CT 扫描。一名肿瘤学家在所有 CT 扫描中勾画膀胱、直肠、盆腔淋巴结临床靶区(CTV-ln)和前列腺(CTV-p)。参考 CT 扫描通过最近发布的商业临床软件应用程序与重复 CT 扫描进行刚性和形变配准。应用了两种不同的基于扩散的“恶魔”形变配准算法,允许的变形量不同,算法 A 比算法 B 更宽松。传播结构的评估包括定量测量和定性评分。

结果

我们发现算法之间的差异在膀胱和直肠上最为明显。与算法 B 相比,算法 A 使膀胱和直肠相对于刚性配准的平均 Dice 相似系数分别增加了 12%和 13%。对于膀胱,算法 A 的平均灵敏度和阳性预测值分别为 0.92 和 0.87,算法 B 分别为 0.82 和 0.83。对于直肠,算法 A 的相应值分别为 0.81 和 0.76,算法 B 分别为 0.75 和 0.69。这意味着算法 A 有 57%和 26%的膀胱和直肠通过临床评估,而算法 B 分别为 17%和 14%。对于 CTV-ln 和 CTV-p,两种算法在所有测量指标上都表现良好,例如,86%的目标结构通过临床评估。

结论

形变图像配准提高了所有研究器官在骨盆中的轮廓传播。算法的性能存在差异,在膀胱和直肠等高度变形的器官上更为明显。

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