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管理头颈部放疗中变形的校正策略。

Correction strategies to manage deformations in head-and-neck radiotherapy.

机构信息

Department of Radiation Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.

出版信息

Radiother Oncol. 2010 Feb;94(2):199-205. doi: 10.1016/j.radonc.2009.12.016. Epub 2010 Jan 18.

Abstract

BACKGROUND AND PURPOSE

To optimize couch shifts based on multiple region-of-interest (ROI) registrations and derive criteria for adaptive replanning for management of deformations in head-and-neck (H&N) cancer patients.

MATERIALS AND METHODS

Eight ROIs containing bony structures were defined on the planning-CT and individually registered to daily cone-beam CTs for 19 H&N cancer patients. Online couch shifts were retrospectively optimized to correct the mean setup error over all ROIs (mean correction) or to minimize the maximum error (MiniMax correction). Residual error distributions were analyzed for both methods. The number of measurements before adaptive-intervention and corresponding action-level were optimized.

RESULTS

Overall residual setup errors were smallest for the mean corrections, while MiniMax corrections reduced the largest errors. The percentage of fractions with residual errors >5 mm was 38% versus 19%. Reduction of deformations by single plan adaptation was most effective after eight fractions: systematic deformations reduced from 1.7 to 0.9 mm. Fifty percent of this reduction can already be achieved by replanning 1/3 of the patients.

CONCLUSION

Two correction methods based on multiple ROI registration were introduced to manage setup errors from deformations that either minimize overall geometrical uncertainties or maximum errors. Moreover, the registrations could be used to select patient with large deformations for replanning.

摘要

背景与目的

为了基于多个感兴趣区域(ROI)的配准优化床面移动,并为头颈部(H&N)癌症患者的变形管理制定自适应计划的标准。

材料与方法

在 19 例 H&N 癌症患者的计划 CT 上定义了 8 个包含骨性结构的 ROI,并分别对其进行了个体化的配准,以获得每日锥形束 CT。在线对床面进行了回顾性的优化,以纠正所有 ROI 的平均设置误差(平均校正)或最小化最大误差(最小最大校正)。分析了两种方法的残余误差分布。对自适应干预前的测量次数和相应的行动水平进行了优化。

结果

对于平均校正,整体残余设置误差最小,而最小最大校正则降低了最大误差。残余误差>5mm 的分数百分比为 38%,而 19%。通过单次计划自适应调整,变形减少最为有效,在 8 个分数后,系统变形从 1.7 毫米减少到 0.9 毫米。这种减少的 50%可以通过重新规划 1/3 的患者来实现。

结论

引入了两种基于多个 ROI 配准的校正方法,以管理由于变形引起的设置误差,这些方法要么最小化整体几何不确定性,要么最小化最大误差。此外,配准还可以用于选择需要重新计划的变形较大的患者。

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