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机器人放射外科中的放射毒性:提出一种用于优化脑转移瘤治疗计划的新质量指标。

Radiotoxicity in robotic radiosurgery: proposing a new quality index for optimizing the treatment planning of brain metastases.

作者信息

Hellerbach Alexandra, Luyken Klaus, Hoevels Mauritius, Gierich Andreas, Rueß Daniel, Baus Wolfgang W, Kocher Martin, Ruge Maximilian I, Treuer Harald

机构信息

Department of Stereotaxy and Functional Neurosurgery, University Hospital Cologne, Cologne, Germany.

Department of Radiotherapy, University Hospital Cologne, Cologne, Germany.

出版信息

Radiat Oncol. 2017 Aug 17;12(1):136. doi: 10.1186/s13014-017-0867-z.

DOI:10.1186/s13014-017-0867-z
PMID:28818094
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5561581/
Abstract

BACKGROUND

As irradiated brain volume at 12 Gy (V12) is a predictor for radionecrosis, the purpose of the study was to develop a model for Cyberknife (CK) plans that is able to predict the lowest achievable V12 at a given tumor size and prescription dose (PD), and to suggest a new quality index regarding V12 for optimizing the treatment planning of brain metastases.

METHOD

In our model V12 was approximated as a spherical shell around the tumor volume. The radial distance between tumor surface and the 12 Gy isodose line was calculated using an approximation of the mean dose gradient in that area. Assuming a radially symmetrical irradiation from the upper half space, the dose distribution is given by the superposition of single fields. The dose profiles of a single field were derived by the measured off-center ratios (OCR) of the CK system. Using the calculated gradients of the sum dose profiles, minimal-V12 was estimated for different tumor sizes. The model calculation was tested using a phantom dataset and retrospectively applied on clinical cases.

RESULTS

Our model allows the prediction of a best-case scenario for V12 at a given tumor size and PD which was confirmed by the results of the isocentric phantom plans. The results of the non-isocentric phantom plans showed that an optimization of coverage caused an increase in V12. This was in accordance with the results of the retrospective analysis. V12 s of the clinical cases were on average twice that of the predicted model calculation. A good agreement was achieved for plans with an optimal conformity index (nCI). Re-planning of cases with high V12 showed that lower values could be reached by selecting smaller collimators and by allowing a larger number of total MU and more MU per beam.

CONCLUSIONS

V12 is a main parameter for assessing plan quality in terms of radiotoxicity. The index f12 defined as the ratio of V12 from the actual plan with the evaluated V12 from our model describes the conformity of an optimally possible V12 and thus can be used as a new quality index for optimizing treatment plans.

摘要

背景

由于12 Gy时的受照射脑体积(V12)是放射性坏死的一个预测指标,本研究的目的是开发一种适用于射波刀(CK)计划的模型,该模型能够在给定肿瘤大小和处方剂量(PD)的情况下预测可实现的最低V12,并提出一个关于V12的新质量指标,以优化脑转移瘤的治疗计划。

方法

在我们的模型中,V12被近似为围绕肿瘤体积的一个球壳。利用该区域平均剂量梯度的近似值计算肿瘤表面与12 Gy等剂量线之间的径向距离。假设从上半空间进行径向对称照射,剂量分布由单野叠加给出。单野的剂量分布通过CK系统测量的离轴比(OCR)得出。利用计算出的总剂量分布梯度,估计不同肿瘤大小下的最小V12。使用体模数据集对模型计算进行测试,并回顾性应用于临床病例。

结果

我们的模型能够预测在给定肿瘤大小和PD时V12的最佳情况,等中心体模计划的结果证实了这一点。非等中心体模计划的结果表明,覆盖范围的优化导致V12增加。这与回顾性分析的结果一致。临床病例的V12平均是预测模型计算值的两倍。对于具有最佳适形指数(nCI)的计划,达成了良好的一致性。对V12较高的病例进行重新计划表明,通过选择较小的准直器、允许更大的总MU数和每束更多的MU数,可以达到更低的值。

结论

就放射毒性而言,V12是评估计划质量的一个主要参数。定义为实际计划的V12与我们模型评估的V12之比的指标f12描述了最佳可能V12的适形性,因此可作为优化治疗计划的一个新质量指标。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/9a575234ecc2/13014_2017_867_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/8a1b3ca58142/13014_2017_867_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/12b0671f858a/13014_2017_867_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/fffad6691a1a/13014_2017_867_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/704e21d78899/13014_2017_867_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/9a575234ecc2/13014_2017_867_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/8a1b3ca58142/13014_2017_867_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/12b0671f858a/13014_2017_867_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/fffad6691a1a/13014_2017_867_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/704e21d78899/13014_2017_867_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e77/5561581/9a575234ecc2/13014_2017_867_Fig5_HTML.jpg

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