将卷积算法纳入Leksell GammaPlan中用于常规治疗计划的实用策略

IF 0.7 Q4 SURGERY
Journal of radiosurgery and SBRT Pub Date : 2022-01-01
Yoichi Watanabe, Damien Mathew, Gopishankar Natanasabapathi
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引用次数: 0

摘要

目的:本研究旨在建立卷积剂量计算标准和有效的程序,以包括GammaKnife放射外科(GKRS)治疗计划中的异质性效应。方法与材料:对114例不同疾病类型、肿瘤部位、大小、组份数、处方剂量的GKRS病例进行分析。总共有205个肿瘤。除常规MRI扫描外,还对所有治疗进行CT扫描。所有治疗方案均采用TMR10算法(TMR10)创建。我们用卷积算法(Conv)重复了本研究的剂量计算。我们计算了治疗体积(TxtVol)、一半处方剂量覆盖的体积(TxtVol2)、肿瘤中最小、最大和平均剂量(minDose、maxDose和meanDose)和处方等剂量覆盖的肿瘤体积(covVol)的Conv和TMR10之间的比值。然后,我们将这些数量分类为头骨表面距离肿瘤中心(distC)和肿瘤边缘(distE)的最短距离所代表的肿瘤位置。[表:见正文]。结果:6个比值均随距离和距离的增加而增加。例如,随着距离的增加,中位minDose ratio从0.885增加到0.933。远端< 2 cm与远端≥2 cm肿瘤的minDose比差异有统计学意义。另一方面,中位maxDose ratio约为0.933[0.928-0.939],几乎与distE无关。这表明TMR10给药剂量高估了6.1%。结论:应用卷积算法计算体积剂量时,当颅骨表面到肿瘤最近点的距离小于2 cm时,必须考虑异质性效应,准确度低于3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A practical strategy for incorporating the convolution algorithm in Leksell GammaPlan for routine treatment planning<sup>†</sup>.

A practical strategy for incorporating the convolution algorithm in Leksell GammaPlan for routine treatment planning<sup>†</sup>.

A practical strategy for incorporating the convolution algorithm in Leksell GammaPlan for routine treatment planning.

Purpose: This study aims to establish criteria for convolution dose calculations and an efficient procedure to include the heterogeneity effects in GammaKnife radiosurgery (GKRS) treatment plans.

Methods and materials: We analyzed 114 GKRS cases of various disease types, tumor locations, sizes, the number of fractions, and prescription doses. There was a total of 205 tumors. CT scans were performed in addition to routine MRI scans for all treatments. All treatment plans were created using the TMR10 algorithm (TMR10). We repeated the dose calculations for this study with the convolution algorithm (Conv). We calculated the ratios between Conv and TMR10 of the treatment volume (TxtVol), the volume covered by half of the prescription dose (TxtVol2), the minimum, maximum, and mean doses in the tumor (minDose, maxDose, and meanDose), and the volume of tumor covered by the prescription isodose (covVol). We then categorized those quantities for locations of tumors represented by the shortest distance of the skull surface from the tumor center (distC) and the tumor edge (distE). [Table: see text].

Results: All six ratios increased with increasing distC and distE. For example, the median minDose ratio increased from 0.885 to 0.933 as distE increased. There was a statistically significant difference in the minDose ratio between tumors of distE < 2 cm and distE ≥ 2 cm. On the other hand, the median maxDose ratio was about 0.933 [0.928-0.939], being almost independent of distE. This suggested a 6.1% overestimation of the delivered dose with TMR10.

Conclusion: The heterogeneity effects must be considered for the volume dose calculations by applying the convolution algorithm when the distance of the skull surface from the closest point of the tumor is less than 2 cm to achieve less than 3% accuracy.

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CiteScore
1.40
自引率
8.30%
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