Suppr超能文献

一种新型剂量衰减指数及其在脑和肺立体定向放射治疗中的初步应用。

A novel dose fall-off index and preliminary application in brain and lung stereotactic radiotherapy.

作者信息

Shen Zhengwen, Luo Huanli, Li Shi, Tan Xia, Tian Xiumei, Liu Qiang, Jin Fu

机构信息

Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China.

Department of Oncology, Chongqing University Three Gorges Hospital, Chongqing, China.

出版信息

Med Phys. 2023 May;50(5):3127-3136. doi: 10.1002/mp.16383. Epub 2023 Apr 3.

Abstract

BACKGROUND

Stereotactic radiotherapy (SRT) has been widely used for the treatment of brain metastases and early stage non-small-cell lung cancer (NSCLC). Excellent SRT plans are characterized by steep dose fall-off, making it critical to accurately and comprehensively predict and evaluate dose fall-off.

PURPOSE

A novel dose fall-off index was proposed to ensure high-quality SRT planning.

METHODS

The novel gradient index (NGI) had two different modes: NGIx V for three-dimensions and NGIx r for one-dimension. NGIx V and NGIx r were defined as the ratios of the decreased percentage dose (x%) to the corresponding isodose volume and equivalent sphere radii, respectively. A total of 243 SRT plans at our institution between April 2020 and March 2022 were enrolled, including 126 brain and 117 lung SRT plans. Measurement-based verifications were performed using SRS MapCHECK. Ten plan complexity indexes were calculated. Dosimetric parameters related to radiation injuries were also extracted, including the normal brain volume exposed to 12 Gy (V ) and 18 Gy (V ) during single-fraction SRT (SF-SRT) and multi-fraction SRT (MF-SRT), respectively, and the normal lung volume exposed to 12 Gy (V ). The performance of NGI and other common dose fall-off indexes, gradient index (GI), R and D were evaluated using Spearman correlation analysis to explore their correlations with the PTV size, gamma passing rate (GPR), plan complexity indexes, and dosimetric parameters.

RESULTS

There were statistically significant correlations between NGI and PTV size (r = -0.98, P < 0.01 for NGI50 V and r = -0.93, P < 0.01 for NGI50 r), which were the strongest correlations compared with GI (r = 0.11, P = 0.13), R (r = -0.08, P = 0.19) and D (r = 0.84, P < 0.01). The fitted formulas of NGI50 V = 23.86V and NGI50 r = 113.5r were established. The GPRs of enrolled SRT plans were 98.6 ± 1.7%, 94.2 ± 4.7% and 97.1 ± 3.1% using the criteria of 3%/2 mm, 3%/1 mm, and 2%/2 mm, respectively. NGI50 V achieved the strongest correlations with various plan complexity indexes (|r| ranged from 0.67 to 0.91, P < 0.01). NGI50 V also showed the highest r values with V (r = -0.93, P < 0.01) and V (r = -0.96, P < 0.01) of the normal brain during SF-SRT and MF-SRT, respectively, and V (r = -0.86, P < 0.01) of the normal lung during lung SRT.

CONCLUSIONS

Compared with GI, R and D , the proposed dose fall-off index, NGI, had the strongest correlations with the PTV size, plan complexity and V /V of the normal tissues. These correlations established on NGI are more helpful and reliable for SRT planning, quality control, and reducing the risk of radiation injuries.

摘要

背景

立体定向放射治疗(SRT)已广泛应用于脑转移瘤和早期非小细胞肺癌(NSCLC)的治疗。优秀的SRT计划具有陡峭的剂量下降特征,因此准确、全面地预测和评估剂量下降至关重要。

目的

提出一种新的剂量下降指数以确保高质量的SRT计划。

方法

新梯度指数(NGI)有两种不同模式:三维的NGIxV和一维的NGIxr。NGIxV和NGIxr分别定义为剂量下降百分比(x%)与相应等剂量体积和等效球半径的比值。纳入了2020年4月至2022年3月期间本机构的243个SRT计划,包括126个脑部SRT计划和117个肺部SRT计划。使用SRS MapCHECK进行基于测量的验证。计算了10个计划复杂性指数。还提取了与放射性损伤相关的剂量学参数,包括单次分割SRT(SF-SRT)和多次分割SRT(MF-SRT)期间分别暴露于12 Gy(V)和18 Gy(V)的正常脑体积,以及暴露于12 Gy(V)的正常肺体积。使用Spearman相关分析评估NGI与其他常见剂量下降指数、梯度指数(GI)、R和D的性能,以探讨它们与靶区体积(PTV)大小、伽马通过率(GPR)、计划复杂性指数和剂量学参数的相关性。

结果

NGI与PTV大小之间存在统计学显著相关性(NGI50V的r = -0.9...

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验