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最小移动性胸部病变的剂量-质量反向优化

Dose-mass inverse optimization for minimally moving thoracic lesions.

作者信息

Mihaylov I B, Moros E G

机构信息

Department of Radiation Oncology, University of Miami, 1475 NW 12th Ave, Suite 1500, Miami, FL 33136, USA.

出版信息

Phys Med Biol. 2015 May 21;60(10):3927-37. doi: 10.1088/0031-9155/60/10/3927. Epub 2015 Apr 24.

Abstract

In the past decade, several different radiotherapy treatment plan evaluation and optimization schemes have been proposed as viable approaches, aiming for dose escalation or an increase of healthy tissue sparing. In particular, it has been argued that dose-mass plan evaluation and treatment plan optimization might be viable alternatives to the standard of care, which is realized through dose-volume evaluation and optimization. The purpose of this investigation is to apply dose-mass optimization to a cohort of lung cancer patients and compare the achievable healthy tissue sparing to that one achievable through dose-volume optimization. Fourteen non-small cell lung cancer (NSCLC) patient plans were studied retrospectively. The range of tumor motion was less than 0.5 cm and motion management in the treatment planning process was not considered. For each case, dose-volume (DV)-based and dose-mass (DM)-based optimization was performed. Nine-field step-and-shoot IMRT was used, with all of the optimization parameters kept the same between DV and DM optimizations. Commonly used dosimetric indices (DIs) such as dose to 1% the spinal cord volume, dose to 50% of the esophageal volume, and doses to 20 and 30% of healthy lung volumes were used for cross-comparison. Similarly, mass-based indices (MIs), such as doses to 20 and 30% of healthy lung masses, 1% of spinal cord mass, and 33% of heart mass, were also tallied. Statistical equivalence tests were performed to quantify the findings for the entire patient cohort. Both DV and DM plans for each case were normalized such that 95% of the planning target volume received the prescribed dose. DM optimization resulted in more organs at risk (OAR) sparing than DV optimization. The average sparing of cord, heart, and esophagus was 23, 4, and 6%, respectively. For the majority of the DIs, DM optimization resulted in lower lung doses. On average, the doses to 20 and 30% of healthy lung were lower by approximately 3 and 4%, whereas lung volumes receiving 2000 and 3000 cGy were lower by 3 and 2%, respectively. The behavior of MIs was very similar. The statistical analyses of the results again indicated better healthy anatomical structure sparing with DM optimization. The presented findings indicate that dose-mass-based optimization results in statistically significant OAR sparing as compared to dose-volume-based optimization for NSCLC. However, the sparing is case-dependent and it is not observed for all tallied dosimetric endpoints.

摘要

在过去十年中,已经提出了几种不同的放射治疗计划评估和优化方案作为可行的方法,旨在提高剂量或增加对健康组织的保护。特别是,有人认为剂量-质量计划评估和治疗计划优化可能是护理标准的可行替代方案,护理标准是通过剂量-体积评估和优化来实现的。本研究的目的是将剂量-质量优化应用于一组肺癌患者,并将可实现的对健康组织的保护与通过剂量-体积优化可实现的保护进行比较。回顾性研究了14例非小细胞肺癌(NSCLC)患者的计划。肿瘤运动范围小于0.5厘米,且未考虑治疗计划过程中的运动管理。对于每个病例,进行了基于剂量-体积(DV)和基于剂量-质量(DM)的优化。采用九野静态调强放疗,DV和DM优化之间的所有优化参数保持相同。使用常用的剂量学指标(DIs),如脊髓体积1%的剂量、食管体积50%的剂量以及健康肺体积20%和30%的剂量进行交叉比较。同样,也计算了基于质量的指标(MIs),如健康肺质量20%和30%的剂量、脊髓质量1%的剂量以及心脏质量33%的剂量。进行了统计等效性检验以量化整个患者队列的结果。对每个病例的DV和DM计划进行归一化,以使95%的计划靶体积接受规定剂量。DM优化比DV优化导致更多的危及器官(OAR)得到保护。脊髓、心脏和食管的平均保护率分别为23%、4%和6%。对于大多数DIs,DM优化导致较低的肺剂量。平均而言,健康肺20%和30%的剂量分别降低了约3%和4%,而接受2000和3000 cGy的肺体积分别降低了3%和2%。MIs的表现非常相似。结果的统计分析再次表明,DM优化对健康解剖结构的保护更好。所呈现的结果表明,与基于剂量-体积的优化相比,基于剂量-质量的优化在NSCLC中导致了具有统计学意义的OAR保护。然而,这种保护因病例而异,并非所有计算的剂量学终点都能观察到。

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Mathematical Formulation of DMH-Based Inverse Optimization.
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3
Complication probability models for radiation-induced heart valvular dysfunction: do heart-lung interactions play a role?
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4
Automated improvement of radiation therapy treatment plans by optimization under reference dose constraints.
Phys Med Biol. 2012 Dec 7;57(23):7799-811. doi: 10.1088/0031-9155/57/23/7799. Epub 2012 Nov 6.
7
Radiation dose-volume effects in the lung.
Int J Radiat Oncol Biol Phys. 2010 Mar 1;76(3 Suppl):S70-6. doi: 10.1016/j.ijrobp.2009.06.091.
8
Lung dose for minimally moving thoracic lesions treated with respiration gating.
Int J Radiat Oncol Biol Phys. 2010 May 1;77(1):285-91. doi: 10.1016/j.ijrobp.2009.08.021. Epub 2010 Jan 25.
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Association between RT-induced changes in lung tissue density and global lung function.
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