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基于蒙特卡罗的立体定向体部放疗中肺壁肿瘤调强适形放疗计划中改善剂量分布的实用方法。

Practical methods for improving dose distributions in Monte Carlo-based IMRT planning of lung wall-seated tumors treated with SBRT.

机构信息

Department of Radiation Oncology, Henry Ford Health System, Detroit, MI, USA.

出版信息

J Appl Clin Med Phys. 2012 Nov 8;13(6):4007. doi: 10.1120/jacmp.v13i6.4007.

Abstract

Current commercially available planning systems with Monte Carlo (MC)-based final dose calculation in IMRT planning employ pencil-beam (PB) algorithms in the optimization process. Consequently, dose coverage for SBRT lung plans can feature cold-spots at the interface between lung and tumor tissue. For lung wall (LW)-seated tumors, there can also be hot spots within nearby normal organs (example: ribs). This study evaluated two different practical approaches to limiting cold spots within the target and reducing high doses to surrounding normal organs in MC-based IMRT planning of LW-seated tumors. First, "iterative reoptimization", where the MC calculation (with PB-based optimization) is initially performed. The resultant cold spot is then contoured and used as a simultaneous boost volume. The MC-based dose is then recomputed. The second technique uses noncoplanar beam angles with limited path through lung tissue. Both techniques were evaluated against a conventional coplanar beam approach with a single MC calculation. In all techniques the prescription dose was normalized to cover 95% of the PTV. Fifteen SBRT lung cases with LW-seated tumors were planned. The results from iterative reoptimization showed that conformity index (CI) and/or PTV dose uniformity (UPTV) improved in 12/15 plans. Average improvement was 13%, and 24%, respectively. Nonimproved plans had PTVs near the skin, trachea, and/or very small lung involvement. The maximum dose to 1cc volume (D1cc) of surrounding OARs decreased in 14/15 plans (average 10%). Using noncoplanar beams showed an average improvement of 7% in 10/15 cases and 11% in 5/15 cases for CI and UPTV, respectively. The D1cc was reduced by an average of 6% in 10/15 cases to surrounding OARs. Choice of treatment planning technique did not statistically significantly change lung V5. The results showed that the proposed practical approaches enhance dose conformity in MC-based IMRT planning of lung tumors treated with SBRT, improving target dose coverage and potentially reducing toxicities to surrounding normal organs.

摘要

目前,基于蒙特卡罗(MC)的调强放射治疗计划中,商业化的计划系统在优化过程中采用笔束(PB)算法。因此,对于立体定向放射治疗(SBRT)肺计划,在肺组织和肿瘤组织之间的界面可能会出现冷点。对于肺壁(LW)上的肿瘤,附近的正常器官(例如肋骨)内也可能出现热点。本研究评估了两种不同的实用方法,用于限制 MC 调强放射治疗 LW 上肿瘤计划中的靶区内冷点,并降低周围正常器官的高剂量。首先,“迭代再优化”,即首先进行 MC 计算(基于 PB 优化)。然后,将所得冷点勾画出来,并用作同时的增强体积。然后重新计算基于 MC 的剂量。第二种技术使用非共面射束角度,限制通过肺组织的路径。这两种技术都与单次 MC 计算的常规共面射束方法进行了比较。在所有技术中,处方剂量归一化为覆盖 PTV 的 95%。对 15 个有 LW 上肿瘤的 SBRT 肺病例进行了计划。迭代再优化的结果表明,12/15 个计划的适形指数(CI)和/或 PTV 剂量均匀性(UPTV)得到改善。平均改善分别为 13%和 24%。没有改善的计划 PTV 靠近皮肤、气管和/或肺参与非常小。15 个计划中,14/15 个计划(平均 10%)周围 OARs 的 1cc 体积最大剂量(D1cc)降低。使用非共面射束,在 10/15 例中分别有 7%和 5/15 例的 CI 和 UPTV 平均改善 11%。与周围 OARs 相比,10/15 例的 D1cc 平均降低 6%。治疗计划技术的选择并未显著改变肺 V5。结果表明,所提出的实用方法可提高 SBRT 治疗肺肿瘤的 MC 调强放射治疗计划中的剂量适形性,改善靶区剂量覆盖,潜在降低周围正常器官的毒性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0212/5718552/07c14454acc6/ACM2-13-112-g001.jpg

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