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估算光子或质子束放射外科治疗肝转移瘤后发生放射性肝损伤的风险。

Estimation of the risk for radiation-induced liver disease following photon- or proton-beam radiosurgery of liver metastases.

机构信息

Department of Physics - Medical Radiation Physics, Stockholm University, Stockholm, Sweden.

Department of Physics, Universidade Eduardo Mondlane, Maputo, Mozambique.

出版信息

Radiat Oncol. 2018 Oct 22;13(1):206. doi: 10.1186/s13014-018-1151-6.

DOI:10.1186/s13014-018-1151-6
PMID:30348194
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6196431/
Abstract

BACKGROUND

Radiotherapy of liver metastases is commonly being performed with photon-beam based stereotactic body radiation therapy (SBRT). The high risk for radiation-induced liver disease (RILD) is a limiting factor in these treatments. The use of proton-beam based SBRT could potentially improve the sparing of the healthy part of the liver. The aim of this study was to use estimations of normal tissue complication probability (NTCP) to identify liver-metastases patients that could benefit from being treated with intensity-modulated proton therapy (IMPT), based on the reduction of the risk for RILD.

METHODS

Ten liver metastases patients, previously treated with photon-beam based SBRT, were retrospectively planned with IMPT. A CTV-based robust optimisation (accounting for setup and range uncertainties), combined with a PTV-based conventional optimisation, was performed. A robustness criterion was defined for the CTV (V > 98% for at least 10 of the 12 simulated scenarios). The NTCP was estimated for different endpoints using the Lyman-Kutcher-Burman model. The ΔNTCP (NTCP - NTCP) for RILD was registered for each patient. The patients for which the NTCP (RILD) < 5% were also identified. A generic relative biological effectiveness of 1.1 was assumed for the proton beams.

RESULTS

For all patients, the objectives set for the PTV and the robustness criterion set for the CTV were fulfilled with the IMPT plans. An improved sparing of the healthy part of the liver, right kidney, lungs, spinal cord and the skin was achieved with the IMPT plans, compared to the SBRT plans. Mean liver doses larger than the threshold value of 32 Gy led to NTCP values for RILD exceeding 5% (7 patients with SBRT and 3 patients with the IMPT plans). ΔNTCP values (RILD) ranging between - 98% and - 17% (7 patients) and between 0 and 2% (3 patients), were calculated.

CONCLUSIONS

In this study, liver metastases patients that could benefit from being treated with IMPT, based on the NTCP reductions, were identified. The clinical implementation of such a model-based approach to select liver metastases patients to proton therapy needs to be made with caution while considering the uncertainties involved in the NTCP estimations.

摘要

背景

肝转移瘤的放射治疗通常采用基于光子束的立体定向体放射治疗(SBRT)。放射性肝损伤(RILD)的高风险是这些治疗方法的一个限制因素。质子束立体定向放射治疗(SBRT)的应用可能会降低健康肝组织的照射剂量。本研究旨在使用正常组织并发症概率(NTCP)的估计值,根据 RILD 风险降低的情况,确定可能从强度调制质子治疗(IMPT)中获益的肝转移瘤患者。

方法

回顾性地为 10 例接受光子束 SBRT 治疗的肝转移瘤患者制定 IMPT 计划。采用基于 CTV 的稳健优化(考虑了摆位和范围不确定性),结合基于 PTV 的常规优化。为 CTV 定义了一个稳健性标准(在 12 个模拟场景中至少有 10 个场景的 V>98%)。使用 Lyman-Kutcher-Burman 模型估计不同终点的 NTCP。为每位患者记录 RILD 的ΔNTCP(NTCP- NTCP)。还确定了 NTCP(RILD)<5%的患者。假设质子束的通用相对生物学效应为 1.1。

结果

对于所有患者,IMPT 计划都满足 PTV 的目标和 CTV 的稳健性标准。与 SBRT 计划相比,IMPT 计划能更好地保护肝脏、右肾、肺、脊髓和皮肤的健康组织。肝脏剂量大于 32Gy 的阈值,导致 RILD 的 NTCP 值超过 5%(7 例 SBRT 患者和 3 例 IMPT 计划患者)。计算出的ΔNTCP 值(RILD)范围在-98%至-17%(7 例患者)和 0 至 2%(3 例患者)之间。

结论

在这项研究中,根据 NTCP 降低,确定了可能从 IMPT 治疗中获益的肝转移瘤患者。在考虑 NTCP 估计中的不确定性的情况下,需要谨慎地将这种基于模型的方法应用于选择接受质子治疗的肝转移瘤患者。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/0d71b1c6ad71/13014_2018_1151_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/51655d9c2d37/13014_2018_1151_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/ad4ce2dd6bb8/13014_2018_1151_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/c37c00f3a914/13014_2018_1151_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/0d71b1c6ad71/13014_2018_1151_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/51655d9c2d37/13014_2018_1151_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/ad4ce2dd6bb8/13014_2018_1151_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/c37c00f3a914/13014_2018_1151_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba01/6196431/0d71b1c6ad71/13014_2018_1151_Fig4_HTML.jpg

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