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胸段癌患者放射性肺炎:基于多中心体素的分析

Radiation Pneumonitis in Thoracic Cancer Patients: Multi-Center Voxel-Based Analysis.

作者信息

Palma Giuseppe, Monti Serena, Pacelli Roberto, Liao Zhongxing, Deasy Joseph O, Mohan Radhe, Cella Laura

机构信息

Institute of Biostructures and Bioimaging, National Research Council, 80145 Napoli, Italy.

Department of Advanced Biomedical Sciences, University of Naples "Federico II", 80131 Napoli, Italy.

出版信息

Cancers (Basel). 2021 Jul 15;13(14):3553. doi: 10.3390/cancers13143553.

Abstract

This study investigates the dose-response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (α/β = 3 Gy) was spatially normalized on a common anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a -level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained findings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.

摘要

本研究调查了采用不同放疗方式治疗胸部恶性肿瘤的患者中与放射性肺炎(RP)相关的剂量反应模式。为此,应用了基于体素的分析(VBA),该分析由一种用于表征剂量图空间特性的新策略赋能。分析了来自三个机构的382例接受不同放射治疗(RT)技术治疗的肺癌和纵隔淋巴瘤患者的数据。每个计划CT和生物有效剂量图(α/β = 3 Gy)在共同的解剖学参考上进行空间归一化。对有RP和无RP患者之间的局部剂量差异进行VBA,并相应地生成与RP在0.05水平显著相关的剂量差异体素簇。基于概率独立成分分析(PICA)和连接图对剂量图空间特性进行新的表征,评估VBA推断的稳健性。这为所获得的肺部下部和心脏在RP发生中起重要作用的研究结果奠定了坚实基础。连接图显示,该数据集可以支持主要心脏和肺部亚结构之间的放射生物学区分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6816/8306650/610109f62adb/cancers-13-03553-g001.jpg

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