论著摘要 |【Radiomics-PET】定量FDG-PET放射组学中SUV离散化的影响:肿瘤纹理分析中标准化方法的需求(双语版)

2018-01-26 11:37:57 admin 0
标签:   影像组学 纹理特征 强度分辨率 肺癌 肿瘤纹理分析

The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis.

发表日期: 2016.09.26   来源:Sci Rep. 2015 Aug 5;5:11075.

作者:

Leijenaar RT11, Nalbantov G1, Carvalho S1, van Elmpt WJ1, Troost EG1, Boellaard R2, Aerts HJ3, Gillies RJ4, Lambin P1.

作者介绍:

1. Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC+), Maastricht, the Netherlands.

2. Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands.

3. 1] Department of Radiation Oncology (MAASTRO), GROW-School for Oncology and Developmental Biology, Maastricht University Medical Centre (MUMC+), Maastricht, the Netherlands [2] Departments of Radiation Oncology and Radiology, Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

4. Department of Cancer Imaging and Metabolism, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

摘要

描述肿瘤内异质性的DG-PET衍生的结构特征作为成像生物标志物越来越多地被研究。作为定量异质性过程的一部分,图像强度(SUVs)通常被重新采样成数量减少的离散箱。我们专注于实现这种离散化方式的应用。同时需要评估两种方法:(1)RD,将SUV范围划分为D等间隔的箱,其中强度分辨率(即箱体尺寸)在每个图像中都是不同的;(2)RB,保持恒定的强度分辨率B. 对35名肺癌患者进行临床可行性评估,在放射治疗的第二周之前和放射治疗后成像。在两个成像时间点中,对不同的D和B确定了四十四个纹理特征。特征值取决于强度分辨率和两种评估方法,显示RB来允许有意义的患者自身和患者之间的特征值比较。总而言之,患者的排名根据不同的特征值而不同,这些特征值被用作两种离散化方法之间的纹理特征解释的替代。我们的研究表明,SUV离散化的方式对结果的特征及其解释有重要的影响,强调了肿瘤纹理分析中标准化方法的重要性。

Abstact

FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly investigated as imaging biomarkers. As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins. We focused on the implications of the manner in which this discretization is implemented. Two methods were evaluated: (1) R(D), dividing the SUV range into D equally spaced bins, where the intensity resolution (i.e. bin size) varies per image; and (2) R(B), maintaining a constant intensity resolution B. Clinical feasibility was assessed on 35 lung cancer patients, imaged before and in the second week of radiotherapy. Forty-four textural features were determined for different D and B for both imaging time points. Feature values depended on the intensity resolution and out of both assessed methods, R(B) was shown to allow for a meaningful inter- and intra-patient comparison of feature values. Overall, patients ranked differently according to feature values–which was used as a surrogate for textural feature interpretation–between both discretization methods. Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

阅读原文:PMID: 26242464  PMCID: PMC4525145  DOI: 10.1038/srep11075


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