论著摘要 |【Radiomics-综述】利用纹理分析在18F-FDG PET/CT成像中量化肿瘤异质性(双语版))

2018-02-06 10:02:36 admin 3
标签:   影像组学 18F-FDG PET/CT 纹理特征 纹理分析 肿瘤 异质性

Quantifying tumour heterogeneity in 18F-FDG PET/CT imaging by texture analysis.

发表日期: 2012.10.13   来源:Eur J Nucl Med Mol Imaging. 2013 Jan;40(1):133-40.

作者:

Chicklore S1, Goh V1, Siddique M1, Roy A1, Marsden PK1, Cook GJ1.

作者介绍:

1. Clinical PET Centre, Division of Imaging Sciences and Biomedical Engineering, Kings College London, St Thomas' Hospital, London, UK.

摘要

18F-FDG PET / CT现在通常用于肿瘤成像来进行诊断和分期,并且越来越多地通过采用半定量测量的病变活动,如标准化摄取值(SUV)来确定对治疗的早期反应。然而,使用来自治疗前的基线扫描的SUV来预测未来的治疗反应或者预后方面的肿瘤行为的能力是有限的。由于医学图像可能包含了比肉眼可以感知到的更有用的信息成为共识,使得“影像组学”领域诞生,由此可以通过计算后处理技术提取更多的特征。近年来,越来越多的证据表明通过放射学图像纹理分析获得的,反映肿瘤内体素的强度的潜在空间性区域差异和异质性参数,可能产生额外的预测和预后信息。希望这些组织特征的测量可能比现有的成像生物标志物更好地进行组织表征,以及在临床试验或未来的个性化癌症治疗中更好地分层治疗。在这篇综述中,我们专注于描述18FDG PET / CT中纹理分析的新兴方法以及其他成像方式的文献,以及如何测量图像中体素灰度强度的空间区域性差异,来提供额外的预测和预后信息,并推测潜在的生物学机制。

Abstact

18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) is now routinely used in oncological imaging for diagnosis and staging and increasingly to determine early response to treatment, often employing semiquantitative measures of lesion activity such as the standardized uptake value (SUV). However, the ability to predict the behaviour of a tumour in terms of future therapy response or prognosis using SUVs from a baseline scan prior to treatment is limited. It is recognized that medical images contain more useful information than may be perceived with the naked eye, leading to the field of “radiomics” whereby additional features can be extracted by computational postprocessing techniques. In recent years, evidence has slowly accumulated showing that parameters obtained by texture analysis of radiological images, reflecting the underlying spatial variation and heterogeneity of voxel intensities within a tumour, may yield additional predictive and prognostic information. It is hoped that measurement of these textural features may allow better tissue characterization as well as better stratification of treatment in clinical trials, or individualization of future cancer treatment in the clinic, than is possible with current imaging biomarkers. In this review we focus on the literature describing the emerging methods of texture analysis in 18FDG PET/CT, as well as other imaging modalities, and how the measurement of spatial variation of voxel grey-scale intensity within an image may provide additional predictive and prognostic information, and postulate the underlying biological mechanisms.

阅读原文:PMID: 23064544  DOI: 10.1007/s00259-012-2247-0


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