Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Junction of Shahid Hemmat and Shahid Chamran Expressways, Tehran, Iran.
Department of Radiology, Johns Hopkins University, Baltimore, MD, 21287, USA.
Eur Radiol. 2017 Nov;27(11):4498-4509. doi: 10.1007/s00330-017-4859-z. Epub 2017 May 31.
The purpose of this study was to investigate the robustness of different PET/CT image radiomic features over a wide range of different reconstruction settings.
Phantom and patient studies were conducted, including two PET/CT scanners. Different reconstruction algorithms and parameters including number of sub-iterations, number of subsets, full width at half maximum (FWHM) of Gaussian filter, scan time per bed position and matrix size were studied. Lesions were delineated and one hundred radiomic features were extracted. All radiomics features were categorized based on coefficient of variation (COV).
Forty seven percent features showed COV ≤ 5% and 10% of which showed COV > 20%. All geometry based, 44% and 41% of intensity based and texture based features were found as robust respectively. In regard to matrix size, 56% and 6% of all features were found non-robust (COV > 20%) and robust (COV ≤ 5%) respectively.
Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent, and different settings have different effects on different features. Radiomic features with low COV can be considered as good candidates for reproducible tumour quantification in multi-center studies.
• PET/CT image radiomics is a quantitative approach assessing different aspects of tumour uptake. • Radiomic features robustness is an important issue over different image reconstruction settings. • Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent. • Robust radiomic features can be considered as good candidates for tumour quantification.
本研究旨在探究在广泛的不同重建设置下，不同 PET/CT 图像放射组学特征的稳健性。
进行了包括两台 PET/CT 扫描仪在内的体模和患者研究。研究了不同的重建算法和参数，包括子迭代次数、子集数量、高斯滤波器的半峰全宽（FWHM）、每个床位扫描时间和矩阵大小。对病变进行了描绘，并提取了 100 个放射组学特征。所有放射组学特征均基于变异系数（COV）进行分类。
47%的特征 COV≤5%，其中 10%的特征 COV＞20%。所有基于几何形状的、44%的基于强度的和 41%的基于纹理的特征分别被认为是稳健的。关于矩阵大小，56%和 6%的所有特征分别被认为是非稳健的（COV＞20%）和稳健的（COV≤5%）。
高级重建设置下的 PET/CT 图像放射组学的可变性和稳健性是特征依赖性的，不同的设置对不同的特征有不同的影响。具有低 COV 的放射组学特征可以被认为是多中心研究中肿瘤定量的可靠候选者。
PET/CT 图像放射组学是一种评估肿瘤摄取不同方面的定量方法。
放射组学特征的稳健性是不同图像重建设置中的一个重要问题。
高级重建设置下的 PET/CT 图像放射组学的可变性和稳健性是特征依赖性的。
稳健的放射组学特征可以被认为是肿瘤定量的可靠候选者。
