Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Department of Oncology and Haemato-Oncology, Università degli Studi di Milano, Milan, Italy.
Med Phys. 2023 Feb;50(2):750-762. doi: 10.1002/mp.16054. Epub 2022 Nov 9.
Aim of this study is to assess the repeatability of radiomic features on magnetic resonance images (MRI) and their stability to variations in time of repetition (TR), time of echo (TE), slice thickness (ST), and pixel spacing (PS) using vegetable phantoms.
The organic phantom was realized using two cucumbers placed inside a cylindrical container, and the analysis was performed using T1-weighted (T1w), T2-weighted (T2w), and diffusion-weighted images. One dataset was used to test the repeatability of the radiomic features, whereas other four datasets were used to test the sensitivity of the different MRI sequences to image acquisition parameters (TR, TE, ST, and PS). Four regions of interest (ROIs) were segmented: two for the central part of each cucumber and two for the external parts. Radiomic features were extracted from each ROI using Pyradiomics. To assess the effect of preprocessing on the reduction of variability, features were extracted both before and after the preprocessing. The coefficient of variation (CV) and intra-class correlation coefficient (ICC) were used to evaluate variability.
The use of intensity standardization increased the stability for the first-order statistics features. Shape and size features were always stable for all the analyses. Textural features were particularly sensitive to changes in ST and PS, although some increase in stability could be obtained by voxel size resampling. When images underwent image preprocessing, the number of stable features (ICC > 0.75 and mean absolute CV < 0.3) was 33 for apparent diffusion coefficient (ADC), 52 for T1w, and 73 for T2w.
The most critical source of variability is related to changes in voxel size (either caused by changes in ST or PS). Preprocessing increases features stability to both test-retest and variation of the image acquisition parameters for all the types of analyzed MRI (T1w, T2w, and ADC), except for ST.
本研究旨在使用植物体模评估磁共振成像（MRI）中放射组学特征的可重复性及其对重复时间（TR）、回波时间（TE）、层厚（ST）和像素间距（PS）变化的稳定性。
有机体模是使用两个放在圆柱形容器内的黄瓜制成的，分析采用 T1 加权（T1w）、T2 加权（T2w）和弥散加权图像进行。一个数据集用于测试放射组学特征的重复性，而其他四个数据集用于测试不同 MRI 序列对图像采集参数（TR、TE、ST 和 PS）的敏感性。四个感兴趣区（ROI）进行分割：每个黄瓜的中心部分两个，外部部分两个。使用 Pyradiomics 从每个 ROI 提取放射组学特征。为了评估预处理对降低变异性的影响，在预处理前后都提取了特征。变异系数（CV）和组内相关系数（ICC）用于评估变异性。
使用强度标准化增加了一阶统计特征的稳定性。形状和大小特征在所有分析中均始终稳定。纹理特征对 ST 和 PS 的变化特别敏感，但通过体素大小重采样可以获得一定程度的稳定性增加。当图像进行图像预处理时，对于表观扩散系数（ADC）有 33 个稳定特征（ICC>0.75，平均绝对 CV<0.3），T1w 有 52 个，T2w 有 73 个。
最关键的变异性来源与体素大小的变化有关（无论是由 ST 还是 PS 引起的）。预处理增加了所有分析的 MRI（T1w、T2w 和 ADC）类型的测试-重测和图像采集参数变化的特征稳定性，除了 ST。
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