Institute of Clinical Radiology and Nuclear Medicine, University Medical Centre Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim.
Philips Healthcare Hamburg, Hamburg, Germany.
Invest Radiol. 2019 Apr;54(4):221-228. doi: 10.1097/RLI.0000000000000530.
The aim of this study was to investigate the robustness and reproducibility of radiomic features in different magnetic resonance imaging sequences.
A phantom was scanned on a clinical 3 T system using fluid-attenuated inversion recovery (FLAIR), T1-weighted (T1w), and T2-weighted (T2w) sequences with low and high matrix size. For retest data, scans were repeated after repositioning of the phantom. Test and retest datasets were segmented using a semiautomated approach. Intraobserver and interobserver comparison was performed. Radiomic features were extracted after standardized preprocessing of images. Test-retest robustness was assessed using concordance correlation coefficients, dynamic range, and Bland-Altman analyses. Reproducibility was assessed by intraclass correlation coefficients.
The number of robust features (concordance correlation coefficient and dynamic range ≥ 0.90) was higher for features calculated from FLAIR than from T1w and T2w images. High-resolution FLAIR images provided the highest percentage of robust features (n = 37/45, 81%). No considerable difference in the number of robust features was observed between low- and high-resolution T1w and T2w images (T1w low: n = 26/45, 56%; T1w high: n = 25/45, 54%; T2 low: n = 21/45, 46%; T2 high: n = 24/45, 52%). A total of 15 (33%) of 45 features showed excellent robustness across all sequences and demonstrated excellent intraobserver and interobserver reproducibility (intraclass correlation coefficient ≥ 0.75).
FLAIR delivers the most robust substrate for radiomic analyses. Only 15 of 45 features showed excellent robustness and reproducibility across all sequences. Care must be taken in the interpretation of clinical studies using nonrobust features.
本研究旨在探究不同磁共振成像序列中放射组学特征的稳健性和可重复性。
使用低和高矩阵大小的液体衰减反转恢复(FLAIR)、T1 加权(T1w)和 T2 加权(T2w)序列对体模在临床 3T 系统上进行扫描。对于复测数据,在重新定位体模后重复扫描。使用半自动方法对测试和复测数据集进行分割。进行了观察者内和观察者间的比较。在对图像进行标准化预处理后提取放射组学特征。使用一致性相关系数、动态范围和 Bland-Altman 分析评估测试-复测稳健性。使用组内相关系数评估可重复性。
与 T1w 和 T2w 图像相比,从 FLAIR 计算得到的特征具有更高数量的稳健特征(一致性相关系数和动态范围≥0.90)。高分辨率 FLAIR 图像提供了最高比例的稳健特征(n=37/45,81%)。低分辨率和高分辨率 T1w 和 T2w 图像之间稳健特征的数量没有明显差异(T1w 低:n=26/45,56%;T1w 高:n=25/45,54%;T2 低:n=21/45,46%;T2 高:n=24/45,52%)。共有 45 个特征中的 15 个(33%)在所有序列中表现出良好的稳健性,并表现出良好的观察者内和观察者间可重复性(组内相关系数≥0.75)。
FLAIR 为放射组学分析提供了最稳健的基础。只有 45 个特征中的 15 个在所有序列中表现出良好的稳健性和可重复性。在使用非稳健特征解释临床研究时必须谨慎。