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基于 MRI 体模评估的放射组学特征稳健性。

Radiomics feature robustness as measured using an MRI phantom.

机构信息

Department of Radiation Physics, Unit 1420, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, TX, 77030, USA.

Department of Computational Medicine and Bioinformatics, University of Michigan, 500 S State Street, Ann Arbor, MI, 48109, USA.

出版信息

Sci Rep. 2021 Feb 17;11(1):3973. doi: 10.1038/s41598-021-83593-3.

DOI:10.1038/s41598-021-83593-3
PMID:33597610
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7889870/
Abstract

Radiomics involves high-throughput extraction of large numbers of quantitative features from medical images and analysis of these features to predict patients' outcome and support clinical decision-making. However, radiomics features are sensitive to several factors, including scanning protocols. The purpose of this study was to investigate the robustness of magnetic resonance imaging (MRI) radiomics features with various MRI scanning protocol parameters and scanners using an MRI radiomics phantom. The variability of the radiomics features with different scanning parameters and repeatability measured using a test-retest scheme were evaluated using the coefficient of variation and intraclass correlation coefficient (ICC) for both T1- and T2-weighted images. For variability measures, the features were categorized into three groups: large, intermediate, and small variation. For repeatability measures, the average T1- and T2-weighted image ICCs for the phantom (0.963 and 0.959, respectively) were higher than those for a healthy volunteer (0.856 and 0.849, respectively). Our results demonstrated that various radiomics features are dependent on different scanning parameters and scanners. The radiomics features with a low coefficient of variation and high ICC for both the phantom and volunteer can be considered good candidates for MRI radiomics studies. The results of this study will assist current and future MRI radiomics studies.

摘要

放射组学涉及从医学图像中提取大量定量特征,并对这些特征进行分析,以预测患者的预后并支持临床决策。然而,放射组学特征对包括扫描方案在内的多种因素敏感。本研究旨在使用 MRI 放射组学体模研究不同 MRI 扫描方案参数和扫描仪对 MRI 放射组学特征的稳健性。使用变异系数和组内相关系数 (ICC) 评估不同扫描参数和使用测试-再测试方案测量的重复性的放射组学特征的可变性。对于可变性度量,特征分为三大类:大、中、小变化。对于重复性度量,体模的平均 T1 和 T2 加权图像 ICC(分别为 0.963 和 0.959)高于健康志愿者(分别为 0.856 和 0.849)。我们的研究结果表明,各种放射组学特征取决于不同的扫描参数和扫描仪。对于体模和志愿者,变异系数低且 ICC 高的放射组学特征可以被认为是 MRI 放射组学研究的良好候选者。本研究的结果将有助于当前和未来的 MRI 放射组学研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/2fceca63a55a/41598_2021_83593_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/647d3c605352/41598_2021_83593_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/681105442005/41598_2021_83593_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/34d0f381ee98/41598_2021_83593_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/2fceca63a55a/41598_2021_83593_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/647d3c605352/41598_2021_83593_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/681105442005/41598_2021_83593_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/34d0f381ee98/41598_2021_83593_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/46bd/7889870/2fceca63a55a/41598_2021_83593_Fig4_HTML.jpg

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