定量心脏磁共振 T1 和 T2 图谱心肌放射学特征的测试重复性。

IF 2.1 4区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Magnetic resonance imaging Pub Date : 2024-07-25 DOI:10.1016/j.mri.2024.110217
Daniela Marfisi , Marco Giannelli , Chiara Marzi , Jacopo Del Meglio , Andrea Barucci , Luigi Masturzo , Claudio Vignali , Mario Mascalchi , Antonio Traino , Giancarlo Casolo , Stefano Diciotti , Carlo Tessa
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引用次数: 0

摘要

心脏磁共振(MR)成像的放射组学已被证明可用于研究各种心肌疾病。因此,评估放射组学特征测量的重复性至关重要。本研究旨在评估从定量 T1 和 T2 图谱中提取的心肌放射学特征的测试-重复性。24 名临床心脏磁共振成像转诊受试者(平均年龄 54 ± 18 岁)参加了这项研究。在 1.5 T 下,分别通过 MOLLI 和 T2 预处理 TrueFISP 采集序列对每个受试者进行了 T1 和 T2 图谱分析。然后,在短轴切片中,从包括整个左心室心肌的感兴趣区提取 98 个不同类别(形状、一阶、二阶)的放射学特征。对重复性的评估采用了不同的互补分析方法:类内相关系数(ICC)和一致性限值(LOA)(即两次重复测量之间 95% 的百分比差异预计在哪个区间内)。就 ICC 和 LOA 而言,放射组学特征的重复性范围相对较大。总体而言,44.9% 和 38.8% 的放射线学特征显示 T1 和 T2 图的 ICC 值大于 0.75,而 25.5% 和 23.4% 的放射线学特征显示 LOA 在 ±10% 之间。T1(平均值、中位数、10珀森特里值、90珀森特里值、根均方值、Imc2、RunLengthNon-UniformityNormalized、RunPercentage和ShortRunEmphasis)和T2(最大直径、RunLengthNon-UniformityNormalized、RunPercentage、ShortRunEmphasis)图的放射学特征子集的ICC值均大于0.75,LOA值在±5%之间。总体而言,从 T1 地图中提取的放射学特征比从 T2 地图中提取的特征表现出更好的可重复性,其中形状特征的可重复性优于一阶特征和纹理特征。此外,就 ICC 和 LOA 而言,T1 和 T2 地图分别只有 9 个和 4 个有限的放射学特征子集显示出较高的可重复性。这些结果证实了在放射学特征估计中评估测试-再测试重复性的重要性,可能有助于在临床或研究中更有效/可靠地使用心肌 T1 和 T2 图谱放射学。
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Test-retest repeatability of myocardial radiomic features from quantitative cardiac magnetic resonance T1 and T2 mapping

Radiomics of cardiac magnetic resonance (MR) imaging has proved to be potentially useful in the study of various myocardial diseases. Therefore, assessing the repeatability degree in radiomic features measurement is of fundamental importance.

The aim of this study was to assess test-retest repeatability of myocardial radiomic features extracted from quantitative T1 and T2 maps.

A representative group of 24 subjects (mean age 54 ± 18 years) referred for clinical cardiac MR imaging were enrolled in the study. For each subject, T1 and T2 mapping through MOLLI and T2-prepared TrueFISP acquisition sequences, respectively, were performed at 1.5 T. Then, 98 radiomic features of different classes (shape, first-order, second-order) were extracted from a region of interest encompassing the whole left ventricle myocardium in a short axis slice. The repeatability was assessed performing different and complementary analyses: intraclass correlation coefficient (ICC) and limits of agreement (LOA) (i.e., the interval within which 95% of the percentage differences between two repeated measures are expected to lie).

Radiomic features were characterized by a relatively wide range of repeatability degree in terms of both ICC and LOA. Overall, 44.9% and 38.8% of radiomic features showed ICC values > 0.75 for T1 and T2 maps, respectively, while 25.5% and 23.4% of radiomic features showed LOA between ±10%. A subset of radiomic features for T1 (Mean, Median, 10Percentile, 90Percentile, RootMeanSquared, Imc2, RunLengthNonUniformityNormalized, RunPercentage and ShortRunEmphasis) and T2 (MaximumDiameter, RunLengthNonUniformityNormalized, RunPercentage, ShortRunEmphasis) maps presented both ICC > 0.75 and LOA between ±5%.

Overall, radiomic features extracted from T1 maps showed better repeatability performance than those extracted from T2 maps, with shape features characterized by better repeatability than first-order and textural features. Moreover, only a limited subset of 9 and 4 radiomic features for T1 and T2 maps, respectively, showed high repeatability degree in terms of both ICC and LOA. These results confirm the importance of assessing test-retest repeatability degree in radiomic feature estimation and might be useful for a more effective/reliable use of myocardial T1 and T2 mapping radiomics in clinical or research studies.

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来源期刊
Magnetic resonance imaging
Magnetic resonance imaging 医学-核医学
CiteScore
4.70
自引率
4.00%
发文量
194
审稿时长
83 days
期刊介绍: Magnetic Resonance Imaging (MRI) is the first international multidisciplinary journal encompassing physical, life, and clinical science investigations as they relate to the development and use of magnetic resonance imaging. MRI is dedicated to both basic research, technological innovation and applications, providing a single forum for communication among radiologists, physicists, chemists, biochemists, biologists, engineers, internists, pathologists, physiologists, computer scientists, and mathematicians.
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