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参数特征图在纠正不同感兴趣区体积中的作用:一项活体肝脏 MRI 研究。

The role of parametric feature maps to correct different volume of interest sizes: an in vivo liver MRI study.

机构信息

Charité-Universitätsmedizin Berlin, Department of Radiology, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Hindenburgdamm 30, 12203, Berlin, Germany.

出版信息

Eur Radiol Exp. 2023 Sep 6;7(1):48. doi: 10.1186/s41747-023-00362-9.

Abstract

BACKGROUND

Different volume of interest (VOI) sizes influence radiomic features. This study examined if translating images into feature maps before feature sampling could compensate for these effects in liver magnetic resonance imaging (MRI).

METHODS

T1- and T2-weighted sequences from three different scanners (two 3-T scanners, one 1.5-T scanner) of 66 patients with normal abdominal MRI were included retrospectively. Three differently sized VOIs (10, 20, and 30 mm in diameter) were drawn in the liver parenchyma (right lobe), excluding adjacent structures. Ninety-three features were extracted conventionally using PyRadiomics. All images were also converted to 93 parametric feature maps using a pretested software. Agreement between the three VOI sizes was assessed with overall concordance correlation coefficients (OCCCs), while OCCCs > 0.85 were rated reproducible. OCCCs were calculated twice: for the VOI sizes of 10, 20, and 30 mm and for those of 20 and 30 mm.

RESULTS

When extracted from original images, only 4 out of the 93 features were reproducible across all VOI sizes in T1- and T2-weighted images. When the smallest VOI was excluded, 5 features (T1-weighted) and 7 features (T2-weighted) were reproducible. Extraction from parametric maps increased the number of reproducible features to 9 (T1- and T2-weighted) across all VOIs. Excluding the 10-mm VOI, reproducibility improved to 16 (T1-weighted) and 55 features (T2-weighted). The stability of all other features also increased in feature maps.

CONCLUSIONS

Translating images into parametric maps before feature extraction improves reproducibility across different VOI sizes in normal liver MRI.

RELEVANCE STATEMENT

The size of the segmented VOI influences the feature quantity of radiomics, while software-based conversion of images into parametric feature maps before feature sampling improves reproducibility across different VOI sizes in MRI of normal liver tissue.

KEY POINTS

• Parametric feature maps can compensate for different VOI sizes. • The effect seems dependent on the VOI sizes and the MRI sequence. • Feature maps can visualize features throughout the entire image stack.

摘要

背景

不同的感兴趣区(VOI)大小会影响放射组学特征。本研究旨在探讨在进行特征采样之前,将图像转换为特征图是否可以补偿肝脏磁共振成像(MRI)中这些影响。

方法

回顾性纳入 66 例腹部 MRI 正常患者的三个不同扫描仪(两台 3T 扫描仪,一台 1.5T 扫描仪)的 T1 加权和 T2 加权序列。在肝实质(右叶)中分别绘制三个不同大小的 VOI(直径 10、20 和 30mm),排除相邻结构。使用 PyRadiomics 常规提取 93 个特征。使用预测试软件将所有图像也转换为 93 个参数特征图。使用整体一致性相关系数(OCCCs)评估三种 VOI 大小之间的一致性,而 OCCCs>0.85 被评为可重复的。OCCCs 计算了两次:一次是在 10、20 和 30mm 的 VOI 大小之间,另一次是在 20 和 30mm 的 VOI 大小之间。

结果

当从原始图像中提取时,仅在 T1 加权和 T2 加权图像中,4 个 93 个特征中的 4 个在所有 VOI 大小上具有可重复性。当排除最小 VOI 时,T1 加权图像中有 5 个特征和 T2 加权图像中有 7 个特征具有可重复性。从参数图中提取可将具有可重复性的特征数量增加到所有 VOI 上的 9 个(T1 和 T2 加权)。排除 10mm VOI 后,可重复性提高到 16 个(T1 加权)和 55 个特征(T2 加权)。所有其他特征的稳定性也在特征图中增加。

结论

在进行特征提取之前,将图像转换为参数图可改善正常肝脏 MRI 中不同 VOI 大小的可重复性。

相关性声明

所分割的 VOI 的大小会影响放射组学的特征数量,而基于软件的图像转换为参数特征图在进行特征采样之前可改善正常肝组织 MRI 中不同 VOI 大小的可重复性。

重点

•参数特征图可以补偿不同的 VOI 大小。•该效果似乎取决于 VOI 大小和 MRI 序列。•特征图可以可视化整个图像堆栈中的特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1969/10480134/cc34f8767008/41747_2023_362_Fig1_HTML.jpg

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