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图像扰动下CT影像组学和剂量组学特征的可重复性比较分析:一项针对宫颈癌患者的研究

Comparative Analysis of Repeatability in CT Radiomics and Dosiomics Features under Image Perturbation: A Study in Cervical Cancer Patients.

作者信息

Ma Zongrui, Zhang Jiang, Liu Xi, Teng Xinzhi, Huang Yu-Hua, Zhang Xile, Li Jun, Pan Yuxi, Sun Jiachen, Dong Yanjing, Li Tian, Chan Lawrence Wing Chi, Chang Amy Tien Yee, Siu Steven Wai Kwan, Cheung Andy Lai-Yin, Yang Ruijie, Cai Jing

机构信息

Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China.

Department of Radiation Oncology, Cancer Center, Peking University Third Hospital, Beijing 100191, China.

出版信息

Cancers (Basel). 2024 Aug 18;16(16):2872. doi: 10.3390/cancers16162872.

DOI:10.3390/cancers16162872
PMID:39199643
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11352227/
Abstract

This study aims to evaluate the repeatability of radiomics and dosiomics features via image perturbation of patients with cervical cancer. A total of 304 cervical cancer patients with planning CT images and dose maps were retrospectively included. Random translation, rotation, and contour randomization were applied to CT images and dose maps before radiomics feature extraction. The repeatability of radiomics and dosiomics features was assessed using intra-class correlation of coefficient (ICC). Pearson correlation coefficient (r) was adopted to quantify the correlation between the image characteristics and feature repeatability. In general, the repeatability of dosiomics features was lower compared with CT radiomics features, especially after small-sigma Laplacian-of-Gaussian (LoG) and wavelet filtering. More repeatable features (ICC > 0.9) were observed when extracted from the original, Large-sigma LoG filtered, and LLL-/LLH-wavelet filtered images. Positive correlations were found between image entropy and high-repeatable feature number in both CT and dose (r = 0.56, 0.68). Radiomics features showed higher repeatability compared to dosiomics features. These findings highlight the potential of radiomics features for robust quantitative imaging analysis in cervical cancer patients, while suggesting the need for further refinement of dosiomics approaches to enhance their repeatability.

摘要

本研究旨在通过宫颈癌患者的图像扰动来评估影像组学和剂量组学特征的可重复性。回顾性纳入了304例有计划CT图像和剂量图的宫颈癌患者。在影像组学特征提取之前,对CT图像和剂量图进行随机平移、旋转和轮廓随机化处理。使用组内相关系数(ICC)评估影像组学和剂量组学特征的可重复性。采用Pearson相关系数(r)来量化图像特征与特征可重复性之间的相关性。总体而言,与CT影像组学特征相比,剂量组学特征的可重复性较低,尤其是在小标准差高斯-拉普拉斯(LoG)和小波滤波之后。从原始图像、大标准差LoG滤波图像以及LLL-/LLH-小波滤波图像中提取时,观察到更多可重复的特征(ICC>0.9)。在CT和剂量方面,均发现图像熵与高可重复特征数量之间存在正相关(r=0.56,0.68)。影像组学特征比剂量组学特征具有更高的可重复性。这些发现突出了影像组学特征在宫颈癌患者稳健定量成像分析中的潜力,同时表明需要进一步完善剂量组学方法以提高其可重复性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/18a12b74b81d/cancers-16-02872-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/fb77790bb0a0/cancers-16-02872-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/477d12bf8291/cancers-16-02872-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/398f4b9e6a50/cancers-16-02872-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/7a9e50fbe83d/cancers-16-02872-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/18a12b74b81d/cancers-16-02872-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/fb77790bb0a0/cancers-16-02872-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/477d12bf8291/cancers-16-02872-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/398f4b9e6a50/cancers-16-02872-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/7a9e50fbe83d/cancers-16-02872-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/93a7/11352227/18a12b74b81d/cancers-16-02872-g005.jpg

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本文引用的文献

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