Abstract
PurposeTo evaluate the reproducibility of radiomics features by repeating computed tomographic (CT) scans in rectal cancer. To choose stable radiomics features for rectal cancer.ResultsVolume normalized features are much more reproducible than unnormalized features. The average value of all slices is the most reproducible feature type in rectal cancer. Different filters have little effect for the reproducibility of radiomics features. For the average type features, 496 out of 775 features showed high reproducibility (ICC ≥ 0.8), 225 out of 775 features showed medium reproducibility (0.8 > ICC ≥ 0.5) and 54 out of 775 features showed low reproducibility (ICC < 0.5).Methods40 rectal cancer patients with stage II were enrolled in this study, each of whom underwent two CT scans within average 8.7 days. 775 radiomics features were defined in this study. For each features, five different values (value from the largest slice, maximum value, minimum value, average value of all slices and value from superposed intermediate matrix) were extracted. Meanwhile a LOG filter with different parameters was applied to these images to find stable filter value. Concordance correlation coefficients (CCC) and inter-class correlation coefficients (ICC) of two CT scans were calculated to assess the reproducibility, based on original features and volume normalized features.ConclusionsFeatures are recommended to be normalized to volume in radiomics analysis. The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction.
Highlights
As human oncology has a strong phenotypic difference from normal tissue, which may be visualized non-invasively by different imaging modalities, such as X-ray computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI)
40 rectal cancer patients with stage II were enrolled in this study, each of whom underwent two CT scans within average 8.7 days. 775 radiomics features were defined in this study
The average type radiomics features are the most stable features in rectal cancer. Further analysis of these features of rectal cancer can be warranted for treatment monitoring and prognosis prediction
Summary
As human oncology has a strong phenotypic difference from normal tissue, which may be visualized non-invasively by different imaging modalities, such as X-ray computed tomography (CT), positron emission tomography (PET), and magnetic resonance imaging (MRI). Radiomics become a novel approach because it can utilize medical imaging to quantify the tumor phenotype non-invasively for further study, such as patients’ survival, treatment monitoring and outcome prediction [2]. Recent publications have demonstrated that radiomics features be reproducibly measured from CT images for patients with non-small cell lung cancer [3]. For nonsmall cell lung cancer (NSCLC) patients, quantitative image features extracted from computed tomography (CT) images can be used to improve tumor diagnosis, staging, and response assessment [4]. No researches have been conducted to analyze which kind of extraction process is the best, including max slice, max value, min value, average value or matrix sum
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