Reproducibility with repeat CT in radiomics study for rectal cancer

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.

Stability of radiomic features of apparent diffusion coefficient (ADC) maps for locally advanced rectal cancer in response to image pre-processing

“…Again, most of the available work on this topic was carried on lung and head and neck cancers using CT or PET. However, Hu et al [13] did demonstrate that volume-normalized features were more stable than not normalized features extracted from CT; while for MRI global textural descriptors showed more temporal stability than local-regional texture parameters [14].…”

Test–Retest Reproducibility Analysis of Bone Mineral Densitometry Radiomics Features

“…In our study, we found that most radiomics features extracted from BMD images are vulnerable against changes in the time of acquisition. Based on the results presented in the heatmap gure, we observed (20,22). In this study, the time between two image acquisitions was ten minutes, this time may not induce any change in the bone status.…”

Multicenter CT phantoms public dataset for radiomics reproducibility tests

“…[11][12][13] Studies have shown that feature reproducibility may be affected by differences in image acquisition parameters, such as slice thickness and reconstruction algorithm. [14][15][16][17] Since clinical image acquisition protocols are one of the major sources of variation among different hospitals, phantoms allow testing, comparison, and harmonization of radiomic features in similar vein to diagnostic imaging quality assurance. We hypothesize that even simplified phantoms allow us to test for radiomic features that may already become unstable even under tightly constrained conditions.…”