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Cited by 256

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Effects of contrast-enhancement, reconstruction slice thickness and convolution kernel on the diagnostic performance of radiomics signature in solitary pulmonary nodule

Open access
He, Lan, Huang, Yanqi, Ma, Zelan, Liang, Cuishan, Liang, Changhong, Liu, Zaiyi·2016·Scientific Reports
DOI 10.1038/srep34921
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Abstract

The Effects of contrast-enhancement, reconstruction slice thickness and convolution kernel on the diagnostic performance of radiomics signature in solitary pulmonary nodule (SPN) remains unclear. 240 patients with SPNs (malignant, n = 180; benign, n = 60) underwent non-contrast CT (NECT) and contrast-enhanced CT (CECT) which were reconstructed with different slice thickness and convolution kernel. 150 radiomics features were extracted separately from each set of CT and diagnostic performance of each feature were assessed. After feature selection and radiomics signature construction, diagnostic performance of radiomics signature for discriminating benign and malignant SPN was also assessed with respect to the discrimination and classification and compared with net reclassification improvement (NRI). Our results showed NECT-based radiomics signature demonstrated better discrimination and classification capability than CECT in both primary (AUC: 0.862 vs. 0.829, p = 0.032; NRI = 0.578) and validation cohort (AUC: 0.750 vs. 0.735, p = 0.014; NRI = 0.023). Thin-slice (1.25 mm) CT-based radiomics signature had better diagnostic performance than thick-slice CT (5 mm) in both primary (AUC: 0.862 vs. 0.785, p = 0.015; NRI = 0.867) and validation cohort (AUC: 0.750 vs. 0.725, p = 0.025; NRI = 0.467). Standard convolution kernel-based radiomics signature had better diagnostic performance than lung convolution kernel-based CT in both primary (AUC: 0.785 vs. 0.770, p = 0.015; NRI = 0.156) and validation cohort (AUC: 0.725 vs.0.686, p = 0.039; NRI = 0.467). Therefore, this study indicates that the contrast-enhancement, reconstruction slice thickness and convolution kernel can affect the diagnostic performance of radiomics signature in SPN, of which non-contrast, thin-slice and standard convolution kernel-based CT is more informative.

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Metadata

Authors
He, L., Huang, Y., Ma, Z., Liang, C., Liang, C., & Liu, Z.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2016-10-10
Volume
6
Issue
1
Pages
34921-34921
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/srep34921
OpenAlex
W2530038065
Cited by
256
References
34
FWCI
14.45
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Effects of contrast-enhancement, reconstruction slice thickness and convolution kernel on the diagnostic performance of radiomics signature in solitary pulmonary nodule. https://app.cochat.ai/papers/10.1038/srep34921
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He, L., Huang, Y., Ma, Z., Liang, C., Liang, C., & Liu, Z. (2016). Effects of contrast-enhancement, reconstruction slice thickness and convolution kernel on the diagnostic performance of radiomics signature in solitary pulmonary nodule. Scientific Reports. https://doi.org/10.1038/srep34921

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