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

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.

SUBMITTER: He L 

PROVIDER: S-EPMC5056507 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature