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  • Title: Correlation between dual-energy spectral CT imaging parameters and pathological grades of non-small cell lung cancer.
    Author: Lin LY, Zhang Y, Suo ST, Zhang F, Cheng JJ, Wu HW.
    Journal: Clin Radiol; 2018 Apr; 73(4):412.e1-412.e7. PubMed ID: 29221718.
    Abstract:
    AIM: To investigate the correlation between pathological grades of non-small cell lung cancers (NSCLCs) and quantitative parameters generated in dual-energy spectral computed tomography (CT). MATERIALS AND METHODS: Fifty-three patients with NSCLCs who underwent preoperative dual-energy spectral CT imaging and surgical resection were evaluated retrospectively. These patients were divided into a low-grade group and a high-grade group based on their histopathological differentiation. In the arterial phase (AP) and venous phase (VP), iodine concentration (IC) in cancers was measured in iodine-based material decomposition images, and normalised to the IC in the aorta to calculate the normalised iodine concentration (NIC), the spectral CT curve was generated from the monochromatic images to calculate the slope of the spectral curve (λHU). Differences in quantitative parameters (NIC and λHU) were compared using the two-sample t-test. The correlations between spectral CT parameters and tumour grades were evaluated using the Spearman rank correlation analysis. Receiver operating characteristic (ROC) curves were generated to calculate their diagnostic efficacies. RESULTS: The NIC and λHU in the low-grade NSCLC group were significantly higher than those in the high-grade NSCLC group both in AP and VP (all p<0.001). There was a significant negative correlation between spectral CT parameters and pathological grades by the Spearman rank correlation (all p<0.001). ROC analysis indicated that λHU in VP provided the best diagnostic performance in distinguishing high-grade cancers from low-grade cancers (area under the ROC curve [AUC], 0.914; sensitivity, 85.7%; specificity, 84.4%). CONCLUSION: The quantitative parameters in dual-energy spectral CT imaging provide useful information to differentiate the pathological grades of NSCLCs.
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