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The application of dual-layer spectral detector computed tomography in solitary pulmonary nodule identification

霍恩斯菲尔德秤 肺癌 医学 核医学 组内相关 肺孤立结节 接收机工作特性 双重能量 放射科 黑色素瘤 结核(地质) 计算机断层摄影术 病理 内科学 古生物学 心理测量学 癌症研究 骨质疏松症 骨矿物 生物 临床心理学
作者
Qingyun Wen,Yong Yue,Jin Shang,Xiaomei Lü,Lu Gao,Yang Hou
出处
期刊:Quantitative imaging in medicine and surgery [AME Publishing Company]
卷期号:11 (2): 521-532 被引量:18
标识
DOI:10.21037/qims-20-2
摘要

Differentiating between malignant solitary pulmonary nodules (SPNs) and other lung diseases remains a substantial challenge. The latest generation of dual-energy computed tomography (CT), which realizes dual-energy technology at the detector level, has clinical potential for distinguishing lung cancer from other benign SPNs. This study aimed to evaluate the performance of dual-layer spectral detector CT (SDCT) for the differentiation of SPNs.Spectral images of 135 SPNs confirmed by pathology were retrospectively analyzed in both the arterial phase (AP) and the venous phase (VP). Patients were classified into two groups [the malignant group (n=93) and the benign group (n=42)], with the malignant group further divided into small cell lung cancer (SCLC, n=30) and non-small cell lung cancer (NSCLC, n=63) subtypes. The slope of the spectral Hounsfield Unit (HU) curve (λHU), normalized iodine concentration (NIC), CT values of 40 keV monochromatic images (CT40keV), and normalized arterial enhancement fraction (NAEF) in contrast-enhanced images were calculated and compared between the benign and malignant groups, as well as between the SCLC and NSCLC subgroups. ROC curve analysis was performed to assess the diagnostic performance of the above parameters. Seventy cases were randomly selected and independently measured by two radiologists, and intraclass correlation coefficient (ICC) and Bland-Altman analyses were performed to calculate the reliability of the measurements.Except for NAEF (P=0.23), the values of the parameters were higher in the malignant group than in the benign group (all P<0.05). NIC, λHU, and CT40keV performed better in the VP (NICVP, λVPHU, and CTVP40keV) (P<0.001), with an area under the ROC curve (AUC) of 0.93, 0.89, and 0.89 respectively. With respective cutoffs of 0.31, 1.83, and 141.00 HU, the accuracy of NICVP, λVPHU, and CTVP40keV was 91.11%, 85.19%, and 88.15%, respectively. In the subgroup differentiating NSCLC and SCLC, the diagnostic performances of NICAP (AUC =0.89) were greater than other parameters. NICAP had an accuracy of 86.02% when the cutoff was 0.14. ICC and Bland-Altman analyses indicated that the measurement of SDCT has great reproducibility.Quantitative measures from SDCT can help to differentiate benign from malignant SPNs and may help with the further subclassification of malignant cancer into SCLC and NSCLC.
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