Author(s)

Dan Wang^#, Jianye Liang^#, Yiyong Liu, Changzheng Shi^*

Affiliation(s)

Medical Imaging Center, the First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, China

Corresponding Author

Changzheng Shi

ABSTRACT

Objectives: To collect and analyze the studies regarding the diagnostic value of spectral computed tomography (CT) for the differentiation between lung cancer and inflammatory mass. Material and Methods: English and Chinese studies regarding the differentiation of lung cancer from inflammatory mass with spectral CT were systematically searched in Medline, PubMed, China National Knowledge Infrastructure database (CNKI), Wanfang database, Cochrane Library and Embase from January 2006 to December 2017. Review Manager 5.3 was used to calculate the standardized mean difference (SMD) and 95% confidence intervals (CI) of iodine concentration (IC), water concentration (WC), normalized iodine concentration (NIC) and slope of energy spectrum curve. Stata 12.0 was used to evaluate the diagnostic efficacy and publication bias. Results: After a detailed search, 14 studies including 638 cases of lung cancer and 308 cases of inflammatory mass were admitted eventually. SMD and 95% CI of IC, WC, NIC and slope between lung cancer and inflammatory mass were -1.48 (-2.49, -0.48), 0.01 (-0.20, 0.23), -0.85 (-1.45, -0.25) and -0.82 (-1.52, -0.11). All the results showed statistical difference except WC. The sensitivity and specificity of NIC were 0.82 (0.75, 0.87), 0.93 (0.73, 0.98), respectively. Conclusion: The energy spectrum CT is adequate to differentiate lung cancer from inflammatory mass with the iodine-related indicators of IC, NIC, and slope of spectrum curve. Besides, NIC is regarded as the most valuable indicator for better reflection of blood supply of the lesions.

KEYWORDS

Spectral CT; lung cancer; inflammatory mass; standardized mean difference; Meta-analysis

CITE THIS PAPER

Dan Wang, Jianye Liang, Yiyong Liu, Changzheng Shi. Diagnostic performance of spectral imaging in the differentiation of lung cancer from inflammatory mass. Acta Translational Medicine. 2018, 1(2): 1-9.

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