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Diagnostic Value of Spectral CT Parameters in Differentiating Different Types of Lung Cancer
- Source :
- Journal of Medical Imaging and Health Informatics. 10:1804-1808
- Publication Year :
- 2020
- Publisher :
- American Scientific Publishers, 2020.
-
Abstract
- Background: This study proposed to quantitatively assess the value of spectral CT imaging parameters in differentiating different pathological types of lung cancer. Methods: Eighty five patients with lung cancer (66 non-mucinous adenocarcinomas, 7 Squamous cell carcinomas, 8 small cell carcinomas, 1 mucinous adenocarcinoma, 1 sarcomatoid carcinoma, 1 carcinoid, 1 large cell carcinoma) underwent CT plain scan, contrast enhanced CT scans in arterial phase (a) and venous phase (v) with spectral imaging mode on a GE Revolution Xtream CT scanner. The Spectral CT Imaging parameters: Iodine concentrations (IC) of lesion in arterial phase (ICLa) and venous phase (ICLv), Normalized IC (NICa/NICv)-normalized to the IC in the aorta, slope of the spectral HU curve (λHUa/λHUv) and monochromatic CT number (CT40keVa/CT40keVv, CT70keVa/CT70keVv) enhancement on 40 keV and 70 keV images were calculated. The One-way ANOVA or Kruskal-Wallis test was used to compare quantitative parameters among lung squamous carcinoma, small cell carcinoma and lung adenocarcinoma groups, Bonferroni method was used to correct P value for multiple comparisons. Results: Among the different pathological types of lung cancers, these quantitative parameters of spectral CT imaging CT70keVa has significant difference. The CT70keVa of lung adenocarcinoma was lower than small cell carcinoma (P = 0.048) and squamous cell carcinoma (P = 0.039), respectively. And these CT40keVa, CT70keVa/CT70keVv parameters of lung adenocarcinoma was lower than non-adenocarcinomas (P < 0.05). However, there was no significant difference in spectral CT parameters between small cell lung cancer and squamous cell lung cancer, small cell lung cancer and non-small cell carcinoma (P > 0.05). Conclusion: Spectral CT parameters may be of value in distinguishing different pathological types of lung cancer.
Details
- ISSN :
- 21567018
- Volume :
- 10
- Database :
- OpenAIRE
- Journal :
- Journal of Medical Imaging and Health Informatics
- Accession number :
- edsair.doi...........533ab10e0d2d67eabf246b6cf6184dc4
- Full Text :
- https://doi.org/10.1166/jmihi.2020.3189