Correlation of dual-source computed tomography/dual-energyimaging with pathological grading of lung adenocarcinoma and its clinical value

Haifeng Jiang, Xiao Li

Abstract


Objective: To explore the correlation of dual-source computed tomography (DSCT)/dual-energy imaging with pathological grading of lung adenocarcinoma.

Methods: A total of 47 patients with lung adenocarcinoma were selected. Tissues were histopathologically confirmed by routine DSCT scanning and dual-energy enhanced scanning. Arterial-phase and venous-phase iodine distribution images and single-energy images at 40-190 keV were obtained. The region of interest was outlined to obtain CT values. The iodine concentrations of each tumor in two phases were recorded to calculate normalized iodine concentrations (NICs).

Results: The maximum diameter and minimum diameter of tumors in low differentiation (LD) group were significantly higher than those of high differentiation (HD) group (P<0.05). In LD group, 70.8% of margins were lobulated, which significantly exceeded that of HD group (30.4%) (P<0.05). Besides, 26.1% of patients in HD group were complicated with ground-glass opacity, which was significantly higher than that of LD group (4.2%) (P<0.05). In venous phase, there were significant differences between the two groups at low energy levels (40-70 keV) (P<0.05). At high energy levels (80-190 keV), the CT values of LD group were slightly higher than those of HD group. In arterial and venous phases, NICs of HD group were lower than those of LD group (P>0.05).

Conclusion: HD and LD groups could be predictably distinguished by single-energy images at low energy levels (40-70 keV) in the venous phase. Quantitative analysis of NIC in the venous phase is also valuable for predicting the pathological grade of lung adenocarcinoma.

doi: https://doi.org/10.12669/pjms.336.13320

How to cite this:Jiang H, Li X. Correlation of dual-source computed tomography/dual-energy imaging with pathological grading of lung adenocarcinoma and its clinical value. Pak J Med Sci. 2017;33(6):1429-1433.   doi: https://doi.org/10.12669/pjms.336.13320

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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