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Lung nodules assessment in ultra-low-dose CT with iterative reconstruction compared to conventional dose CT

  
@article{QIMS20071,
	author = {Shiqi Jin and Bo Zhang and Lina Zhang and Shu Li and Songbai Li and Peiling Li},
	title = {Lung nodules assessment in ultra-low-dose CT with iterative reconstruction compared to conventional dose CT},
	journal = {Quantitative Imaging in Medicine and Surgery},
	volume = {8},
	number = {5},
	year = {2018},
	keywords = {},
	abstract = {Background: To retrospectively assess whether the low-voltage lung CT scan coupled with iterative reconstruction algorithms can be an optimal scanning method for measuring the size and density of lung nodules in cancer patients. 
Methods: Eighty two cancer patients receiving both chest scan with low-voltage (80 kV) and abdomen CT scan with standard voltage (120 kV) were enrolled in this study. Lung nodules were measured manually and semi-automatically by two different computer-aided diagnosis (CAD) systems. The nodules were then divided into large-, medium- and small-size groups based on their largest diameter. Additionally, the nodules were categorized into three different groups according to their density: calcified, solid and partial-solid nodules. The 3D volumes, average diameter and CT value of lung nodules were measured using the two CAD semi-automated systems, and the CT values were compared with regards to the different tube voltages. Furthermore, the accuracy and reliability of CAD systems were validated in the large nodules. 
Results: The scores of subjective evaluation indicated that the quality of lung nodule images yielded optimal clinical diagnostic value for both 80 kV (2.35±0.054) and 120 kV (2.51±0.053) scanning methods, with a strong inter-observer consistency (Kappa =0.848 and 0.829, respectively). Intraclass correlation coefficient (ICC) and Bland-Altman plot revealed that two CAD systems produced the consistent results. Mean CT values of large nodules (n=18) were significantly different between 80 and 120 kV (−28.11±47.39 vs. −39.61±43.32 HU, P},
	issn = {2223-4306},	url = {https://qims.amegroups.org/article/view/20071}
}