Diagnostic and Interventional Radiology
Chest Imaging - Original Article

Effect of iterative reconstruction techniques on image quality in low radiation dose chest CT: a phantom study

1.

Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China

2.

Department of Radiology, Weihai Wendeng Central Hospital, Weihai, Shandong, China

Diagn Interv Radiol 2019; 25: 442-450
DOI: 10.5152/dir.2019.18539
Read: 160 Downloads: 48 Published: 04 November 2019

PURPOSE

We aimed to evaluate the quality of chest computed tomography (CT) images obtained with low-dose CT using three iterative reconstruction (IR) algorithms.

 

METHODS

Two 64-detector spiral CT scanners (HDCT and iCT) were used to scan a chest phantom containing 6 ground-glass nodules (GGNs) at 11 radiation dose levels. CT images were reconstructed by filtered back projection or three IR algorithms. Reconstructed images were analyzed for CT values, average noise, contrast-to-noise ratio (CNR) values, subjective image noise, and diagnostic acceptability of the GGNs. Repeated-measures analysis of variance was used for statistical analyses.

 

RESULTS

Average noise decreased and CNR increased with increasing radiation dose when the same reconstruction algorithm was applied. Average image noise was significantly lower when reconstructed with MBIR than with iDOSE4 at the same low radiation doses. The two radiologists showed good interobserver consistency in image quality with kappa 0.83. A significant relationship was found between image noise and diagnostic acceptability of the GGNs.

 

CONCLUSION

Three IR algorithms are able to reduce the image noise and improve the image quality of low-dose CT. In the same radiation dose, the low-dose CT image quality reconstructed with MBIR algorithms is better than that of other IR algorithms.

 

You may cite this article as: Xu Y, Zhang T, Hu Z, et al. Effect of iterative reconstruction techniques on image quality in low radiation dose chest CT: a phantom study. Diagn Interv Radiol 2019; 25:442–450.

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