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Feasibility of iterative model reconstruction technique in low dose dual phase contrast-enhanced chest CT / 中国医学影像技术
Chinese Journal of Medical Imaging Technology ; (12): 768-772, 2017.
Article in Chinese | WPRIM | ID: wpr-609652
ABSTRACT
Objective To investigate the feasibility of low dose dual phase contrast-enhanced chest CT with iterative mod el reconstruction (IMR) technique.Methods Totally 130 patients with suspected pulmonary occupying lesions underwent dual phase contrast-enhanced chest CT,who were randomly assigned into 2 groups (group A and group B,each n=65).Patients in group A were scanned with 100 kV,DoseRight technique with dose right index 10,and images were reconstructed with the hybrid iterative reconstruction (iDose4).While patients in group B were scanned with 80 kV,DoseRight technique with dose right index 8,and images were reconstructed with iterative model reconstruction (IMR).The objective image quality,subjective image scores and the excellence rate of vascular visualization were compared in both pulmonary artery (PA) and bronchial artery (BA) phases.The radiation dose was also calculated.Results The effective dose was (3.30 ±0.89)mSv in group A and (1.27 ±0.19)mSv in group B.Compared to group A,the effective dose reduced 61.52% in group B (P<0.001).Lower image noise and greater CNR were obtained in group B compared to group A in both PA and BA phases (all P<0.001).No significant difference was found in subjective image scores of lung and mediastinal setting and the excellence rate of vascular visualization in both groups (all P>0.05).Conclusion Using IMR,dual phase contrast-enhanced chest CT allows for a radiation dose reduction up to 61.52%,meanwhile,ensures the image quality and meets the diagnostic requirements.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Medical Imaging Technology Year: 2017 Type: Article