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Ultralow-dose CT with knowledge-based iterative model reconstruction (IMR) in evaluation of pulmonary tuberculosis: comparison of radiation dose and image quality

  • Chenggong Yan
  • Chunyi Liang
  • Jun Xu
  • Yuankui Wu
  • Wei Xiong
  • Huan Zheng
  • Yikai XuEmail author
Chest
  • 54 Downloads

Abstract

Objectives

To evaluate the image quality of ultralow-dose computed tomography (ULDCT) reconstructed with knowledge-based iterative model reconstruction (IMR) in patients with pulmonary tuberculosis (TB).

Methods

This IRB-approved prospective study enrolled 59 consecutive patients (mean age, 43.9 ± 16.6 years; F:M 18:41) with known or suspected pulmonary TB. Patients underwent a low-dose CT (LDCT) using automatic tube current modulation followed by an ULDCT using fixed tube current. Raw image data were reconstructed with filtered-back projection (FBP), hybrid iterative reconstruction (iDose), and IMR. Objective measurements including CT attenuation, image noise, and contrast-to-noise ratio (CNR) were assessed and compared using repeated-measures analysis of variance. Overall image quality and visualization of normal and pathological findings were subjectively scored on a five-point scale. Radiation output and subjective scores were compared by the paired Student t test and Wilcoxon signed-rank test, respectively.

Results

Compared with FBP and iDose, IMR yielded significantly lower noise and higher CNR values at both dose levels (p < 0.01). Subjective ratings for pathological findings including centrilobular nodules, consolidation, tree-in-bud, and cavity were significantly better with ULDCT IMR images than those with LDCT iDose images (p < 0.01), but blurred edges were observed. With IMR implementation, a 59% reduction of the mean effective dose was achieved with ULDCT (0.28 ± 0.02 mSv) compared with LDCT (0.69 ± 0.15 mSv) without impairing image quality (p < 0.001).

Conclusions

IMR offers considerable noise reduction and improvement in image quality for patients with pulmonary TB undergoing chest ULDCT at an effective dose of 0.28 mSv.

Key Points

• Radiation dose is a major concern for tuberculosis patients requiring repeated follow-up CT.

• IMR allows substantial radiation dose reduction in chest CT without compromising image quality.

• ULDCT reconstructed with IMR allows accurate depiction of CT features of pulmonary tuberculosis.

Keywords

Tomography, X-ray computed Infection Thorax Pulmonary tuberculosis Radiation dosage 

Abbreviations

CNR

Contrast-to-noise ratio

CTDIvol

Volume CT dose index

DLP

Dose-length product

DRI

Dose right index

ED

Effective dose

FBP

Filtered-back projection

FOM

Figure of merit

GGO

Ground-glass opacity

IMR

Iterative model reconstruction

IR

Iterative reconstruction

LDCT

Low-dose CT

ROI

Region of interest

TB

Tuberculosis

ULDCT

Ultralow-dose CT

Notes

Acknowledgements

The authors would like to thank Dr. Yan Jiang from the Philips Healthcare for providing technical support.

Funding

This study has received funding by the National Key Research and Development Program of China (grant 2016YFC0107104) and the Science and Technology Planning Project of Guangdong Province, China (grant 2015B010131011).

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is Prof. Yikai Xu.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• prospective

• observational

• performed at one institution

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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Chenggong Yan
    • 1
  • Chunyi Liang
    • 1
  • Jun Xu
    • 2
  • Yuankui Wu
    • 1
  • Wei Xiong
    • 1
  • Huan Zheng
    • 1
  • Yikai Xu
    • 1
    Email author
  1. 1.Department of Medical Imaging Center, Nanfang HospitalSouthern Medical UniversityGuangzhouPeople’s Republic of China
  2. 2.Department of Hematology, Nanfang HospitalSouthern Medical UniversityGuangzhouPeople’s Republic of China

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