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Initial exploration of coronary stent image subtraction using dual-layer spectral CT

  • Le Qin
  • ShengJia Gu
  • ChiHua Chen
  • Huan Zhang
  • ZhenBin Zhu
  • XingBiao Chen
  • Qun Han
  • FuHua Yan
  • WenJie YangEmail author
Computed Tomography
  • 21 Downloads

Abstract

Objectives

This study aimed to investigate the feasibility of coronary stent image subtraction using spectral tools derived from dual-layer spectral computed tomography (CT).

Methods

Forty-three patients (65 stents) who underwent coronary CT angiography using dual-layer spectral CT were included. Conventional, 50-keV (kilo electron-volt), 100-keV, and virtual non-contrast (VNC) images were reconstructed from the same cardiac phase. Stents were subtracted on VNC images from conventional (convsub), 100-keV (100-keVsub), and 50-keV (50-keVsub) images. The in-stent lumen diameters were measured on subtraction, conventional, and 100-keV images. Subjective evaluation of reader confidence and subtractive quality was evaluated. Friedman tests were performed to compare in-stent lumen diameters and subjective evaluation among different images. Correlation between stent diameter and subjective evaluation was expressed as Spearman’s rank correlation coefficient (rs). The diagnostic accuracy was assessed according to invasive coronary angiography (ICA) performed in 11 patients (20 stents).

Results

In-stent lumen diameters were significantly larger on subtraction images than those on conventional and 100-keV images (p < 0.05). Higher reader confidence was found on 100-keV, convsub, 100-keVsub, and 50-keVsub images compared with conventional images (p < 0.05). Subtractive quality of 100-keVsub images was better than that of convsub images (p = 0.037). A moderate-to-strong correlation between stent diameter and subjective evaluation was found (rs = 0.527~0.790, p < 0.05). Higher specificity, positive predictive value, and negative predictive value of subtraction images were shown by ICA results.

Conclusions

Subtraction images derived from dual-layer spectral CT enhanced in-stent lumen visibility and could potentially improve diagnostic performance for evaluating coronary stents.

Key Points

• Dual-layer spectral CT enabled good subtractive quality of coronary stents without misregistration artifacts.

• Subtraction images could improve in-stent lumen visibility.

• Reader confidence and diagnostic performance were enhanced with subtraction images.

Keywords

Computed tomography angiography Stents Subtraction technique 

Abbreviations

BMI

Body mass index

CCTA

Coronary computed tomography angiography

CTDIvol

Volume of CT dose index

DLP

Dose length product

ECG

Electrocardiogram

ED

Effective dose

HR

Heart rate

HU

Hounsfield unit

ICA

Invasive coronary angiography

ICC

Intraclass correlation coefficient

ISR

In-stent restenosis

keV

Kilo electron-volt

NPV

Negative predictive value

PCI

Percutaneous coronary intervention

PPV

Positive predictive value

ROI

Region of interest

SEM

Standard error of measurement

VNC

Virtual non-contrast

WL

Window level

WW

Window width

Notes

Acknowledgements

The authors thank Baisong Wang, PhD, a statistic teacher at Shanghai JiaoTong University, for providing statistical analysis. We also thank Yan Jiang and JianQing Sun for their great technical support.

Funding

The authors state that this work has not received any funding.

Compliance with ethical standards

Guarantor

The scientific guarantor of this publication is WenJie Yang.

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 waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• cross-sectional study

• performed at one institution

References

  1. 1.
    André F, Korosoglou G, Hosch W et al (2013) Performance of dual source versus 256-slice multi-slice CT in the evaluation of 16 coronary artery stents. Eur J Radiol 82:601–607CrossRefGoogle Scholar
  2. 2.
    Maintz D, Burg MC, Seifarth H et al (2008) Update on multidetector coronary CT angiography of coronary stents: in vitro evaluation of 29 different stent types with dual-source CT. Eur Radiol 19:42–49CrossRefGoogle Scholar
  3. 3.
    Ebersberger U, Tricarico F, Schoepf UJ et al (2013) CT evaluation of coronary artery stents with iterative image reconstruction: improvements in image quality and potential for radiation dose reduction. Eur Radiol 23:125–132CrossRefGoogle Scholar
  4. 4.
    Stehli J, Fuchs TA, Singer A et al (2015) First experience with single-source, dual-energy CCTA for monochromatic stent imaging. Eur Heart J Cardiovasc Imaging 16:507–512CrossRefGoogle Scholar
  5. 5.
    Alani A, Nakanishi R, Budoff MJ (2014) Recent improvement in coronary computed tomography angiography diagnostic accuracy. Clin Cardiol 37:428–433CrossRefGoogle Scholar
  6. 6.
    Kalisz K, Halliburton S, Abbara S et al (2017) Update on cardiovascular applications of multienergy CT. Radiographics 37:1955–1974CrossRefGoogle Scholar
  7. 7.
    Rajiah P, Rong R, Martinez-Rios C, Rassouli N, Landeras L (2017) Benefit and clinical significance of retrospectively obtained spectral data with a novel detector-based spectral computed tomography - initial experiences and results. Clin Imaging 49:65–72CrossRefGoogle Scholar
  8. 8.
    Fuchs A, Kühl JT, Chen MY et al (2015) Feasibility of coronary calcium and stent image subtraction using 320-detector row CT angiography. J Cardiovasc Comput Tomogr 9:393–398CrossRefGoogle Scholar
  9. 9.
    Yamaguchi T, Ichikawa K, Takahashi D, Sugaya T, Furuya J, Igarashi K (2017) A new contrast enhancement protocol for subtraction coronary computed tomography requiring a short breath-holding time. Acad Radiol 24:38–44Google Scholar
  10. 10.
    Ananthakrishnan L, Rajiah P, Ahn R et al (2017) Spectral detector CT-derived virtual non-contrast images: comparison of attenuation values with unenhanced CT. Abdom Radiol (NY) 42:702–709CrossRefGoogle Scholar
  11. 11.
    Hickethier T, Baeßler B, Kroeger JR et al (2017) Monoenergetic reconstructions for imaging of coronary artery stents using spectral detector CT: in-vitro experience and comparison to conventional images. J Cardiovasc Comput Tomogr 11:33–39CrossRefGoogle Scholar
  12. 12.
    American Association of Physicists in Medicine (2008) The measurement, reporting, and management of radiation dose in CT: report of AAPM task group 23 of the diagnostic imaging council CT committee. Technical report, College Park, MD: AAPM, 2008: AAPM report 96Google Scholar
  13. 13.
    Mangold S, Cannaó PM, Schoepf UJ et al (2016) Impact of an advanced image-based monoenergetic reconstruction algorithm on coronary stent visualization using third generation dual-source dual-energy CT: a phantom study. Eur Radiol 26:1871–1878CrossRefGoogle Scholar
  14. 14.
    Ehn S, Sellerer T, Muenzel D et al (2018) Assessment of quantification accuracy and image quality of a full-body dual-layer spectral CT system. J Appl Clin Med Phys 19:204–217CrossRefGoogle Scholar
  15. 15.
    de Vet HC, Terwee CB, Knol DL, Bouter LM (2006) When to use agreement versus reliability measures. J Clin Epidemiol 59:1033–1039CrossRefGoogle Scholar
  16. 16.
    Kottner J, Audigé L, Brorson S et al (2011) Guidelines for reporting reliability and agreement studies (GRRAS) were proposed. J Clin Epidemiol 64:96–106CrossRefGoogle Scholar
  17. 17.
    Amanuma M, Kondo T, Sano T et al (2016) Assessment of coronary in-stent restenosis: value of subtraction coronary computed tomography angiography. Int J Cardiovasc Imaging 32:661–670CrossRefGoogle Scholar
  18. 18.
    Kidoh M, Utsunomiya D, Oda S et al (2015) Optimized subtraction coronary CT angiography protocol for clinical use with short breath-holding time-initial experience. Acad Radiol 22:117–120CrossRefGoogle Scholar
  19. 19.
    Halpern EJ, Halpern DJ, Yanof JH et al (2009) Is coronary stent assessment improved with spectral analysis of dual energy CT? Acad Radiol 16:1241–1250CrossRefGoogle Scholar
  20. 20.
    Ozguner O, Dhanantwari A, Halliburton S, Wen G, Utrup S, Jordan D (2018) Objective image characterization of a spectral CT scanner with dual-layer detector. Phys Med Biol 63:025027Google Scholar
  21. 21.
    Moon JW, Park BK, Kim CK, Park SY (2012) Evaluation of virtual unenhanced CT obtained from dual-energy CT urography for detecting urinary stones. Br J Radiol 85:e176–e181CrossRefGoogle Scholar
  22. 22.
    Patino M, Prochowski A, Agrawal MD et al (2016) Material separation using dual-energy CT: current and emerging applications. Radiographics 36:1087–1105CrossRefGoogle Scholar
  23. 23.
    Mangold S, Thomas C, Fenchel M et al (2012) Virtual nonenhanced dual-energy CT urography with tin-filter technology determinants of detection of urinary calculi in the renal collecting system. Radiology 264:119–125CrossRefGoogle Scholar
  24. 24.
    Esposito A, Colantoni C, De Cobelli F et al (2013) Multidetector computed tomography for coronary stents imaging high-voltage (140-kVp) prospective ECG-triggered versus standard-voltage (120-kVp) retrospective ECG-gated helical scanning. J Comput Assist Tomogr 37:395–401CrossRefGoogle Scholar
  25. 25.
    Menke J, Unterberg-Buchwald C, Staab W, Sohns JM, Seif Amir Hosseini A, Schwarz A (2013) Head-to-head comparison of prospectively triggered vs retrospectively gated coronary computed tomography angiography: meta-analysis of diagnostic accuracy, image quality, and radiation dose. Am Heart J 165:154–163 e153Google Scholar
  26. 26.
    Andreini D, Pontone G, Bartorelli AL et al (2011) High diagnostic accuracy of prospective ECG-gating 64-slice computed tomography coronary angiography for the detection of in-stent restenosis: in-stent restenosis assessment by low-dose MDCT. Eur Radiol 21:1430–1438CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Le Qin
    • 1
  • ShengJia Gu
    • 1
  • ChiHua Chen
    • 1
  • Huan Zhang
    • 1
  • ZhenBin Zhu
    • 2
  • XingBiao Chen
    • 3
  • Qun Han
    • 3
  • FuHua Yan
    • 1
  • WenJie Yang
    • 1
    Email author
  1. 1.Department of RadiologyRuijin Hospital Affiliated to Shanghai Jiaotong University School of MedicineShanghaiChina
  2. 2.Department of CardiologyRuijin Hospital Affiliated to Shanghai Jiaotong University School of MedicineShanghaiChina
  3. 3.Philips HealthcareShanghaiChina

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