Skip to main content
SpringerLink
Log in

Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance

  • Original Paper
  • Published:
The International Journal of Cardiovascular Imaging Aims and scope Submit manuscript

Abstract

We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p < 0.05). The use of IMR enables significant improvement of image quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Cheong BY, Muthupillai R, Wilson JM, Sung A, Huber S, Amin S, Elayda MA, Lee VV, Flamm SD (2009) Prognostic significance of delayed-enhancement magnetic resonance imaging: survival of 857 patients with and without left ventricular dysfunction. Circulation 120:2069–2076

    Article  PubMed  Google Scholar 

  2. Kim RJ, Wu E, Rafael A, Chen EL, Parker MA, Simonetti O, Klocke FJ, Bonow RO, Judd RM (2000) The use of contrast-enhanced magnetic resonance imaging to identify reversible myocardial dysfunction. N Engl J Med 343:1445–1453

    Article  CAS  PubMed  Google Scholar 

  3. Lardo AC, Cordeiro MA, Silva C, Amado LC, George RT, Saliaris AP, Schuleri KH, Fernandes VR, Zviman M, Nazarian S, Halperin HR, Wu KC, Hare JM, Lima JA (2006) Contrast-enhanced multidetector computed tomography viability imaging after myocardial infarction: characterization of myocyte death, microvascular obstruction, and chronic scar. Circulation 113:394–404

    Article  PubMed  PubMed Central  Google Scholar 

  4. Choe YH, Choo KS, Jeon ES, Gwon HC, Choi JH, Park JE (2008) Comparison of MDCT and MRI in the detection and sizing of acute and chronic myocardial infarcts. Eur J Radiol 66:292–299

    Article  PubMed  Google Scholar 

  5. Goetti R, Feuchtner G, Stolzmann P, Donati OF, Wieser M, Plass A, Frauenfelder T, Leschka S, Alkadhi H (2011) Delayed enhancement imaging of myocardial viability: low-dose high-pitch CT versus MRI. Eur Radiol 21:2091–2099

    Article  PubMed  Google Scholar 

  6. Matsuda T, Kido T, Itoh T, Saeki H, Shigemi S, Watanabe K, Kido T, Aono S, Yamamoto M, Matsuda T, Mochizuki T (2015) Diagnostic accuracy of late iodine enhancement on cardiac computed tomography with a denoise filter for the evaluation of myocardial infarction. Int J Cardiovasc Imaging 31:177–185

    Article  PubMed  Google Scholar 

  7. Kurata A, Kawaguchi N, Kido T, Inoue K, Suzuki J, Ogimoto A, Funada J, Higaki J, Miyagawa M, Vembar M, Mochizuki T (2013) Qualitative and quantitative assessment of adenosine triphosphate stress whole-heart dynamic myocardial perfusion imaging using 256-slice computed tomography. PLoS ONE 8:e83950

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kurobe Y, Kitagawa K, Ito T, Kurita Y, Shiraishi Y, Nakamori S, Nakajima H, Nagata M, Ishida M, Dohi K, Ito M, Sakuma H (2014) Myocardial delayed enhancement with dual-source CT: advantages of targeted spatial frequency filtration and image averaging over half-scan reconstruction. J Cardiovasc Comput Tomogr 8:289–298

    Article  PubMed  Google Scholar 

  9. Brodoefel H, Klumpp B, Reimann A, Ohmer M, Fenchel M, Schroeder S, Miller S, Claussen C, Kopp AF, Scheule AM (2007) Late myocardial enhancement assessed by 64-MSCT in reperfused porcine myocardial infarction: diagnostic accuracy of low-dose CT protocols in comparison with magnetic resonance imaging. Eur Radiol 17:475–483

    Article  CAS  PubMed  Google Scholar 

  10. Marin D, Nelson RC, Barnhart H, Schindera ST, Ho LM, Jaffe TA, Yoshizumi TT, Youngblood R, Samei E (2010) Detection of pancreatic tumors, image quality, and radiation dose during the pancreatic parenchymal phase: effect of a low-tube-voltage, high-tube-current CT technique–preliminary results. Radiology 256(2):450–459

    Article  PubMed  Google Scholar 

  11. Nieman K, Shapiro MD, Ferencik M, Nomura CH, Abbara S, Hoffmann U, Gold HK, Jang IK, Brady TJ, Cury RC (2008) Reperfused myocardial infarction: contrast-enhanced 64-Section CT in comparison to MR imaging. Radiology 247:49–56

    Article  PubMed  Google Scholar 

  12. Deseive S, Bauer RW, Lehmann R, Kettner M, Kaiser C, Korkusuz H, Tandi C, Theisen A, Schächinger V, Schoepf UJ, Vogl TJ, Kerl JM (2011) Dual-energy computed tomography for the detection of late enhancement in reperfused chronic infarction: a comparison to magnetic resonance imaging and histopathology in a porcine model. Invest Radiol 46:450–456

    Article  PubMed  Google Scholar 

  13. Silva AC, Lawder HJ, Hara A, Kujak J, Pavlicek W (2010) Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm. AJR Am J Roentgenol 194:191–199

    Article  PubMed  Google Scholar 

  14. Gramer BM, Muenzel D, Leber V, von Thaden AK, Feussner H, Schneider A, Vembar M, Soni N, Rummeny EJ, Huber AM (2012) Impact of iterative reconstruction on CNR and SNR in dynamic myocardial perfusion imaging in an animal model. Eur Radiol 22:2654–2661

    Article  CAS  PubMed  Google Scholar 

  15. Oda S, Utsunomiya D, Funama Y, Katahira K, Honda K, Tokuyasu S, Vembar M, Yuki H, Noda K, Oshima S, Yamashita Y (2014) A knowledge-based iterative model reconstruction algorithm: can super-low-dose cardiac CT be applicable in clinical settings? Acad Radiol 21:104–110

    Article  PubMed  Google Scholar 

  16. Yuki H, Utsunomiya D, Funama Y, Tokuyasu S, Namimoto T, Hirai T, Itatani R, Katahira K, Oshima S, Yamashita Y (2014) Value of knowledge-based iterative model reconstruction in low-kV 256-slice coronary CT angiography. J Cardiovasc Comput Tomogr 8:115–123

    Article  PubMed  Google Scholar 

  17. Kido T, Kido T, Nakamura M, Kawaguchi N, Nishiyama Y, Ogimoto A, Miyagawa M, Mochizuki T (2014) Three-dimensional phase-sensitive inversion recovery sequencing in the evaluation of left ventricular myocardial scars in ischemic and non-ischemic cardiomyopathy: comparison to three-dimensional inversion recovery sequencing. Eur J Radiol 83(12):2159–2166

    Article  PubMed  Google Scholar 

  18. Cerqueira MD, Weissman NJ, Dilsizian V, Jacobs AK, Kaul S, Laskey WK, Pennell DJ, Rumberger JA, Ryan T, Verani MS (2002) Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. A statement for healthcare professionals from the Cardiac Imaging Committee of the Council on Clinical Cardiology of the American Heart Association. Circulation 105:539–542

    Article  PubMed  Google Scholar 

  19. Kawaguchi N, Kurata A, Kido T, Nishiyama Y, Kido T, Miyagawa M, Ogimoto A, Mochizuki T (2014) Optimization of coronary attenuation in coronary computed tomography angiography using diluted contrast material. Circ J 78:662–670

    Article  PubMed  Google Scholar 

  20. Sternberg MR, Hadgu A (2001) A GEE approach to estimating sensitivity and specificity and coverage properties of the confidence intervals. Stat Med 20:1529–1539

    Article  CAS  PubMed  Google Scholar 

  21. Gerber BL, Belge B, Legros GJ, Lim P, Poncelet A, Pasquet A, Gisellu G, Coche E, Vanoverschelde JL (2006) Characterization of acute and chronic myocardial infarcts by multidetector computed tomography: comparison with contrast-enhanced magnetic resonance. Circulation 113:823–833

    Article  PubMed  Google Scholar 

  22. Oda S, Utsunomiya D, Funama Y, Awai K, Katahira K, Nakaura T, Yanaga Y, Namimoto T, Yamashita Y (2011) A low tube voltage technique reduces the radiation dose at retrospective ECG-gated cardiac computed tomography for anatomical and functional analyses. Acad Radiol 18:991–999

    Article  PubMed  Google Scholar 

  23. Wichmann JL, Arbaciauskaite R, Kerl JM, Frellesen C, Bodelle B, Lehnert T, Monsefi N, Vogl TJ, Bauer RW (2014) Evaluation of monoenergetic late iodine enhancement dual-energy computed tomography for imaging of chronic myocardial infarction. Eur Radiol 24:1211–1218

    Article  PubMed  Google Scholar 

  24. Langer C, Both M, Harders H, Lutz M, Eden M, Kühl C, Sattler B, Jansen O, Schaefer P, Frey N (2015) Late enhanced computed tomography in hypertrophic cardiomyopathy enables accurate left-ventricular volumetry. Eur Radiol 25:575–584

    Article  PubMed  Google Scholar 

  25. Rodríguez-Palomares JF, Ortiz-Pérez JT, Lee DC, Bucciarelli-Ducci C, Tejedor P, Bonow RO, Wu E (2015) Time elapsed after contrast injection is crucial to determine infarct transmurality and myocardial functional recovery after an acute myocardial infarction. J Cardiovasc Magn Reson 17:43

    Article  PubMed  PubMed Central  Google Scholar 

  26. Nakaura T, Nakamura S, Maruyama N, Funama Y, Awai K, Harada K, Uemura S, Yamashita Y (2012) Low contrast agent and radiation dose protocol for hepatic dynamic CT of thin adults at 256-detector row CT: effect of low tube voltage and hybrid iterative reconstruction algorithm on image quality. Radiology 264:445–454

    Article  PubMed  Google Scholar 

  27. Ryu YJ, Choi YH, Cheon JE, Ha S, Kim WS, Kim IO (2016) Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom. Pediatr Radiol 46:303–315

    Article  PubMed  Google Scholar 

  28. Oda S, Weissman G, Vembar M, Weigold WG (2014) Iterative model reconstruction: improved image quality of low-tube-voltage prospective ECG-gated coronary CT angiography images at 256-slice CT. Eur J Radiol 83:1408–1415

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology, Ehime University Graduate School of Medicine, Shitsukawa, Toon, Ehime, 791-0295, Japan

    Yuki Tanabe, Teruhito Kido, Akira Kurata, Naoki Fukuyama, Takahiro Yokoi, Tomoyuki Kido, Teruyoshi Uetani & Teruhito Mochizuki

  2. CT Clinical Science, Philips Healthcare, 595 Miner Road, Cleveland, OH, 44143, USA

    Mani Vembar & Amar Dhanantwari

  3. CT Clinical Scientist, Philips Electronics Japan, Kohnan 2-13-37, Minato-ku, Tokyo, 108-8507, Japan

    Shinichi Tokuyasu

  4. Department of Clinical Biostatistics, Section of Cancer Prevention and Epidemiology, Clinical Research Center, National Hospital Organization Shikoku Cancer Center, Minamiumenomoto, Matsuyama, Ehime, 791-0280, Japan

    Natsumi Yamashita

Authors
  1. Yuki Tanabe
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Teruhito Kido
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Akira Kurata
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Naoki Fukuyama
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Takahiro Yokoi
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tomoyuki Kido
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Teruyoshi Uetani
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mani Vembar
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Amar Dhanantwari
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Shinichi Tokuyasu
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Natsumi Yamashita
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Teruhito Mochizuki
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuki Tanabe.

Ethics declarations

Conflict of interest

Mani Vembar is an employee of Philips Healthcare. Amar Dhanantwari is an employee of Philips Healthcare. Shinichi Tokuyasu is an employee of Philips Electronics Japan. All the other authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tanabe, Y., Kido, T., Kurata, A. et al. Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance. Int J Cardiovasc Imaging 33, 1609–1618 (2017). https://doi.org/10.1007/s10554-017-1137-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10554-017-1137-8

Keywords

Search

Navigation