Skip to main content
SpringerLink
Log in

Automatic alignment of myocardial perfusion PET and 64-slice coronary CT angiography on hybrid PET/CT

  • Original Article
  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

Background

Hybrid PET/CT allows for acquisition of cardiac PET and coronary CT angiography (CCTA) in one session. However, PET and CCTA are acquired with differing breathing protocols and require software registration. We aimed to validate automatic correction for breathing misalignment between PET and CCTA acquired on hybrid scanner.

Methods

Single-session hybrid PET/CT studies of rest/stress 13N-ammonia PET and CCTA in 32 consecutive patients were considered. Automated registration of PET left ventricular (LV) surfaces with CCTA volumes was evaluated by comparing with expert manual alignment by two observers.

Results

The average initial misalignments between the position of LV on PET and CCTA were 27.2 ± 11.8, 13.3 ± 11.5, and 14.3 ± 9.1 mm in x, y, and z axes on rest, and 26.3 ± 10.2, 11.1 ± 9.5, and 11.7 ± 7.1 mm in x, y, and z axes on stress, respectively. The automated PET-CCTA co-registration had 95% agreement as judged visually. Compared with expert manual alignment, the translation errors of the algorithm were 5.3 ± 2.8 mm (rest) and 6.0 ± 3.5 mm (stress). 3D visualization of combined coronary vessel anatomy and hypoperfusion from PET could be made without further manual adjustments.

Conclusion

Software co-registration of CCTA and PET myocardial perfusion imaging on hybrid PET/CT scanners is necessary, but can be performed automatically, facilitating integrated 3D display on PET/CT.

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

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7

Similar content being viewed by others

References

  1. Berman D, Hachamovitch R, Shaw L, Friedman J, Hayes S, Thomson L, et al. Roles of nuclear cardiology, cardiac computed tomography, and cardiac magnetic resonance: assessment of patients with suspected coronary artery disease. J Nucl Med 2006;47:74-82.

    PubMed  Google Scholar 

  2. Taylor AJ, Cerqueira M, Hodgson JM, Mark D, Min J, O’Gara P, et al. ACCF/SCCT/ACR/AHA/ASE/ASNC/NASCI/SCAI/SCMR 2010 appropriate use criteria for cardiac computed tomography: A report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, the Society of Cardiovascular Computed Tomography, the American College of Radiology, the American Heart Association, the American Society of Echocardiography, the American Society of Nuclear Cardiology, the North American Society for Cardiovascular Imaging, the Society for Cardiovascular Angiography and Interventions, and the Society for Cardiovascular Magnetic Resonance. J Am Coll Cardiol 2010;56:1864-94.

    Article  PubMed  Google Scholar 

  3. Gaemperli O, Schepis T, Valenta I, Husmann L, Scheffel H, Duerst V, et al. Cardiac image fusion from stand-alone SPECT and CT: clinical experience. J Nucl Med 2007;48:696-703.

    Article  PubMed  Google Scholar 

  4. Santana CA, Garcia EV, Faber TL, Sirineni GK, Esteves FP, Sanyal R, et al. Diagnostic performance of fusion of myocardial perfusion imaging (MPI) and computed tomography coronary angiography. J Nucl Cardiol 2009;16:201-11.

    Article  PubMed  Google Scholar 

  5. Gaemperli O, Schepis T, Kalff V, Namdar M, Valenta I, Stefani L, et al. Validation of a new cardiac image fusion software for three-dimensional integration of myocardial perfusion SPECT and stand-alone 64-slice CT angiography. Eur J Nucl Med Mol Imaging 2007;34:1097-106.

    Article  PubMed  Google Scholar 

  6. Slomka P, Cheng V, Dey D, Woo J, Ramesh A, Van Kriekinge S, et al. Quantitative analysis of myocardial perfusion SPECT anatomically guided by coregistered 64-slice coronary CT angiography. J Nucl Med 2009;50:1621-30.

    Article  PubMed  Google Scholar 

  7. Woo J, Slomka PJ, Dey D, Cheng VY, Hong BW, Ramesh A, et al. Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion SPECT. Med Phys 2009;36:5467-79.

    Article  PubMed  Google Scholar 

  8. Aladl UE, Hurwitz GA, Dey D, Levin D, Drangova M, Slomka PJ. Automated image registration of gated cardiac single-photon emission computed tomography and magnetic resonance imaging. J Magn Reson Imaging 2004;19:283-90.

    Article  PubMed  Google Scholar 

  9. Johansson L, Mattsson S, Nosslin B, Leide-Svegborn S. Effective dose from radiopharmaceuticals. Eur J Nucl Med 1992;19:933-8.

    Article  PubMed  CAS  Google Scholar 

  10. Raff G, Abidov A, Achenbach S, Berman D, Boxt L, Budoff M, et al. SCCT guidelines for the interpretation and reporting of coronary computed tomographic angiography. J Cardiovasc Comput Tomogr 2009;3:122-36.

    Article  PubMed  Google Scholar 

  11. Slomka PJ, Nishina H, Berman DS, Akincioglu C, Abidov A, Friedman JD, et al. Automated quantification of myocardial perfusion SPECT using simplified normal limits. J Nucl Cardiol 2005;12:66-77.

    Article  PubMed  Google Scholar 

  12. Berman D, Kang X, Hayes S, Friedman J, Cohen I, Abidov A, et al. Adenosine myocardial perfusion single-photon emission computed tomography in women compared with men. Impact of diabetes mellitus on incremental prognostic value and effect on patient management. J Am Coll Cardiol 2003;41:1125-33.

    Article  PubMed  Google Scholar 

  13. Shaw LJ, Berman DS, Maron DJ, Mancini GB, Hayes SW, Hartigan PM, et al. Optimal medical therapy with or without percutaneous coronary intervention to reduce ischemic burden: Results from the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) trial nuclear substudy. Circulation 2008;117:1283-91.

    Article  PubMed  Google Scholar 

  14. Nakazato R, Berman D, Dey D, Le Meunier L, Hayes S, Fermin J, et al. Automated quantitative Rb-82 3D PET/CT myocardial perfusion imaging: Normal limits and correlation with invasive coronary angiography. J Nucl Cardiol 2011 Dec 28 [Epub ahead of print].

  15. Slomka PJ, Alexanderson E, Jácome R, Jiménez M, Romero E, Meave A, et al. Comparison of clinical tools for measurements of regional stress and rest myocardial blood flow assessed with 13N-ammonia PET/CT. J Nucl Med 2012;53:171-81.

    Article  PubMed  CAS  Google Scholar 

  16. Slomka P, Germano G, Kavanagh P, Javadi M, Berman D, Bengel F. Evaluation of a new automatic algorithm for quantification of ECG-gated 82Rb cardiac PET. J Nucl Med 2009;50:1167.

    Article  Google Scholar 

  17. Slomka PJ. Software approach to merging molecular with anatomic information. J Nucl Med 2004;45:36S-45S.

    PubMed  Google Scholar 

  18. Busch S, Johnson TR, Nikolaou K, von Ziegler F, Knez A, Reiser MF, et al. Visual and automatic grading of coronary artery stenoses with 64-slice CT angiography in reference to invasive angiography. Eur Radiol 2007;17:1445-51.

    Article  PubMed  Google Scholar 

  19. Levin D, Aladl U, Germano G, Slomka P. Techniques for efficient, real-time, 3D visualization of multi-modality cardiac data using consumer graphics hardware. Comput Med Imaging Graph 2005;29:463-75.

    Article  PubMed  Google Scholar 

  20. Germano G, Kavanagh PB, Slomka PJ, Van Kriekinge SD, Pollard G, Berman DS. Quantitation in gated perfusion SPECT imaging: The Cedars-Sinai approach. J Nucl Cardiol 2007;14:433-54.

    Article  PubMed  Google Scholar 

  21. Rispler S, Keidar Z, Ghersin E, Roguin A, Soil A, Dragu R, et al. Integrated single-photon emission computed tomography and computed tomography coronary angiography for the assessment of hemodynamically significant coronary artery lesions. J Am Coll Cardiol 2007;49:1059-67.

    Article  PubMed  Google Scholar 

  22. Di Carli MF, Dorbala S, Hachamovitch R. Integrated cardiac PET-CT for the diagnosis and management of CAD. J Nucl Cardiol 2006;13:139-44.

    Article  PubMed  Google Scholar 

  23. Namdar M, Hany TF, Koepfli P, Siegrist PT, Burger C, Wyss CA, et al. Integrated PET/CT for the assessment of coronary artery disease: A feasibility study. J Nucl Med 2005;46:930-5.

    PubMed  Google Scholar 

  24. Javadi M, Mahesh M, McBride G, Voicu C, Epley W, Merrill J, et al. Lowering radiation dose for integrated assessment of coronary morphology and physiology: First experience with step-and-shoot CT angiography in a rubidium 82 PET-CT protocol. J Nucl Cardiol 2008;15:783-90.

    PubMed  Google Scholar 

  25. Slomka PJ, Baum RP. Multimodality image registration with software: State-of-the-art. Eur J Nucl Med Mol Imaging 2009;36:S44-55.

    Article  PubMed  Google Scholar 

  26. Slomka P, Nishina H, Berman D, Kang X, Akincioglu C, Friedman J, et al. “Motion-frozen” display and quantification of myocardial perfusion. J Nucl Med 2004;45:1128-34.

    PubMed  Google Scholar 

  27. Di Carli MF, Dorbala S, Curillova Z, Kwong RJ, Goldhaber SZ, Rybicki FJ, et al. Relationship between CT coronary angiography and stress perfusion imaging in patients with suspected ischemic heart disease assessed by integrated PET-CT imaging. J Nucl Cardiol 2007;14:799-809.

    Article  PubMed  Google Scholar 

  28. Kajander S, Joutsiniemi E, Saraste M, Pietilä M, Ukkonen H, Saraste A, et al. Cardiac positron emission tomography/computed tomography imaging accurately detects anatomically and functionally significant coronary artery disease. Circulation 2010;122:603-13.

    Article  PubMed  CAS  Google Scholar 

  29. Einstein AJ, Moser KW, Thompson RC, Cerqueira MD, Henzlova MJ. Radiation dose to patients from cardiac diagnostic imaging. Circulation 2007;116:1290-305.

    Article  PubMed  Google Scholar 

  30. Husmann L, Herzog BA, Gaemperli O, Tatsugami F, Burkhard N, Valenta I, et al. Diagnostic accuracy of computed tomography coronary angiography and evaluation of stress-only single-photon emission computed tomography/computed tomography hybrid imaging: Comparison of prospective electrocardiogram-triggering vs. retrospective gating. Eur Heart J 2009;30:600-7.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported in part by a grant to Dr Berman from the Diane and Gilford Glazer Foundation. We would like to thank Mark Hyun from Cedars-Sinai Medical Center for his technical help. We would like to thank Arpine Oganyan for editing and proof-reading the text. Drs Daniel Berman and Piotr Slomka receive royalties from the software employed in the study. All others disclose no current conflict of interest.

Author information

Authors and Affiliations

  1. Artificial Intelligence in Medicine Program, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Taper Building Suite A047, Los Angeles, CA, 90048, USA

    Ryo Nakazato MD, PhD, Daniel S. Berman MD & Piotr J. Slomka PhD

  2. Department of Biomedical Sciences and Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA

    Damini Dey PhD

  3. David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA

    Damini Dey PhD, Daniel S. Berman MD & Piotr J. Slomka PhD

  4. Unidad PET/CT Ciclotrón, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico, DF, Mexico

    Erick Alexánderson MD, Aloha Meave MD, Moisés Jiménez MD, Edgar Romero MD, Rodrigo Jácome MD & Marco Peña MD

  5. Instituto Nacional de Cardiología Ignacio Chávez Mexico, Mexico, DF, Mexico

    Erick Alexánderson MD, Aloha Meave MD & Moisés Jiménez MD

Authors
  1. Ryo Nakazato MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Damini Dey PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Erick Alexánderson MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Aloha Meave MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Moisés Jiménez MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Edgar Romero MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rodrigo Jácome MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Marco Peña MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Daniel S. Berman MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Piotr J. Slomka PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Piotr J. Slomka PhD.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Nakazato, R., Dey, D., Alexánderson, E. et al. Automatic alignment of myocardial perfusion PET and 64-slice coronary CT angiography on hybrid PET/CT. J. Nucl. Cardiol. 19, 482–491 (2012). https://doi.org/10.1007/s12350-012-9528-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-012-9528-7

Keywords

Search

Navigation