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Comprehensive visualization of multimodal cardiac imaging data for assessment of coronary artery disease: first clinical results of the SMARTVis tool

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

In clinical practice, both coronary anatomy and myocardial perfusion information are needed to assess coronary artery disease (CAD). The extent and severity of coronary stenoses can be determined using computed tomography coronary angiography (CTCA); the presence and amount of ischemia can be identified using myocardial perfusion imaging, such as perfusion magnetic resonance imaging (PMR). To determine which specific stenosis is associated with which ischemic region, experts use assumptions on coronary perfusion territories. Due to the high variability between patient’s coronary artery anatomies, as well as the uncertain relation between perfusion territories and supplying coronary arteries, patient-specific systems are needed.

Material and methods

We present a patient-specific visualization system, called Synchronized Multimodal heART Visualization (SMARTVis), for relating coronary stenoses and perfusion deficits derived from CTCA and PMR, respectively. The system consists of the following comprehensive components: (1) two or three-dimensional fusion of anatomical and functional information, (2) automatic detection and ranking of coronary stenoses, (3) estimation of patient-specific coronary perfusion territories.

Results

The potential benefits of the SMARTVis tool in assessing CAD were investigated through a case-study evaluation (conventional vs. SMARTVis tool): two experts analyzed four cases of patients with suspected multivessel coronary artery disease. When using the SMARTVis tool, a more reliable estimation of the relation between perfusion deficits and stenoses led to a more accurate diagnosis, as well as a better interobserver diagnosis agreement.

Conclusion

The SMARTVis comprehensive visualization system can be effectively used to assess disease status in multivessel CAD patients, offering valuable new options for the diagnosis and management of these patients.

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Abbreviations

BEP:

Bull’s eye plot

CAD:

Coronary artery disease

CTCA:

Computed tomography coronary angiography

CPR:

Curved-planar reformatted

FFR:

Fractional flow reserve

ICA:

Invasive coronary angiography

ICP:

Iterative closest point

LAD:

Left anterior descending artery

LCX:

Left circumflex artery

MPR:

Multi-planar reformatted

MPRI:

Myocardial perfusion reserve index

PMR:

Perfusion magnetic resonance imaging

RCA:

Right coronary artery

SMARTVis:

Synchronized multimodal heart visualization

TIC:

Time-intensity curve

References

  1. Lloyd-Jones D, Adams RJ, Brown TM, Carnethon M, Dai S, De Simone G, Ferguson TB, Ford E, Furie K, Gillespie C, Go A, Greenlund K, Haase N, Hailpern S, Ho PM, Howard V, Kissela B, Kittner S, Lackland D, Lisabeth L, Marelli A, McDermott MM, Meigs J, Mozaffarian D, Mussolino M, Nichol G, Roger VL, Rosamond W, Sacco R, Sorlie P, Roger VL, Thom T, Wasserthiel-Smoller S, Wong ND, Wylie-Rosett J, A.H.A. S. Committee and S.S. Subcommittee, Heart disease and stroke statistics-2010 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circul 121(12):e46–e215

  2. Weustink A, de Feyter P (2011) The role of multi-slice computed tomography in stable angina management—a current perspective. Neth Heart J, in press. doi:10.1007/s12471-011-0096-2

  3. Kirschbaum S, Springeling T, Rossi A, Duckers E, GutiTrrez-Chico J, Regar E, de Feyter P, van Geuns R (2011) Comparison of adenosine magnetic resonance perfusion imaging with invasive coronary flow reserve and fractional flow reserve in patients with suspected coronary artery disease. Int J Cardiol 147: 184– 186

    Article  PubMed  Google Scholar 

  4. Kirschbaum S, van Geuns R (2011) Cardiac magnetic resonance imaging to detect and evaluate ischemic heart disease. Hell J Cardiol 50: 119–126

    Google Scholar 

  5. AHA: (2002) Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart. Circulation 105: 539–542

    Article  PubMed  Google Scholar 

  6. Pereztol-Valdés O, Candell-Riera J, Santana-Boado C, Angel J, Aguadé-Bruix S, Castell-Conesa J, Garcia E, Soler-Soler J (2005) Correspondence between left ventricular 17 myocardial segments and coronary arteries. Eur Heart J 26(24): 637–643

    Article  Google Scholar 

  7. Termeer M, Bescós J, Breeuwer M, Vilanova A, Gerritsen F, Gröller M (2007) Covicad: comprehensive visualization of coronary artery disease. IEEE Trans Vis Comput Graph 13(6): 1632–1641

    Article  PubMed  Google Scholar 

  8. Faber T, Santana C, Garcia E, Candell-Riera J, Folks R, Peifer J, Hopper A, Aguade S, Angel J, Klein J (2004) Three-dimensional fusion of coronary arteries with myocardial perfusion distributions: clinical validation. J Nucl Med 45(5): 745–753

    PubMed  Google Scholar 

  9. Gaemperli O, Schepis T, Kalff V, Namdar M, Valenta I, Stefani L, Desbiolles L, Leschka S, Husmann L, Alkadhi H, Kaufmann P (2007) 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 34: 1097–1106

    Article  PubMed  Google Scholar 

  10. van Werkhoven J, Schuijf J, Gaemperli O, Jukema J, Boersma E, Wijns W, Stolzmann P, Alkadhi H, Valenta I, Stokkel M, Kroft L, de Roos A, Pundziute G, Scholte A, van der Wall E, Kaufmann P, Bax J (2009) Computed tomography and gated single-photon emission computed tomography in patients with suspected coronary artery disease. J Am Coll Cardiol 53: 623–632

    Article  PubMed  Google Scholar 

  11. Scholte A, Roos C, van Werkhoven J (2010) Function and anatomy: SPECT-MPI and MSCT coronary angiography. EuroIntervention 6(G): 94–100

    Google Scholar 

  12. Termeer M, Bescós J, Breeuwer M, Vilanova A, Gerritsen F, Gröller M, Nagel E (2008) Visualization of myocardial perfusion derived from coronary anatomy. IEEE Trans Vis Comput Graph 14(6): 1595–1602

    Article  PubMed  Google Scholar 

  13. Kühnel C, Hennemuth A, Oeltze S, Boskamp T, Peitgen H (2008) Enhanced cardio vascular image analysis by combined representation of results from dynamic MRI and anatomic CTA. In: Proceedings of SPIE medical imaging, vol 6918

  14. Kühnel C, Hennemuth A, Peitgen H, Mahnken A (2008) New analysis tools for the comprehensive assessment of the coronary arteries and myocardial viability in CT data sets. Proc Comput Cardiol 35: 733–736

    Google Scholar 

  15. Kirişli H, Gupta V, Kirschbaum S, Neefjes L, van Geuns R, Mollet N, Lelieveldt B, Reiber J, van Walsum T, Niessen W (2011) A patient-specific visualization tool for comprehensive analysis of coronary CTA and perfusion MRI data. In: Proceedings of SPIE medical imaging

  16. Metz C, Schaap M, Weustink A, Mollet N, van Walsum T, Niessen W (2009) Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach. Med Phys 36(12): 5568–5579

    Article  PubMed  CAS  Google Scholar 

  17. Schaap M, van Walsum T, Neefjes L, Metz C, Capuano E, de Bruijne M, Niessen W (2011) Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA. IEEE Trans Med Imaging, in press

  18. Kirişli H, Schaap M, Klein S, Papadopoulou S, Bonardi M, Chen C, Weustink A, Mollet N, Vonken EPA, van der Geest R, van Walsum T, Niessen W (2010) Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multi-center and multi-vendor study. Med Phys 37(12): 6279–6292. doi:10.1118/1.3512795

    Article  PubMed  Google Scholar 

  19. Milles J, der Geest R, Jerosch-Herold M, Reiber J, Lelieveldt B (2008) Fully automated motion correction in first-pass myocardial perfusion mr image sequences. IEEE Trans Med Imaging 27(11): 1611–1621

    Article  PubMed  Google Scholar 

  20. Gupta V, Hendriks E, Milles J, van der Geest R, Jerosch-Herold M, Reiber J, Lelieveldt B (2010) Fully automatic registration and segmentation of first-pass myocardial perfusion mr image sequences. Acad Radiol 17(11): 1375–1385

    Article  PubMed  Google Scholar 

  21. Debruyne M, Hubert M, Suykens J (2008) Model selection in kernel based regression using the influence function. J Mach Learn Res 9: 2377–2400

    Google Scholar 

  22. Beliveau P, Setser R, Cheriet F, White R, O’Donnell T (2007) Computation of coronary perfusion territories from CT angiography. Proc Comput Cardiol 34: 753–756

    Google Scholar 

  23. Yin RK (2009) Case study research: design and methods. 4th edn. SAGE Publications, Beverly Hills, CA

    Google Scholar 

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Correspondence to Hortense A. Kirişli.

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Kirişli, H.A., Gupta, V., Kirschbaum, S.W. et al. Comprehensive visualization of multimodal cardiac imaging data for assessment of coronary artery disease: first clinical results of the SMARTVis tool. Int J CARS 7, 557–571 (2012). https://doi.org/10.1007/s11548-011-0657-2

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  • DOI: https://doi.org/10.1007/s11548-011-0657-2

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