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Assessing the qualitative and quantitative impacts of simple two-class vs multiple tissue-class MR-based attenuation correction for cardiac PET/MR

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Journal of Nuclear Cardiology Aims and scope

Abstract

Background

Hybrid PET/MR imaging has significant potential in cardiology due to its combination of molecular PET imaging and cardiac MR. Multi-tissue-class MR-based attenuation correction (MRAC) is necessary for accurate PET quantification. Moreover, for thoracic PET imaging, respiration is known to lead to misalignments of MRAC and PET data that result in PET artifacts. These factors can be addressed by using multi-echo MR for tissue segmentation and motion-robust or motion-gated acquisitions. However, the combination of these strategies is not routinely available and can be prone to errors. In this study, we examine the qualitative and quantitative impacts of multi-class MRAC compared to a more widely available simple two-class MRAC for cardiac PET/MR.

Methods and Results

In a cohort of patients with cardiac sarcoidosis, we acquired MRAC data using multi-echo radial gradient-echo MR imaging. Water-fat separation was used to produce attenuation maps with up to 4 tissue classes including water-based soft tissue, fat, lung, and background air. Simultaneously acquired 18F-fluorodeoxyglucose PET data were subsequently reconstructed using each attenuation map separately. PET uptake values were measured in the myocardium and compared between different PET images. The inclusion of lung and subcutaneous fat in the MRAC maps significantly affected the quantification of 18F-fluorodeoxyglucose activity in the myocardium but only moderately altered the appearance of the PET image without introduction of image artifacts.

Conclusion

Optimal MRAC for cardiac PET/MR applications should include segmentation of all tissues in combination with compensation for the respiratory-related motion of the heart. Simple two-class MRAC is adequate for qualitative clinical assessment.

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Abbreviations

PET:

Positron emission tomography

MR:

Magnetic resonance

CT:

Computed tomography

MRAC:

Magnetic resonance attenuation correction

LAC:

Linear attenuation coefficient

18F-FDG:

18F-fluorodeoxyglucose

SUVmean/SUVmax:

Standard uptake value, mean SUV within a region, maximum SUV within a region

TBRmean/SUVmax:

Target-to-background ratio, mean TBR within a region, maximum TBR within a region

References

  1. Robson PM, Dey D, Newby DE, Berman D, Li D, Fayad ZA, et al. MR/PET imaging of the cardiovascular system. JACC Cardiovasc Imaging. 2017;10:1165-79.

    Article  Google Scholar 

  2. Schindler TH. Cardiovascular PET/MR imaging: Quo vadis? J Nucl Cardiol 2017;24:1007-18.

    Article  Google Scholar 

  3. Martinez-Möller A, Souvatzoglou M, Delso G, Bundschuh RA, Chefd’hotel C, Ziegler SI, et al. Tissue classification as a potential approach for attenuation correction in whole-body PET/MRI: Evaluation with PET/CT data. J Nucl Med 2009;50:520-6.

    Article  Google Scholar 

  4. Dixon WT. Simple proton spectroscopic imaging. Radiology 1984;153:189-94.

    Article  CAS  Google Scholar 

  5. Leynes AP, Yang J, Shanbhag DD, Kaushik SS, Seo Y, Hope TA, et al. Hybrid ZTE/Dixon MR-based attenuation correction for quantitative uptake estimation of pelvic lesions in PET/MRI. Med Phys 2017;44:902-13.

    Article  CAS  Google Scholar 

  6. Aasheim LB, Karlberg A, Goa PE, Håberg A, Sørhaug S, Fagerli U-M, et al. PET/MR brain imaging: Evaluation of clinical UTE-based attenuation correction. Eur J Nucl Med Mol Imaging 2015;42:1439-46.

    Article  Google Scholar 

  7. Hofmann M, Bezrukov I, Mantlik F, Aschoff P, Steinke F, Beyer T, et al. MRI-based attenuation correction for whole-body PET/MRI: Quantitative evaluation of segmentation- and atlas-based methods. J Nucl Med 2011;52:1392-9.

    Article  Google Scholar 

  8. Karakatsanis NA, et al. Hybrid PET- and MR-driven attenuation correction for enhanced 18F-NaF and 18F-FDG quantification in cardiovascular PET/MR imaging. J Nucl Cardiol 2019. https://doi.org/10.1007/s12350-019-01928-0.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Robson PM, Dweck MR, Trivieri MG, Abgral R, Karakatsanis NA, Contreras J, et al. Coronary artery PET/MR imaging: Feasibility, limitations, and solutions. JACC Cardiovasc Imaging 2017;10:1103-12.

    Article  Google Scholar 

  10. Lassen ML, Rasul S, Beitzke D, Stelzmüller M-E, Cal-Gonzalez J, Hacker M, et al. Assessment of attenuation correction for myocardial PET imaging using combined PET/MRI. J Nucl Cardiol 2017;26:1107-18.

    Article  Google Scholar 

  11. Kolbitsch C, Neji R, Fenchel M, Mallia A, Marsden P, Schaeffter T. Respiratory-resolved MR-based attenuation correction for motion-compensated cardiac PET-MR. Phys Med Biol 2018;63:135008.

    Article  Google Scholar 

  12. Ai H, Pan T. Feasibility of using respiration-averaged MR images for attenuation correction of cardiac PET/MR imaging. J Appl Clin Med Phys Am Coll Med Phys 2015;16:5194.

    Google Scholar 

  13. Ladefoged CN, Hansen AE, Keller SH, Holm S, Law I, Beyer T, et al. Impact of incorrect tissue classification in Dixon-based MR-AC: Fat-water tissue inversion. EJNMMI Phys 2014;1:101.

    Article  Google Scholar 

  14. Karakatsanis N, Robson P, Dweck M, Abgral R, Trivieri M, Sanz J, et al. MR-based attenuation correction in cardiovascular PET/MR imaging: Challenges and practical solutions for cardiorespiratory motion and tissue class segmentation. J Nucl Med 2016;57:452-3.

    Google Scholar 

  15. Benkert T, Feng L, Sodickson DK, Chandarana H, Block KT. Free-breathing volumetric fat/water separation by combining radial sampling, compressed sensing, and parallel imaging. Magn Reson Med 2017;78:565-76.

    Article  CAS  Google Scholar 

  16. Lau JMC, Laforest R, Sotoudeh H, Nie X, Sharma S, McConathy J, et al. Evaluation of attenuation correction in cardiac PET using PET/MR. J Nucl Cardiol 2017;24:839-46.

    Article  Google Scholar 

  17. Dweck MR, Abgral R, Trivieri MG, Robson PM, Karakatsanis N, Mani V, et al. Hybrid magnetic resonance imaging and positron emission tomography with fluorodeoxyglucose to diagnose active cardiac sarcoidosis. JACC Cardiovasc Imaging 2017;11:94-107.

    Article  Google Scholar 

  18. Kershah S, Partovi S, Traughber BJ, Muzic RF, Schluchter MD, O’Donnell JK, et al. Comparison of standardized uptake values in normal structures between PET/CT and PET/MRI in an oncology patient population. Mol Imaging Biol MIB 2013;15:776-85.

    Article  Google Scholar 

  19. Oldan JD, Shah SN, Brunken RC, DiFilippo FP, Obuchowski NA, Bolen MA. Do myocardial PET-MR and PET-CT FDG images provide comparable information? J Nucl Cardiol 2016;23:1102-9.

    Article  Google Scholar 

  20. Vontobel J, Liga R, Possner M, Clerc OF, Mikulicic F, Veit-Haibach P, et al. MR-based attenuation correction for cardiac FDG PET on a hybrid PET/MRI scanner: Comparison with standard CT attenuation correction. Eur J Nucl Med Mol Imaging 2015;42:1574-80.

    Article  Google Scholar 

  21. Nensa F, Poeppel TD, Beiderwellen K, Schelhorn J, Mahabadi AA, Erbel R, et al. Hybrid PET/MR imaging of the heart: Feasibility and initial results. Radiology 2013;268:366-73.

    Article  Google Scholar 

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Disclosure

The authors have no relevant conflicts of interest to disclose.

Author information

Authors and Affiliations

  1. Translational and Molecular Imaging Institute, Leon and Norma Hess Center for Science and Medicine, Icahn School of Medicine at Mount Sinai, One Gustave Levy Pl, 1470 Madison Ave, TMII – 1st floor, New York, NY, 10029, USA

    Philip M. Robson PhD, Vittoria Vergani MD, Maria Giovanna Trivieri MD, PhD, Nicolas A. Karakatsanis PhD & Zahi A. Fayad PhD

  2. Cardiothoracic and Vascular Department, Vita-Salute University and San Raffaele Hospital, Milan, Italy

    Vittoria Vergani MD

  3. Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University School of Medicine, New York, NY, USA

    Thomas Benkert PhD & Kai Tobias Block PhD

  4. Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA

    Thomas Benkert PhD & Kai Tobias Block PhD

  5. Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Pl, New York, NY, 10029, USA

    Maria Giovanna Trivieri MD, PhD, Pedro R. Moreno MD & Jason C. Kovacic MD, PhD

  6. Division of Radiopharmaceutical Sciences, Department of Radiology, Weill Cornell Medical College, Cornell University, New York, NY, USA

    Nicolas A. Karakatsanis PhD

  7. Department of Nuclear Medicine, University Hospital of Brest, European University of Brittany, EA3878 GETBO, Brest, France

    Ronan Abgral MD, PhD

  8. British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK

    Marc R. Dweck MD, PhD

Authors
  1. Philip M. Robson PhD
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  2. Vittoria Vergani MD
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  3. Thomas Benkert PhD
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  4. Maria Giovanna Trivieri MD, PhD
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  5. Nicolas A. Karakatsanis PhD
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  6. Ronan Abgral MD, PhD
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  7. Marc R. Dweck MD, PhD
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  8. Pedro R. Moreno MD
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  9. Jason C. Kovacic MD, PhD
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  10. Kai Tobias Block PhD
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  11. Zahi A. Fayad PhD
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Corresponding author

Correspondence to Philip M. Robson PhD.

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Funding

This work was supported by National Institutes of Health Grant R01 HL071021.

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Robson, P.M., Vergani, V., Benkert, T. et al. Assessing the qualitative and quantitative impacts of simple two-class vs multiple tissue-class MR-based attenuation correction for cardiac PET/MR. J. Nucl. Cardiol. 28, 2194–2204 (2021). https://doi.org/10.1007/s12350-019-02002-5

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  • DOI: https://doi.org/10.1007/s12350-019-02002-5

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