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A comparison of CT- and MR-based attenuation correction in neurological PET

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

To assess the quantitative accuracy of current MR attenuation correction (AC) methods in neurological PET, in comparison to data derived using CT AC.

Methods

This retrospective study included 25 patients who were referred for a neurological FDG PET examination and were imaged sequentially by PET/CT and simultaneous PET/MR. Differences between activity concentrations derived using Dixon and ultrashort echo time (UTE) MR-based AC and those derived from CT AC were compared using volume of interest and voxel-based approaches. The same comparisons were also made using PET data represented as SUV ratios (SUVr) using grey matter cerebellum as the reference region.

Results

Extensive and statistically significant regional underestimations of activity concentrations were found with both Dixon AC (P < 0.001) and UTE AC (P < 0.001) in all brain regions when compared to CT AC. The greatest differences were found in the cortical grey matter (Dixon AC 21.3 %, UTE AC 15.7 %) and cerebellum (Dixon AC 19.8 %, UTE AC 17.3 %). The underestimation using UTE AC was significantly less than with Dixon AC (P < 0.001) in most regions. Voxel-based comparisons showed that all cortical grey matter and cerebellum uptake was underestimated with Dixon AC compared to CT AC. Using UTE AC the extent and significance of these differences were reduced. Inaccuracies in cerebellar activity concentrations led to a mixture of predominantly cortical underestimation and subcortical overestimation in SUVr PET data for both MR AC methodologies.

Conclusion

MR-based AC results in significant underestimation of activity concentrations throughout the brain, which makes the use of SUVr data difficult. These effects limit the quantitative accuracy of neurological PET/MR.

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References

  1. Catana C, Guimaraes AR, Rosen BR. PET and MR imaging: the odd couple or a match made in heaven? J Nucl Med. 2013;54:815–24.

    Article  CAS  PubMed  Google Scholar 

  2. Fass L. Imaging and cancer: a review. Mol Oncol. 2008;2:115–52.

    Article  PubMed  Google Scholar 

  3. Catana C, Benner T, van der Kouwe A, Byars L, Hamm M, Chonde DB, et al. MRI-assisted PET motion correction for neurologic studies in an integrated MR-PET scanner. J Nucl Med. 2011;52:154–61.

    Article  PubMed Central  PubMed  Google Scholar 

  4. Chun SY, Reese TG, Ouyang J, Guerin B, Catana C, Zhu X, et al. MRI-based nonrigid motion correction in simultaneous PET/MRI. J Nucl Med. 2012;53:1284–91.

    Article  PubMed  Google Scholar 

  5. Rousset OG, Ma Y, Evans AC. Correction for partial volume effects in PET: principle and validation. J Nucl Med. 1998;39:904–11.

    CAS  PubMed  Google Scholar 

  6. Thomas BA, Erlandsson K, Modat M, Thurfjell L, Vandenberghe R, Ourselin S, et al. The importance of appropriate partial volume correction for PET quantification in Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2011;38:1104–19.

    Article  PubMed  Google Scholar 

  7. Vunckx K, Atre A, Baete K, Reilhac A, Deroose CM, Van Laere K, et al. Evaluation of three MRI-based anatomical priors for quantitative PET brain imaging. IEEE Trans Med Imaging. 2012;31:599–612.

    Article  PubMed  Google Scholar 

  8. Yankeelov TE, Peterson TE, Abramson RG, Garcia-Izquierdo D, Arlinghaus LR, Li X, et al. Simultaneous PET-MRI in oncology: a solution looking for a problem? Magn Reson Imaging. 2012;30:1342–56.

    Article  PubMed Central  PubMed  Google Scholar 

  9. Kinahan PE, Townsend DW, Beyer T, Sashin D. Attenuation correction for a combined 3D PET/CT scanner. Med Phys. 1998;25:2046–53.

    Article  CAS  PubMed  Google Scholar 

  10. Hofmann M, Pichler B, Schölkopf B, Beyer T. Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques. Eur J Nucl Med Mol Imaging. 2009;36 Suppl 1:S93–S104.

    Article  PubMed  Google Scholar 

  11. Coombs BD, Szumowski J, Coshow W. Two-point Dixon technique for water-fat signal decomposition with B0 inhomogeneity correction. Magn Reson Med. 1997;38:884–9.

    Article  CAS  PubMed  Google Scholar 

  12. 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  PubMed  Google Scholar 

  13. Samarin A, Burger C, Wollenweber SD, Crook DW, Burger IA, Schmid DT, et al. PET/MR imaging of bone lesions – implications for PET quantification from imperfect attenuation correction. Eur J Nucl Med Mol Imaging. 2012;39:1154–60.

    Article  PubMed  Google Scholar 

  14. Wagenknecht G, Kaiser H-J, Mottaghy FM, Herzog H. MRI for attenuation correction in PET: methods and challenges. MAGMA. 2013;26:99–113.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Keereman V, Fierens Y, Broux T, De Deene Y, Lonneux M, Vandenberghe S. MRI-based attenuation correction for PET/MRI using ultrashort echo time sequences. J Nucl Med. 2010;51:812–8.

    Article  PubMed  Google Scholar 

  16. Camus V, Payoux P, Barré L, Desgranges B, Voisin T, Tauber C, et al. Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment. Eur J Nucl Med Mol Imaging. 2012;39:621–31.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Ashburner J, Friston KJ. Nonlinear spatial normalization using basis functions. Hum Brain Mapp. 1999;7:254–66.

    Article  CAS  PubMed  Google Scholar 

  18. Brett M, Anton J-L, Valabregue R, Poline J-B. Region of interest analysis using the MarsBar toolbox for SPM 99. Sendai, Japan; 2002.

  19. Berker Y, Franke J, Salomon A, Palmowski M, Donker HCW, Temur Y, et al. MRI-based attenuation correction for hybrid PET/MRI systems: a 4-class tissue segmentation technique using a combined ultrashort-echo-time/Dixon MRI sequence. J Nucl Med. 2012;53:796–804.

    Article  PubMed  Google Scholar 

  20. Andersen FL, Ladefoged CN, Beyer T, Keller SH, Hansen AE, Højgaard L, et al. Combined PET/MR imaging in neurology: MR-based attenuation correction implies a strong spatial bias when ignoring bone. Neuroimage. 2013;84C:206–16.

    Google Scholar 

  21. Catana C, van der Kouwe A, Benner T, Michel CJ, Hamm M, Fenchel M, et al. Toward implementing an MRI-based PET attenuation-correction method for neurologic studies on the MR-PET brain prototype. J Nucl Med. 2010;51:1431–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998;17:87–97.

    Article  CAS  PubMed  Google Scholar 

  23. Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med. 1995;36:1238–48.

    CAS  PubMed  Google Scholar 

  24. Schulz V, Torres-Espallardo I, Renisch S, Hu Z, Ojha N, Börnert P, et al. Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data. Eur J Nucl Med Mol Imaging. 2011;38:138–52.

    Article  CAS  PubMed  Google Scholar 

  25. Marshall HR, Prato FS, Deans L, Théberge J, Thompson RT, Stodilka RZ. Variable lung density consideration in attenuation correction of whole-body PET/MRI. J Nucl Med. 2012;53:977–84.

    Article  PubMed  Google Scholar 

  26. Schleyer PJ, Schaeffter T, Marsden PK. The effect of inaccurate bone attenuation coefficient and segmentation on reconstructed PET images. Nucl Med Commun. 2010;31:708–16.

    Article  PubMed  Google Scholar 

  27. Nakamoto Y, Osman M, Cohade C, Marshall LT, Links JM, Kohlmyer S, et al. PET/CT: comparison of quantitative tracer uptake between germanium and CT transmission attenuation-corrected images. J Nucl Med. 2002;43:1137–43.

    PubMed  Google Scholar 

  28. Keat N, Hallett W, Howard J, Searle G. Assessment of quantitative PET image accuracy and uniformity using geometric and realistic brain phantoms. J Nucl Med. 2012;53 Suppl 1:2280.

    Google Scholar 

  29. Burger C, Goerres G, Schoenes S, Buck A, Lonn AHR, Von Schulthess GK. PET attenuation coefficients from CT images: experimental evaluation of the transformation of CT into PET 511-keV attenuation coefficients. Eur J Nucl Med Mol Imaging. 2002;29:922–7.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgments

This study was supported by the National Institute for Health Research, University College London Hospitals Biomedical Research Centre.

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Authors and Affiliations

  1. Institute of Nuclear Medicine, University College London Hospitals, Euston Road, London, NW1 2BU, UK

    John C. Dickson, Celia O’Meara & Anna Barnes

Authors
  1. John C. Dickson
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  2. Celia O’Meara
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  3. Anna Barnes
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Correspondence to John C. Dickson.

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Dickson, J.C., O’Meara, C. & Barnes, A. A comparison of CT- and MR-based attenuation correction in neurological PET. Eur J Nucl Med Mol Imaging 41, 1176–1189 (2014). https://doi.org/10.1007/s00259-013-2652-z

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  • DOI: https://doi.org/10.1007/s00259-013-2652-z

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