SpringerLink
Log in

Direct prospective comparison of 18F-FDG PET and arterial spin labelling MR using simultaneous PET/MR in patients referred for diagnosis of dementia

  • Original Article
  • Published:
European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

Abstract

Purpose

18F-FDG PET is routinely used as an imaging marker in the early and differential diagnosis of dementing disorders and has incremental value over the clinical neurological and neuropsychological evaluation. Perfusion MR imaging by means of arterial spin labelling (ASL) is an alternative modality to indirectly measure neuronal functioning and could be used as complement measurement in a single MR session in the workup of dementia. Using simultaneous PET-MR, we performed a direct head-to-head comparison between enhanced multiplane tagging ASL (eASL) and 18F-FDG PET in a true clinical context of subjects referred for suspicion of neurodegenerative dementia.

Methods

Twenty-seven patients underwent a 20-min 18F-FDG PET/MR and simultaneously acquired eASL on a GE Signa PET/MR. Data were compared with 30 screened age- and gender-matched healthy controls. Both integral eASL and 18F-FDG datasets were analysed visually by two readers unaware of the final clinical diagnosis, either in normal/abnormal classes, or full differential diagnosis (normal, Alzheimer type dementia [AD], dementia with Lewy Bodies [LBD], frontotemporal dementia [FTD] or other). Reader confidence was assessed with a rating scale (range 1–4). Data were also analysed semiquantitatively by VOI and voxel-based analyses.

Results

The ground truth diagnosis for the patient group resulted in 14 patients with a neurodegenerative cognitive disorder (AD, FTD, LBD) and 13 patients with no arguments for an underlying neurodegenerative cause. Visual analysis resulted in equal specificity (0.70) for differentiating normal and abnormal cases between the two modalities, but in a higher sensitivity (0.93), confidence rating (0.64) and interobserver agreement for 18F-FDG PET compared with eASL. The same was true for assigning a specific differential diagnosis (sensitivity: and 0.39 for 18F-FDG PET and eASL, respectively). Semiquantitative analyses revealed prototypical patterns for AD and FTD, with both higher volumes of abnormality and intensity differences on 18F-FDG PET.

Conclusion

In a direct head-to-head comparison on a simultaneous GE Signa PET/MR, 18F-FDG PET performed better compared with ASL in terms of sensitivity and reader confidence, as well as volume and intensity of abnormalities. However, using pure semiquantitative analysis, similar diagnostic accuracy between the two modalities was obtained. Therefore, ASL may still serve as complement to neuroreceptor or protein deposition PET studies when a single simultaneous investigation is warranted.

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
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Drew L. An age-old story of dementia. Nature. 2018;559:S2–3.

    Article  CAS  Google Scholar 

  2. Prince M, Bryce R, Albanese E, Wimo A, Ribeiro W, Ferri CP. The global prevalence of dementia: a systematic review and metaanalysis. Alzheimer’s Dement. 2013;9:63–75.e2.

    Article  Google Scholar 

  3. Shivamurthy VK, Tahari AK, Marcus C, Subramaniam RM, Vkn S. Brain FDG PET and the diagnosis of dementia.

  4. Amy Orciari Herman PFW. For patients with cognitive impairment, amyloid PET leads to changes in clinical management. NEJM J Watch. 2019;2019.

  5. Villemagne VL, Doré V, Bourgeat P, Burnham SC, Laws S, Salvado O, et al. Aβ-amyloid and tau imaging in dementia. Semin Nucl Med. 2017;47:75–88.

    Article  Google Scholar 

  6. Okamura N, Harada R, Furumoto S, Tago T, Yanai K, Arai H, et al. Advances in the development of tau PET radiotracers and their clinical applications. Ageing Res Rev. 2016;30:107–13.

    Article  CAS  Google Scholar 

  7. Mallik A, Drzezga A, Minoshima S. Clinical amyloid imaging. Semin Nucl Med. 2017;47:31–43.

    Article  Google Scholar 

  8. Morbelli S, Garibotto V, Van De Giessen E, Arbizu J, Chételat G, Drezgza A, et al. A Cochrane review on brain [18F]FDG PET in dementia: limitations and future perspectives. Eur J Nucl Med Mol Imaging. 2015;42:1487–91.

    Article  Google Scholar 

  9. Garibotto V, Herholz K, Boccardi M, Picco A, Varrone A, Nordberg A, et al. Clinical validity of brain fluorodeoxyglucose positron emission tomography as a biomarker for Alzheimer’s disease in the context of a structured 5-phase development framework. Neurobiol Aging. 2017;52:183–95.

    Article  CAS  Google Scholar 

  10. Foster NL, Heidebrink JL, Clark CM, Jagust WJ, Arnold SE, Barbas NR, et al. FDG-PET improves accuracy in distinguishing frontotemporal dementia and Alzheimer’s disease. Brain. 2007;130:2616–35.

    Article  Google Scholar 

  11. Tosun D, Schuff N, Rabinovici GD, Ayakta N, Miller BL, Jagust W, et al. Diagnostic utility of ASL-MRI and FDG-PET in the behavioral variant of FTD and AD. Ann Clin Transl Neurol. 2016;3:740–51.

    Article  CAS  Google Scholar 

  12. Jueptner M, Weiller C. Review: does measurement of regional cerebral blood flow reflect synaptic activity? Implications for PET and fMRI. Neuroimage. 1995;2:148–56.

    Article  CAS  Google Scholar 

  13. Du AT, Jahng GH, Hayasaka S, Kramer JH, Rosen HJ, Gorno-Tempini ML, et al. Hypoperfusion in frontotemporal dementia and Alzheimer disease by arterial spin labeling MRI. Neurology. 2006;67:1215–20.

    Article  CAS  Google Scholar 

  14. Raji CA, Lee C, Lopez OL, Tsay J, Boardman JF, Schwartz ED, et al. Initial experience in using continuous arterial spin-labeled MR imaging for early detection of Alzheimer disease. AJNR Am J Neuroradiol. 2010;31:847–55.

    Article  CAS  Google Scholar 

  15. Kaneta T, Katsuse O, Hirano T, Ogawa M, Shihikura-Hino A, Yoshida K, et al. Voxel-wise correlations between cognition and cerebral blood flow using arterial spin-labeled perfusion MRI in patients with Alzheimer’s disease: a cross-sectional study. BMC Neurol. 2017;17:91.

    Article  Google Scholar 

  16. Liu P, Uh J, Devous MD, Adinoff B, Lu H. Comparison of relative cerebral blood flow maps using pseudo-continuous arterial spin labeling and single photon emission computed tomography. NMR Biomed. 2012;25:779–86.

    Article  Google Scholar 

  17. Fällmar D, Haller S, Lilja J, Danfors T, Kilander L, Tolboom N, et al. Arterial spin labeling-based Z-maps have high specificity and positive predictive value for neurodegenerative dementia compared to FDG-PET. Eur Radiol. 2017;27:4237–46.

    Article  Google Scholar 

  18. Verfaillie SCJ, Adriaanse SM, Binnewijzend MAA, Benedictus MR, Ossenkoppele R, Wattjes MP, et al. Cerebral perfusion and glucose metabolism in Alzheimer’s disease and frontotemporal dementia: two sides of the same coin? Eur Radiol. 2015;25:3050–9.

    Article  Google Scholar 

  19. Anazodo UC, Finger E, Kwan BYM, Pavlosky W, Warrington JC, Günther M, et al. Using simultaneous PET/MRI to compare the accuracy of diagnosing frontotemporal dementia by arterial spin labelling MRI and FDG-PET. Neuro Image Clin. 2018;17:405–14.

    Google Scholar 

  20. Riederer I, Bohn KP, Preibisch C, Wiedemann E, Zimmer C, Alexopoulos P, et al. Alzheimer disease and mild cognitive impairment: integrated pulsed arterial spin-labeling MRI and 18 F-FDG PET. Radiology. 2018;288:198–206.

    Article  Google Scholar 

  21. Weyts K, Vernooij M, Steketee R, Valkema R, Smits M. Qualitative agreement and diagnostic performance of arterial spin labelling MRI and FDG PET-CT in suspected early-stage dementia: comparison of arterial spin labelling MRI and FDG PET-CT in suspected dementia. Clin Imaging. 2017;45:1–7.

    Article  Google Scholar 

  22. Musiek ES, Chen Y, Korczykowski M, Saboury B, Martinez PM, Reddin JS, et al. Direct comparison of FDG-PET and ASL-MRI in Alzheimer’s disease. Alzheimers Dement. 2012;8:51–9.

    Article  Google Scholar 

  23. Douglas D, Goubran M, Wilson E, Xu G, Tripathi P, Holley D, et al. Correlation between arterial spin labeling MRI and dynamic FDG on PET-MR in Alzheimer’s disease and non-Alzhiemer’s disease patients. EJNMMI Phys. 2015;2:A83.

    Article  Google Scholar 

  24. Hammers A, Allom R, Koepp MJ, Free SL, Myers R, Lemieux L, et al. Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe. Hum Brain Mapp. 2003;19:224–47.

    Article  Google Scholar 

  25. Bohnen NI, Djang DSW, Herholz K, Anzai Y, Minoshima S. Effectiveness and safety of 18F-FDG PET in the evaluation of dementia: a review of the recent literature. J Nucl Med. 2012;53:59–71.

    Article  CAS  Google Scholar 

  26. Deibler AR, Pollock JM, Kraft RA, Tan H, Burdette JH, Maldjian JA. Arterial spin-labeling in routine clinical practice, part 1: technique and artifacts. AJNR Am J Neuroradiol. 2008;29:1228–34.

    Article  CAS  Google Scholar 

  27. Grade M, Hernandez Tamames JA, Pizzini FB, Achten E, Golay X, Smits M. A neuroradiologist’s guide to arterial spin labeling MRI in clinical practice. Neuroradiology. 2015;57:1181–202.

    Article  CAS  Google Scholar 

  28. Yoshiura T, Hiwatashi A, Yamashita K, Ohyagi Y, Monji A, Takayama Y, et al. Simultaneous measurement of arterial transit time, arterial blood volume, and cerebral blood flow using arterial spin-labeling in patients with Alzheimer disease. Am J Neuroradiol. 2009;30:1388–93.

    Article  CAS  Google Scholar 

  29. Tang X, Cai F, Ding D-X, Zhang L-L, Cai X-Y, Fang Q. Magnetic resonance imaging relaxation time in Alzheimer’s disease. Brain Res Bull. 2018;140:176–89.

    Article  Google Scholar 

  30. Chen Y, Wolk DA, Reddin JS, Korczykowski M, Martinez PM, Musiek ES, et al. Voxel-level comparison of arterial spin-labeled perfusion MRI and FDG-PET in Alzheimer disease. Neurology. 2011;77:1977–85.

    Article  CAS  Google Scholar 

  31. Drzezga A, Lautenschlager N, Siebner H, Riemenschneider M, Willoch F, Minoshima S, et al. Cerebral metabolic changes accompanying conversion of mild cognitive impairment into Alzheimer’s disease: a PET follow-up study. Eur J Nucl Med Mol Imaging. 2003;30:1104–13.

    Article  Google Scholar 

  32. Fällmar D, Lilja J, Velickaite V, Danfors T, Lubberink M, Ahlgren A, et al. Visual assessment of brain perfusion MRI scans in dementia: a pilot study. J Neuroimaging. 2016;26:324–30.

    Article  Google Scholar 

  33. Verclytte S, Lopes R, Lenfant P, Rollin A, Semah F, Leclerc X, et al. Cerebral hypoperfusion and hypometabolism detected by arterial spin labeling MRI and FDG-PET in early-onset Alzheimer’s disease. J Neuroimaging. 2016;26:207–12.

    Article  Google Scholar 

  34. Teune LK, Renken Phd RJ, De Jong BM, Willemsen AT, Van Osch MJ, Roerdink JBTM, et al. Parkinson’s disease-related perfusion and glucose metabolic brain patterns identified with PCASL-MRI and FDG-PET imaging. 2014;

  35. Rabinovici GD, Gatsonis C, Apgar C, Chaudhary K, Gareen I, Hanna L, et al. Association of amyloid positron emission tomography with subsequent change in clinical management among Medicare beneficiaries with mild cognitive impairment or dementia. JAMA. 2019;321:1286.

    Article  Google Scholar 

  36. Henriksen OM, Larsson HBW, Hansen AE, Grüner JM, Law I, Rostrup E. Estimation of intersubject variability of cerebral blood flow measurements using MRI and positron emission tomography. J Magn Reson Imaging. 2012;35:1290–9.

    Article  Google Scholar 

  37. Schramm G, Koole M, Willekens SMA, Rezaei A, Van Weehaeghe D, Delso G, et al. Regional accuracy of ZTE-based attenuation correction in static and dynamic brain PET/MR. ‎Med Phys. 2018.

  38. Ferreira LK, Diniz BS, Forlenza OV, Busatto GF, Zanetti MV. Neurostructural predictors of Alzheimer’s disease: a meta-analysis of VBM studies. Neurobiol Aging. 2011;32:1733–41.

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank all the participants for their willingness to participate in this study, the PET radiopharmacy, research technologists (Kwinten Porters and Jef Van Loock) and radiology team of UZ Leuven for their skilled support. Jenny Ceccarini and Donatienne Van Weehaeghe are postdoctoral and Ph.D. fellows of the Research Foundation Flanders (FWO), respectively. Rik Vandenberghe, Mathieu Vandenbulcke and Koen Van Laere are Senior Clinical Investigators of the FWO.

Funding

Jenny Ceccarini and Donatienne Van Weehaeghe are postdoctoral and Ph.D. fellows of the Research Foundation Flanders (FWO), respectively. Rik Vandenberghe and Koen Van Laere are Senior Clinical Investigators of the FWO.

Author information

Authors and Affiliations

  1. Department of Imaging and Pathology, University Hospitals Leuven and KU Leuven, Herestraat 49, 3000, Leuven, Belgium

    Jenny Ceccarini, Donatienne Van Weehaeghe, Karolien Goffin, Stefan Sunaert & Koen Van Laere

  2. Division of Nuclear Medicine, University Hospitals Leuven, Leuven, Belgium

    Sophie Bourgeois, Donatienne Van Weehaeghe, Karolien Goffin & Koen Van Laere

  3. Department of Neurology, University Hospitals Leuven, Leuven, Belgium

    Rik Vandenberghe

  4. Old Age Psychiatry, University Hospitals Leuven, Leuven, Belgium

    Mathieu Vandenbulcke

  5. Department of Radiology, University Hospitals Leuven, Leuven, Belgium

    Stefan Sunaert

Authors
  1. Jenny Ceccarini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sophie Bourgeois
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Donatienne Van Weehaeghe
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Karolien Goffin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rik Vandenberghe
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Mathieu Vandenbulcke
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Stefan Sunaert
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Koen Van Laere
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jenny Ceccarini.

Ethics declarations

Conflict of interest

The 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 and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

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

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Jenny Ceccarini and Sophie Bourgeois are shared first authors.

This article is part of the Topical Collection on Neurology

Electronic supplementary material

ESM 1

(DOCX 464 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ceccarini, J., Bourgeois, S., Van Weehaeghe, D. et al. Direct prospective comparison of 18F-FDG PET and arterial spin labelling MR using simultaneous PET/MR in patients referred for diagnosis of dementia. Eur J Nucl Med Mol Imaging 47, 2142–2154 (2020). https://doi.org/10.1007/s00259-020-04694-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00259-020-04694-1

Keywords

Search

Navigation