Advertisement

Bayesian Joint Detection-Estimation of Cerebral Vasoreactivity from ASL fMRI Data

  • Thomas Vincent
  • Jan Warnking
  • Marjorie Villien
  • Alexandre Krainik
  • Philippe Ciuciu
  • Florence Forbes
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)

Abstract

Although the study of cerebral vasoreactivity using fMRI is mainly conducted through the BOLD fMRI modality, owing to its relatively high signal-to-noise ratio (SNR), ASL fMRI provides a more interpretable measure of cerebral vasoreactivity than BOLD fMRI. Still, ASL suffers from a low SNR and is hampered by a large amount of physiological noise. The current contribution aims at improving the recovery of the vasoreactive component from the ASL signal. To this end, a Bayesian hierarchical model is proposed, enabling the recovery of perfusion levels as well as fitting their dynamics. On a single-subject ASL real data set involving perfusion changes induced by hypercapnia, the approach is compared with a classical GLM-based analysis. A better goodness-of-fit is achieved, especially in the transitions between baseline and hypercapnia periods. Also, perfusion levels are recovered with higher sensitivity and show a better contrast between gray- and white matter.

Keywords

fMRI ASL cerebral vasoreactivity deconvolution Bayesian analysis Monte Carlo Markov Chain inference 

References

  1. 1.
    Krainik, A., Hund-Georgiadis, M., Zysset, S., von Cramon, D.Y.: Regional impairment of cerebrovascular reactivity and BOLD signal in adults after stroke. Stroke 36(6), 1146–1152 (2005)CrossRefGoogle Scholar
  2. 2.
    Cantin, S., Villien, M., Moreaud, O., Tropres, I., Keignart, S., Chipon, E., Le Bas, J.F., Warnking, J., Krainik, A.: Impaired cerebral vasoreactivity to CO2 in Alzheimer’s disease using BOLD fMRI. Neuroimage 58(2), 579–587 (2011)CrossRefGoogle Scholar
  3. 3.
    Attyé, A., Villien, M., Tahon, F., Warnking, J., Detante, O., Krainik, A.: Normalization of cerebral vasoreactivity using BOLD MRI after intravascular stenting. Hum. Brain Mapp. (2013)Google Scholar
  4. 4.
    Villien, M., Bouzat, P., Rupp, T., Robach, P., Lamalle, L., Troprès, I., Estève, F., Krainik, A., Lévy, P., Warnking, J., Verges, S.: Changes in cerebral blood flow and vasoreactivity to CO(2) measured by Arterial Spin Labeling after 6 days at 4,350 m. Neuroimage (2013)Google Scholar
  5. 5.
    Liu, T.T., Brown, G.: Measurement of cerebral perfusion with arterial spin labeling: Part 1. methods. Journal of the International Neuropsychological Society 13, 517–525 (2007)CrossRefGoogle Scholar
  6. 6.
    Hernandez-Garcia, L., Jahanian, H., Rowe, D.B.: Quantitative analysis of arterial spin labeling FMRI data using a general linear model. Magnetic Resonance Imaging 28(7), 919–927 (2010)CrossRefGoogle Scholar
  7. 7.
    Roc, A., Wang, J., Ances, B., Liebeskind, D., Kasner, S., Detre, J.: Altered hemodynamics and regional cerebral blood flow in patients with hemodynamically significant stenoses. Stroke 37(2), 382–387 (2006)CrossRefGoogle Scholar
  8. 8.
    Woolrich, M., Chiarelli, P., Gallichan, D., Perthen, J., Liu, T.: Bayesian inference of hemodynamic changes in functional arterial spin labeling data. Magn. Reson. Med. 56(4), 891–906 (2006)CrossRefGoogle Scholar
  9. 9.
    Vincent, T., Risser, L., Ciuciu, P.: Spatially adaptive mixture modeling for analysis of within-subject fMRI time series. IEEE Trans. Med. Imag. 29(4), 1059–1074 (2010)CrossRefGoogle Scholar
  10. 10.
    Thirion, B., Flandin, G., Pinel, P., Roche, A., Ciuciu, P., Poline, P.: Dealing with the shortcomings of spatial normalization: Multi-subject parcellation of fMRI datasets. Hum. Brain Mapp. 27(8), 678–693 (2006)CrossRefGoogle Scholar
  11. 11.
    Dai, W., Garcia, D., de Bazelaire, C., Alsop, D.C.: Continuous flow-driven inversion for arterial spin labeling using pulsed radio frequency and gradient fields. Magn. Reson. Med. 60(6), 1488–1497 (2008)CrossRefGoogle Scholar
  12. 12.
    Vincent, T., Ciuciu, P., Thirion, B.: Sensitivity analysis of parcellation in the joint detection-estimation of brain activity in fMRI. In: 5th Proc. IEEE ISBI, Paris, France, pp. 568–571 (May 2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas Vincent
    • 1
  • Jan Warnking
    • 2
  • Marjorie Villien
    • 2
  • Alexandre Krainik
    • 2
  • Philippe Ciuciu
    • 3
  • Florence Forbes
    • 1
  1. 1.INRIA, MISTISGrenoble University, LJKGrenobleFrance
  2. 2.INSERM U836-UJF-CEA-CHU (GIN)GrenobleFrance
  3. 3.CEA/DSV/I2BM NeuroSpin centerGif-sur-YvetteFrance

Personalised recommendations