Details

Autor(en) / Beteiligte

• Vincent, Thomas
• Warnking, Jan
• Villien, Marjorie
• Krainik, Alexandre
• Ciuciu, Philippe
• Forbes, Florence
• Sakuma, Ichiro
• Barillot, Christian
• Sato, Yoshinobu
• Mori, Kensaku
• Navab, Nassir

Titel

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

Ist Teil von

• Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, 2013, Vol.16 (Pt 2), p.616-624

Ort / Verlag

Berlin, Heidelberg: Springer Berlin Heidelberg

Erscheinungsjahr

2013

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• 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.