Assessment of functional development in normal infant brain using arterial spin labeled perfusion MRI
- PMID: 17988892
- PMCID: PMC2268607
- DOI: 10.1016/j.neuroimage.2007.09.045
Assessment of functional development in normal infant brain using arterial spin labeled perfusion MRI
Abstract
Arterial spin labeled (ASL) perfusion MRI provides a noninvasive approach for longitudinal imaging of regional brain function in infants. In the present study, continuous ASL (CASL) perfusion MRI was carried out in normally developing 7- and 13-month-old infants while asleep without sedation. The 13-month infant group showed an increase (P<0.05) of relative CBF in frontal regions as compared to the 7-month group using a region of interest based analysis. Using a machine-learning algorithm to automatically classify the relative CBF maps of the two infant groups, a significant (P<0.05, permutation testing) regional CBF increase was found in the hippocampi, anterior cingulate, amygdalae, occipital lobes, and auditory cortex in the 13-month-old infants. These results are consistent with current understanding of infant brain development and demonstrate the feasibility of using perfusion MRI to noninvasively monitor developing brain function.
Figures
References
-
- Alsop DC, Detre JA. Multisection Cerebral Blood Flow MR Imaging with Continuous Arterial Spin Labeling. Radiology. 1998;208:410–416. - PubMed
-
- Alsop DC, Detre JA, Grossman M. Assessment of cerebral blood flow in Alzheimer's disease by spin-labeled magnetic resonance imaging. Annals of neurology. 2000;47:93–100. - PubMed
-
- Biagi L, Abbruzzese A, Bianchi MC, Alsop DC, Guerra AD, Tosetti M. Age dependence of cerebral perfusion assessed by magnetic resonance continuous arterial spin labeling. J Magn Reson Imaging. 2007;25(4):696–702. - PubMed
-
- Biswal BB, Ulmer JL. Blind source separation of multiple signal sources of fMRI data sets using independent component analysis. Journal of Computer Assisted Tomography. 1999;23:265–271. - PubMed
-
- Burges CJC. A Tutorial on Support Vector Machines for Pattern Recognition. Data Mining and Knowledge Discovery. 1998;2:121–167.
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources
