Proceedings Article | 16 March 2011
KEYWORDS: Stem cells, Brain, Statistical analysis, Therapeutics, In vivo imaging, Injuries, Detection and tracking algorithms, Neurons, Regenerative medicine, Magnetic resonance imaging
Hypoxic-Ischemic Encephalopathy (HIE) is the brain manifestation of systemic asphyxia that occurs in 20 out
of 1000 births. HIE triggers an immediate neuronal and glial injury leading to necrosis secondary to cellular edema and
lysis. Because of this destructive neuronal injury, up to 25% of neonates exhibit severe permanent neuropsychological
handicaps in the form of cerebral palsy, with or without associated mental retardation, learning disabilities, or epilepsy.
Due to the devastating consequences of HIE, much research has focused on interrupting the cascade of events triggered
by HIE. To date, none of these therapies, with the exception of hypothermia, have been successful in the clinical
environment. Even in the case of hypothermia, only neonates with mild to moderate HIE respond to therapy. Stem cell
therapy offers an attractive potential treatment for HIE. The ability to replace necrotic cells with functional cells could
limit the degree of long-term neurological deficits. The neonatal brain offers a unique milieu for stem cell therapy due to
its overall plasticity and the continued division of cells in the sub-ventricular zones.
New powerful imaging tools allow researchers to track stem cells in vivo post-transplant, as shown in Figure 1.
However, neuroimaging still leaves numerous questions unresolved: How can we identify stem cells without using
tracking agents, what cells types are destroyed in the brain post injury? What is the final phenotypic fate of transplanted
cells? Are the transplanted cells still viable? Do the transplanted cells spare endogenous neuronal tissue? We
hypothesize that magnetic resonance spectroscopy (MRS), a broadly used clinical technique that can be performed at the
time of a standard MRI scan, can provide answers to these questions when coupled with advanced computational
approaches. MRS is widely available clinically, and is a relative measure of different metabolites within the sampled
area. These measures are presented as a series of peaks at a particular bandwidth that corresponds to an individual
metabolite, such as lactate or creatine, as shown in Figure 2. Currently, the data are only subjectively interpreted by a
neuro-radiologist, but hold great potential if they were analyzed in a more objective manner.
The overall purpose of the research described here is to develop pattern recognition algorithms for MRS data as
a means to detect novel biomarkers or fingerprints of stem cells. Once identified, this technique will be used to identify
in vivo transplanted stem cells within the brain.
