No abstract

Stroke is a major global health problem, with the prevalence and economic burden predicted to increase due to aging populations in western society. Following stroke, numerous biochemical alterations occur and damage can spread to nearby tissue. This zone of "at risk" tissue is termed the peri-infarct zone (PIZ). As the PIZ contains tissue not initially damaged by the stroke, it is considered by many as salvageable tissue. For this reason, much research effort has been undertaken to improve the identification of the PIZ and to elucidate the biochemical mechanisms that drive tissue damage in the PIZ in the hope of identify new therapeutic targets. Despite this effort, few therapies have evolved, attributed in part, to an incomplete understanding of the biochemical mechanisms driving tissue damage in the PIZ. Magnetic resonance imaging (MRI) has long been the gold standard to study alterations in gross brain structure, and is frequently used to study the PIZ following stroke. Unfortunately, MRI does not have sufficient spatial resolution to study individual cells within the brain, and reveals little information on the biochemical mechanisms driving tissue damage. MRI results may be complemented with histology or immuno-histochemistry to provide information at the cellular or sub-cellular level, but are limited to studying biochemical markers that can be successfully "tagged" with a stain or antigen. However, many important biochemical markers cannot be studied with traditional MRI or histology/histochemical methods. Therefore, we have developed and applied a multi-modal imaging platform to reveal elemental and molecular alterations that could not previously be imaged by other traditional methods. Our imaging platform incorporates a suite of spectroscopic imaging techniques; Fourier transform infrared imaging, Raman spectroscopic imaging, Coherent anti-stoke Raman spectroscopic imaging and X-ray fluorescence imaging. This approach does not preclude the use of traditional imaging techniques, and rather it should be use to complement traditional methods such as MRI or histology and immunohistochemistry, to gain a greater insight into disease mechanisms. We demonstrate the potential of this approach by characterizing biochemical alterations within the PIZ 24h after the induction of photothrombotic stroke in mice. Substantial molecular and elemental alterations were identified in the PIZ 24h after stroke that are consistent with tissue swelling and edema, but not oxidative stress. This reveals important mechanistic information, that could not previously be obtained, which should be considered in future studies aimed at developing therapeutic intervention from this model.

Imaging energy metabolites as markers of the energy shuttle between glia and neurons following ischemia is an ongoing challenge. Traditional microscopies in combination with histochemistry reveal glycogen accumulation within glia following ischemia, indicating an altered metabolic profile. Although semiquantitative histochemical glycogen analysis is possible, the method suffers from typical confounding factors common to histochemistry, such as variation in reagent penetration and binding. In addition, histochemical detection of glycogen does not reveal information on the metabolic fate of glycogen (i.e., lactate production). Therefore, validation of a direct semiquantitative method to simultaneously image both brain glycogen and lactate in the same tissue section would benefit this research field. In this study, we demonstrate the first application of Fourier transform infrared (FTIR) spectroscopy for simultaneous direct spectroscopic imaging of brain glycogen and lactate, in situ within ex vivo tissue sections. Serial tissue sections were analyzed with anti-glial fibrillary acidic protein (GFAP) immunohistochemistry to provide a comparison between the glycogen and lactate distribution revealed by FTIR and the glial distribution revealed by GFAP immunohistochemistry. The distribution of glycogen revealed by FTIR spectroscopic imaging has been further compared with histochemical detection of glycogen on the adjacent tissue sections. This approach was then applied to study spatiotemporal disturbances in metabolism, relative to glia and neuronal populations, following cerebral ischemia in a murine model of stroke.

Stroke exacts a heavy financial and economic burden, is a leading cause of death, and is the leading cause of long-term disability in those who survive. The penumbra surrounds the ischemic core of the stroke lesion and is composed of cells that are stressed and vulnerable to death, which is due to an altered metabolic, oxidative, and ionic environment within the penumbra. Without therapeutic intervention, many cells within the penumbra will die and become part of the growing infarct, however, there is hope that appropriate therapies may allow potential recovery of cells within this tissue region, or at least slow the rate of cell death, therefore, slowing the spread of the ischemic infarct and minimizing the extent of tissue damage. As such, preserving the penumbra to promote functional brain recovery is a central goal in stroke research. While identification of the ischemic infarct, and the infarct/penumbra boundary is relatively trivial using classical histology and microscopy techniques, accurately assessing the penetration of the penumbra zone into undamaged brain tissue, and evaluating the magnitude of chemical alterations in the penumbra, has long been a major challenge to the stroke research field. In this study, we have used synchrotron-based X-ray fluorescence imaging to visualize the elemental changes in undamaged, penumbra, and infarct brain tissue, following ischemic stroke. We have employed a Gaussian mixture model to cluster tissue areas based on their elemental characteristics. The method separates the core of the infarct from healthy tissue, and also demarcates discrete regions encircling the infarct. These regions of interest can be combined with elemental and metabolic data, as well as with conventional histology. The cell populations defined by clustering provide a reproducible means of visualizing the size and extent of the penumbra at the level of the single cell and provide a critically needed tool to track changes in elemental status and penumbra size.