Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6028869 | NeuroImage | 2014 | 17 Pages |
Abstract
Diffuse optical tomography (DOT) has been used by several groups to assess cerebral hemodynamics of cerebral ischemia in humans and animals. In this study, we combined DOT with an indocyanine green (ICG)-tracking method to achieve interleaved images of cerebral hemodynamics and blood flow index (BFI) using two middle cerebral artery occlusion (MCAO) rat models. To achieve volumetric images with high-spatial resolution, we first integrated a depth compensation algorithm (DCA) with a volumetric mesh-based rat head model to generate three-dimensional (3D) DOT on a rat brain atlas. Then, the experimental DOT data from two rat models were collected using interleaved strategy for cerebral hemodynamics and BFI during and after ischemic stroke, with and without a thrombolytic therapy for the embolic MCAO model. The acquired animal data were further analyzed using the integrated rat-atlas-guided DOT method to form time-evolving 3D images of both cerebral hemodynamics and BFI. In particular, we were able to show and identify therapeutic outcomes of a thrombolytic treatment applied to the embolism-induced ischemic model. This paper demonstrates that volumetric DOT is capable of providing high-quality, interleaved images of cerebral hemodynamics and blood perfusion in small animals during and after ischemic stroke, with excellent 3D visualization and quantifications.
Keywords
NIRSGIIrtPAregional CBFrCBFICGHbO2BFIHbRMCAOCBFCCAROIICADCAMCAECAThree-dimensionalNIRMRImiddle cerebral artery occlusionIndocyanine greenThree-dimensional reconstructionMagnetic resonance imagingDiffuse optical tomographycomputed tomographycerebral blood flowReal worldHBTFinite element modelStrokeblood flow indexmiddle cerebral arteryexternal carotid arteryinternal carotid arterycommon carotid arteryNear-infrared spectroscopyRecombinant tissue plasminogen activatorregion of interestNear-infraredDOTFEMoptical density
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Authors
Zi-Jing Lin, Ming Ren, Lin Li, Yueming Liu, Jianzhong Su, Shao-Hua Yang, Hanli Liu,