Sydney C Lindner1, Marina Yu2, Jeffrey R Capadona2, Andrew J Shoffstall3. 1. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States. 2. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States. 3. Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, United States. Electronic address: Ajs215@case.edu.
Abstract
BACKGROUND: Brain-implanted devices, including intracortical microelectrodes, are used in neuroscience applications ranging from research to rehabilitation and beyond. Significant efforts are focused on developing new device designs and insertion strategies that mitigate initial trauma and subsequent neuroinflammation that occurs as a result of implantation. A frequently published metric is the neuroinflammatory response quantified as a function of distance from the interface edge, using fluorescent immunohistochemical markers. NEW METHOD: Here, we sought to develop a graphical user interface software in Matlab to provide an objective, repeatable, and easy-to-use method for analyzing fluorescence immunohistochemistry images of neuroinflammation. The user interface allows for efficient batch-processing and review of images, and incorporates zoom and contrast features to improve the accuracy of identifying the 'region of interest' (ROI). RESULTS: The software was validated against previously published results and demonstrated equivalent scientific conclusions. Furthermore, a comparison between novice and expert users demonstrated consistency across levels of training and a rapid learning-curve. COMPARISON WITH EXISTING METHOD(S): Existing methods published in the intracortical microelectrode literature include a wide variety of procedures within ImageJ and Matlab. However, specific procedural details are often lacking. CONCLUSIONS: The distribution of the methodology may promote efficiency and reproducibility across the field seeking to characterize the tissue response to implanted neural interfaces. It may also serve as a template for researchers seeking to perform other types of histological quantification as a function of distance from an ROI. Published by Elsevier B.V.
BACKGROUND: Brain-implanted devices, including intracortical microelectrodes, are used in neuroscience applications ranging from research to rehabilitation and beyond. Significant efforts are focused on developing new device designs and insertion strategies that mitigate initial trauma and subsequent neuroinflammation that occurs as a result of implantation. A frequently published metric is the neuroinflammatory response quantified as a function of distance from the interface edge, using fluorescent immunohistochemical markers. NEW METHOD: Here, we sought to develop a graphical user interface software in Matlab to provide an objective, repeatable, and easy-to-use method for analyzing fluorescence immunohistochemistry images of neuroinflammation. The user interface allows for efficient batch-processing and review of images, and incorporates zoom and contrast features to improve the accuracy of identifying the 'region of interest' (ROI). RESULTS: The software was validated against previously published results and demonstrated equivalent scientific conclusions. Furthermore, a comparison between novice and expert users demonstrated consistency across levels of training and a rapid learning-curve. COMPARISON WITH EXISTING METHOD(S): Existing methods published in the intracortical microelectrode literature include a wide variety of procedures within ImageJ and Matlab. However, specific procedural details are often lacking. CONCLUSIONS: The distribution of the methodology may promote efficiency and reproducibility across the field seeking to characterize the tissue response to implanted neural interfaces. It may also serve as a template for researchers seeking to perform other types of histological quantification as a function of distance from an ROI. Published by Elsevier B.V.
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