BACKGROUND AND PURPOSE: The extent of brain infarction after local cerebral ischemia is frequently assessed with the mitochondrial activity indicator 2,3,5-triphenyltetrazolium chloride (TTC). We describe an automated procedure for analysis of infarct size in TTC-stained rat brains. METHODS: Rats were subjected to middle cerebral artery occlusion and killed after 24 to 36 hours, and their brains were processed for TTC staining. Digital images of coronal sections from these brains (n > 50) were acquired with a desktop color scanner. The resulting images were divided into red, blue, and green component images. Total brain and infarct areas were automatically determined on the basis of total pixel intensity and area after segmentation of the red and green images, respectively. Automated measurements were compared with those made with a video camera-based image acquisition system that required manual tracing of lesion boundaries. RESULTS: The spatial resolution of scanned brain images (approximately equal to 200 microns) was comparable to that of the camera-based system and provided sufficient detail to recognize infarct boundaries and neuroanatomical features. Scanner-based acquisition and analysis were faster than with the camera-based method. The green component image accurately distinguished infarcted from normal brain, and the red component image represented total brain dimensions. Infarct measurements obtained by the automated method correlated closely with those from conventional apparatus (R2 = .89, P < .001). Intraobserver reliability with the automated method (R2 = 1.00) was higher than with the conventional method (R2 = .77). CONCLUSIONS: Infarct size after middle cerebral artery occlusion in the rat can be rapidly and reproducibly assessed with inexpensive scanning equipment and automated image analysis of TTC-stained brains.
BACKGROUND AND PURPOSE: The extent of brain infarction after local cerebral ischemia is frequently assessed with the mitochondrial activity indicator 2,3,5-triphenyltetrazolium chloride (TTC). We describe an automated procedure for analysis of infarct size in TTC-stained rat brains. METHODS:Rats were subjected to middle cerebral artery occlusion and killed after 24 to 36 hours, and their brains were processed for TTC staining. Digital images of coronal sections from these brains (n > 50) were acquired with a desktop color scanner. The resulting images were divided into red, blue, and green component images. Total brain and infarct areas were automatically determined on the basis of total pixel intensity and area after segmentation of the red and green images, respectively. Automated measurements were compared with those made with a video camera-based image acquisition system that required manual tracing of lesion boundaries. RESULTS: The spatial resolution of scanned brain images (approximately equal to 200 microns) was comparable to that of the camera-based system and provided sufficient detail to recognize infarct boundaries and neuroanatomical features. Scanner-based acquisition and analysis were faster than with the camera-based method. The green component image accurately distinguished infarcted from normal brain, and the red component image represented total brain dimensions. Infarct measurements obtained by the automated method correlated closely with those from conventional apparatus (R2 = .89, P < .001). Intraobserver reliability with the automated method (R2 = 1.00) was higher than with the conventional method (R2 = .77). CONCLUSIONS:Infarct size after middle cerebral artery occlusion in the rat can be rapidly and reproducibly assessed with inexpensive scanning equipment and automated image analysis of TTC-stained brains.
Authors: Marcio Wilker Soares Campelo; Reinaldo Barreto Oriá; Luiz Gonzaga de França Lopes; Gerly Anne de Castro Brito; Armenio Aguiar dos Santos; Raquel Cavalcante de Vasconcelos; Francisco Ordelei Nascimento da Silva; Beatrice Nuto Nobrega; Moisés Tolentino Bento-Silva; Paulo Roberto Leitão de Vasconcelos Journal: Neurochem Res Date: 2011-12-10 Impact factor: 3.996
Authors: Robert F Menger; Whitney L Stutts; Dhanalakshmi S Anbukumar; John A Bowden; David A Ford; Richard A Yost Journal: Anal Chem Date: 2011-12-22 Impact factor: 6.986
Authors: Katherine Poinsatte; Uma Maheswari Selvaraj; Sterling B Ortega; Erik J Plautz; Xiangmei Kong; Jeffrey M Gidday; Ann M Stowe Journal: J Vis Exp Date: 2015-05-04 Impact factor: 1.355