Quantitative Analyses on Gait-training Effect of Stroke Rats

Abstract

Brain stroke is serious disease in modern society which has been not ovecame yet. Thus, various researches and therapies about the stroke have been undergone to solve this problem. Recent stroke researches with rats have been represented the researches with human because of better controllability and homogeneous population. Many challenging researches have been applied to stroke rats, especially monitoring methods. Laser monitoring might be the most remarkable methods, since these monitoring systems obtain various information such as blood flow, blood oxygenation with in-vivo state. However, previous laser monitoring systems were inappropriate to be practical uses because of their penetration depth. Diffuse speckle contrast analysis (DSCA) is a monitoring system which measures blood flow index that is calculated by image contrast due to the speckle effect. DSCA could measure the signal under 5mm of tissue. In this study, possibility of recovery monitoring through gait-training of stroke rats was estimated by using DSCA. For statistically validated biological experiment, 30 rats are divided into rehabilitation group (n=10), stroke group(n=10), and normal group(n=10). All experimental groups had blood flow measurement and other quantitative analyses during 14 days and rehabilitation group had treadmill training 8m/min with 30 minutes daily. Results show the cerebral blood flow in infarction of rehabilitation group increases more than that of stroke group. Blood oxygenation monitoring was also applied, however, there are no significant differnence between experiemental group with 635 nm wavelength. Not only blood flow but also sensorimotor function of rehabilitation group is recovered more during recovery period. Histological analysis shows less infarction volume in rehabilitation group compared to stroke group. There are proportional correlation between blood flow and sensorimotor function recovery. We expect that development of DSCA could offer self diagnosis for stroke patients in near future. ⓒ 2017 DGIST