Background: The middle cerebral artery occlusion (MCAO) model is widely used in ischemic stroke research. But current infarct volume measurements rely on destructive 2, 3, 5-triphenyltetrazolium chloride (TTC) staining or costly, often unavailable MRI. Neurological deficit scores alone provide limited accuracy. We aimed to development a rapid, inexpensive, and non-destructive method for accurately estimating infarct volume and evaluating neuroprotective efficacy. Methods: Data from 295 male Sprague-Dawley (SD) rats subjected to MCAO were retrospectively analyzed. Variables included TTC-measured infarct volume, a newly developed visual Infarct Score (48 h), neurological deficit scores (Longa and Ludmila Belayev), body weight, and percentage weight change at multiple time points. Correlation analyses were performed to evaluate associations with infarct volume, and statistical comparisons were conducted to assess difference between treatment and non-treatment groups. A Comprehensive Score integrating the five most strongly correlated variables was constructed to enhance infarct volume prediction. Results: Infarct Score₄8h showed a very strong correlation with infarct volume (ρ = 0. 79, adjusted p= 1. 34E-25), outperforming other single variables. Longa and Ludmila Belayev scores at 24 and 48 h correlated positively with infarct volume (ρ=0. 55–0. 58). Wt₄8h (ρ = -0. 41, p = 2. 13E-07) and WtChange₄8h. percent (ρ = -0. 42, p = 1. 67E-07) correlated negatively. Treatments, including therapeutic hypothermia, nitroglycerin, remote ischemic conditioning followed by exercise, significantly reduced infarct volume, Infarct Score₄8h and neurological deficits, at 24- and 48-hours post-stroke while attenuating weight loss. The Comprehensive Score demonstrated the highest predictive accuracy (ρ = 0. 90, adjusted p = 9. 62E-11). Conclusion: The Infarct Score provides a simple, rapid, and cost-effective method for infarct and brain damage assessment. The Comprehensive Score further enhances predictive precision, supporting its use as a multidimensional tool for assessing stroke severity and treatment efficacy in preclinical studies.
Mu et al. (Thu,) studied this question.