Abstract:
Objective To assess the value of contrast-enhanced ultrasound (CEUS) and color Doppler ultrasound (DUS) on hemodynamic changes and cerebral perfusion quantitative analyses in Sprague-Dawley (SD) rats with focal permanent ischemic stroke.
Methods Sixteen SD rats with thin skulls were subjected to establish middle cerebral artery occlusion (MCAO) model. CEUS images were performed before modeling (T0), immediately after modeling (5-15 min after modeling, T1), 3 h after modeling (T2), followed by the measurement of bilateral middle cerebral artery (MCA), anterior cerebral artery (ACA), posterior cerebral artery (PCA) using DUS. The peak systolic velocity (PSV), end-diastolic velocity (EDV) and mean velocity (MV) of these arteries were obtained. The brain time-intensity curve was taken as interest region of the whole right brain, and the quantitative parameters of CEUS were obtained, including peak intensity (PI), area under the curve (AUC), wash in slope (WIS), time to peak (TTP), rise time (RT) and time from peak to one half (TPH). The modified neurological deficit score (mNSS) of the rats was performed 3 h after the modeling, and the data of the rats with a score of 9-11 were statistically analyzed.
Results A total of 12 rats were successfully modeled and completed with mNSS score 9-11. No blood flow signals were observed on the right MCA and ACA in the 12 rats at T1 and T2. From T0 to T1, PI, AUC and WIS of the right hemisphere decreased sharply with TTP and RT significantly prolonged, and the differences were statistically significant. However, there was no significant difference in hemodynamic parameters at that period of time. From T1 to T2, there were no significant changes in CEUS quantitative parameters (except AUC and TPH), while PSV, EDV, MV of LMCA and bilateral PCA showed significant acceleration, and the differences were statistically significant.
Conclusion CEUS and DUS can reveal the intracranial hemodynamics and brain tissue perfusion trends of MCAO rats, which could be new methods in assessment of ischemic stroke model at multiple time points.