The transient receptor potential melastatin 4 (TRPM4) channel has been suggested to play a key role in the treatment of ischemic stroke. However, in vivo evaluation of TRPM4 channel, in particular by direct channel suppression, is lacking. In this study, we used multimodal imaging to assess edema formation and quantify the amount of metabolically functional brain salvaged after a rat model of stroke reperfusion. TRPM4 upregulation in endothelium emerges as early as 2 h post-stroke induction. Expression of TRPM4 channel was suppressed directly in vivo by treatment with siRNA; scrambled siRNA was used as a control. T2-weighted MRI suggests that TRPM4 inhibition successfully reduces edema by 30% and concomitantly salvages functionally active brain, measured by F-FDG-PET. These in vivo imaging results correlate well with post-mortem 2,3,5-triphenyltetrazolium chloride (TTC) staining which exhibits a 34.9% reduction in infarct volume after siRNA treatment. Furthermore, in a permanent stroke model, large areas of brain tissue displayed both edema and significant reductions in metabolic activity which was not shown in transient models with or without TRPM4 inhibition, indicating that tissue salvaged by TRPM4 inhibition during stroke reperfusion may survive. Evans Blue extravasation and hemoglobin quantification in the ipsilateral hemisphere were greatly reduced, suggesting that TRPM4 inhibition can improve BBB integrity after ischemic stroke reperfusion. Our results support the use of TRPM4 blocker for early stroke reperfusion.

Brain extraction is an important preprocessing step for further analysis of brain MR images. Significant intensity inhomogeneity can be observed in rodent brain images due to the high-field MRI technique. Unlike most existing brain extraction methods that require bias corrected MRI, we present a high-order and L regularized variational model for bias correction and brain extraction. The model is composed of a data fitting term, a piecewise constant regularization and a smooth regularization, which is constructed on a 3-D formulation for medical images with anisotropic voxel sizes. We propose an efficient multi-resolution algorithm for fast computation. At each resolution layer, we solve an alternating direction scheme, all subproblems of which have the closed-form solutions. The method is tested on three T2 weighted acquisition configurations comprising a total of 50 rodent brain volumes, which are with the acquisition field strengths of 4.7 Tesla, 9.4 Tesla and 17.6 Tesla, respectively. On one hand, we compare the results of bias correction with N3 and N4 in terms of the coefficient of variations on 20 different tissues of rodent brain. On the other hand, the results of brain extraction are compared against manually segmented gold standards, BET, BSE and 3-D PCNN based on a number of metrics. With the high accuracy and efficiency, our proposed method can facilitate automatic processing of large-scale brain studies.

The present findings highlight the adaptive nature of responses to citalopram which exhibits regional and pharmacological specificity. These findings translate well to the clinical findings and suggest that this approach may offer the opportunity to develop more efficacious antidepressants with a faster clinical response.