suMRak: a multi-tool solution for preclinical brain MRI data analysis.

Introduction: Magnetic resonance imaging (MRI) is invaluable for understanding brain disorders, but data complexity poses a challenge in experimental research. In this study, we introduce suMRak, a MATLAB application designed for efficient preclinical brain MRI analysis. SuMRak integrates brain segmentation, volumetry, image registration, and parameter map generation into a unified interface, thereby reducing the number of separate tools that researchers may require for straightforward data handling. Methods and implementation: All functionalities of suMRak are implemented using the MATLAB App Designer and the MATLAB-integrated Python engine. A total of six helper applications were developed alongside the main suMRak interface to allow for a cohesive and streamlined workflow. The brain segmentation strategy was validated by comparing suMRak against manual segmentation and ITK-SNAP, a popular open-source application for biomedical image segmentation. Results: When compared with the manual segmentation of coronal mouse brain slices, suMRak achieved a high Sørensen-Dice similarity coefficient (0.98 ± 0.01), approaching manual accuracy. Additionally, suMRak exhibited significant improvement (p = 0.03) when compared to ITK-SNAP, particularly for caudally located brain slices. Furthermore, suMRak was capable of effectively analyzing preclinical MRI data obtained in our own studies. Most notably, the results of brain perfusion map registration to T2-weighted images were shown, improving the topographic connection to anatomical areas and enabling further data analysis to better account for the inherent spatial distortions of echoplanar imaging. Discussion: SuMRak offers efficient MRI data processing of preclinical brain images, enabling researchers' consistency and precision. Notably, the accelerated brain segmentation, achieved through K-means clustering and morphological operations, significantly reduces processing time and allows for easier handling of larger datasets.

Redefining the Koizumi model of mouse cerebral ischemia: A comparative longitudinal study of cerebral and retinal ischemia in the Koizumi and Longa middle cerebral artery occlusion models.

Cerebral and retinal ischemia share similar pathogenesis and epidemiology, each carrying both acute and prolonged risk of the other and often co-occurring. The most used preclinical stroke models, the Koizumi and Longa middle cerebral artery occlusion (MCAO) methods, have reported retinal damage with great variability, leaving the disruption of retinal blood supply via MCAO poorly investigated, even providing conflicting assumptions on the origin of the ophthalmic artery in rodents. The aim of our study was to use longitudinal in vivo magnetic resonance assessment of cerebral and retinal vascular perfusion after the ischemic injury to clarify whether and how the Koizumi and Longa methods induce retinal ischemia and how they differ in terms of cerebral and retinal lesion evolution. We provided anatomical evidence of the origin of the ophthalmic artery in mice from the pterygopalatine artery. Following the Koizumi surgery, retinal responses to ischemia overlapped with those in the brain, resulting in permanent damage. In contrast, the Longa method produced only extensive cerebral lesions, with greater tissue loss than in the Koizumi method. Additionally, our data suggests the Koizumi method should be redefined as a model of ischemia with chronic hypoperfusion rather than of ischemia and reperfusion.

Lentivirus- or AAV-mediated gene therapy interventions in ischemic stroke: A systematic review of preclinical in vivo studies.

Due to the limited therapeutic options after ischemic stroke, gene therapy has emerged as a promising choice, especially with recent advances in viral vector delivery systems. Therefore, we aimed to provide the current state of the art of lentivirus (LV) and adeno-associated virus (AAV) mediated gene interventions in preclinical ischemic stroke models. A systematic analysis including qualitative and quantitative syntheses of studies published until December 2020 was performed. Most of the 87 selected publications used adult male rodents and the preferred stroke model was transient middle cerebral artery occlusion. LV and AAV vectors were equally used for transgene delivery, however loads of AAVs were higher than LVs. Serotypes having broad cell tropism, the use of constitutive promoters, and virus delivery before the stroke induction via stereotaxic injection in the cortex and striatum were preferred in the analyzed studies. The meta-analysis based on infarct volume as the primary outcome confirmed the efficacy of the preclinical interventions. The quality assessment exposed publication bias and setbacks in regard to risks of bias and study relevance. The translational potential could increase by using specific cell targeting, post-stroke interventions, non-invasive systematic delivery, and use of large animals.