Dataset on stroke infarct volume in rodents: A comparison of MRI and histological methods.

This dataset offers images of mouse brains impacted by photothrombotic stroke in the sensorimotor cortex published by Weber et al. NeuroImage (2024). Data is gathered using two primary techniques: (1) whole-brain ex-vivo magnetic resonance imaging (MRI) and (2) 40 µm thick coronal histological sections that undergo immunofluorescence staining with NeuroTrace. Infarct areas and volumes are assessed through MRI at two distinct time frames-three days (acute) and 28 days (chronic) following photothrombotic stroke induction. Subsequently, the brains are sectioned into 40 µm thick coronal slices, stained with NeuroTrace, and imaged as whole sections. The dataset holds considerable value for reuse, particularly for researchers focused on stroke volume estimation methods as well as those interested in comparing the efficacy of MRI and histological techniques.

A toolkit for stroke infarct volume estimation in rodents.

Stroke volume is a key determinant of infarct severity and an important metric for evaluating treatments. However, accurate estimation of stroke volume can be challenging, due to the often confined 2-dimensional nature of available data. Here, we introduce a comprehensive semi-automated toolkit to reliably estimate stroke volumes based on (1) whole brains ex-vivo magnetic resonance imaging (MRI) and (2) brain sections that underwent immunofluorescence staining. We located and quantified infarct areas from MRI three days (acute) and 28 days (chronic) after photothrombotic stroke induction in whole mouse brains. MRI results were compared with measures obtained from immunofluorescent histologic sections of the same brains. We found that infarct volume determined by post-mortem MRI was highly correlated with a deviation of only 6.6 % (acute) and 4.9 % (chronic) to the measurements as determined in the histological brain sections indicating that both methods are capable of accurately assessing brain tissue damage (Pearson r > 0.9, p < 0.001). The Dice similarity coefficient (DC) showed a high degree of coherence (DC > 0.8) between MRI-delineated regions of interest (ROIs) and ROIs obtained from histologic sections at four to six pre-defined landmarks, with histology-based delineation demonstrating higher inter-operator similarity compared to MR images. We further investigated stroke-related scarring and post-ischemic angiogenesis in cortical peri­infarct regions and described a negative correlation between GFAP+fluorescence intensity and MRI-obtained lesion size.

Optical feedback control loop for the precise and robust acoustic focusing of cells, micro- and nanoparticles.

Despite a long history and the vast number of applications demonstrated, very few market products incorporate acoustophoresis. Because a human operator must run and control a device during an experiment, most devices are limited to proof of concepts. On top of a possible detuning due to temperature changes, the human operator introduces a bias which reduces the reproducibility, performance and reliability of devices. To mitigate some of these problems, we propose an optical feedback control loop that optimizes the excitation frequency. We investigate the improvements that can be expected when a human operator is replaced for acoustic micro- and nanometer particle focusing experiments. Three experiments previously conducted in our group were taken as a benchmark. In addition to being automatic, this resulted in the feedback control loop displaying a superior performance compared to an experienced scientist in 1) improving the particle focusing by at least a factor of two for 5 µm diameter PS particles, 2) increasing the range of flow rates in which 1 µm diameter PS particles could be focused and 3) was even capable of focusing 600 nm diameter PS particles at a frequency of 1.72075 MHz. Furthermore, the feedback control loop is capable of focusing biological cells in one and two pressure nodes. The requirements for the feedback control loop are: an optical setup, a run-of-the-mill computer and a computer controllable function generator. Thus resulting in a cost-effective, high-throughput and automated method to rapidly increase the efficiency of established systems. The code for the feedback control loop is openly accessible and the authors explicitly wish that the community uses and modifies the feedback control loop to their own needs.