Systemic biomarker associated with poor outcome after futile reperfusion.

BACKGROUND: Successful recanalization does not lead to complete tissue reperfusion in a considerable percentage of ischemic stroke patients. This study aimed to identify biomarkers associated with futile recanalization. Leukoaraiosis predicts poor outcomes of this phenomenon. Soluble tumour necrosis factor-like weak inducer of apoptosis (sTWEAK), which is associated with leukoaraiosis degrees, could be a potential biomarker. METHODS: This study includes two cohorts of ischemic stroke patients in a multicentre retrospective observational study. Effective reperfusion, defined as a reduction of ≥8 points in the National Institutes of Health Stroke Scale (NIHSS) within the first 24 h, was used as a clinical marker of effective reperfusion. RESULTS: In the first cohort study, female sex, age, and high NIHSS at admission (44.7% vs. 81.1%, 71.3 ± 13.7 vs. 81.1 ± 6.7; 16 [13, 21] vs. 23 [17, 28] respectively; p < .0001) were confirmed as predictors of futile recanalization. ROC curve analysis showed that leukocyte levels (sensitivity of 99%, specificity of 55%) and sTWEAK level (sensitivity of 92%, specificity of 88%) can discriminate between poor and good outcomes. Both biomarkers simultaneously are higher associated with outcome after effective reperfusion (OR: 2.17; CI 95% 1.63-4.19; p < .0001) than individually (leukocytes OR: 1.38; CI 95% 1.00-1.64, p = .042; sTWEAK OR: 1.00; C I95% 1.00-1.01, p = .019). These results were validated using a second cohort, where leukocytes and sTWEAK showed a sensitivity of 100% and specificity of 66.7% and 75% respectively. CONCLUSIONS: Leukocyte and sTWEAK could be biomarkers of reperfusion failure and subsequent poor outcomes. Further studies will be necessary to explore its role in reperfusion processes.

Perfusion-weighted software written in Python for DSC-MRI analysis.

Introduction: Dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion studies in magnetic resonance imaging (MRI) provide valuable data for studying vascular cerebral pathophysiology in different rodent models of brain diseases (stroke, tumor grading, and neurodegenerative models). The extraction of these hemodynamic parameters via DSC-MRI is based on tracer kinetic modeling, which can be solved using deconvolution-based methods, among others. Most of the post-processing software used in preclinical studies is home-built and custom-designed. Its use being, in most cases, limited to the institution responsible for the development. In this study, we designed a tool that performs the hemodynamic quantification process quickly and in a reliable way for research purposes. Methods: The DSC-MRI quantification tool, developed as a Python project, performs the basic mathematical steps to generate the parametric maps: cerebral blood flow (CBF), cerebral blood volume (CBV), mean transit time (MTT), signal recovery (SR), and percentage signal recovery (PSR). For the validation process, a data set composed of MRI rat brain scans was evaluated: i) healthy animals, ii) temporal blood-brain barrier (BBB) dysfunction, iii) cerebral chronic hypoperfusion (CCH), iv) ischemic stroke, and v) glioblastoma multiforme (GBM) models. The resulting perfusion parameters were then compared with data retrieved from the literature. Results: A total of 30 animals were evaluated with our DSC-MRI quantification tool. In all the models, the hemodynamic parameters reported from the literature are reproduced and they are in the same range as our results. The Bland-Altman plot used to describe the agreement between our perfusion quantitative analyses and literature data regarding healthy rats, stroke, and GBM models, determined that the agreement for CBV and MTT is higher than for CBF. Conclusion: An open-source, Python-based DSC post-processing software package that performs key quantitative perfusion parameters has been developed. Regarding the different animal models used, the results obtained are consistent and in good agreement with the physiological patterns and values reported in the literature. Our development has been built in a modular framework to allow code customization or the addition of alternative algorithms not yet implemented.

Influence of Temperature Chronobiology on Stroke Outcome.

The circadian system regulates numerous physiological variables, including body temperature. Additionally, a circadian patter has been described in stroke onset. Considering this, we hypothesised that the chronobiology of temperature may have an impact on stroke onset and functional outcomes. We also studied the variation of blood biomarkers according to stroke onset time. This is a retrospective observational study. Of the patients included, 2763 had a stroke between midnight and 8:00 h; 1571 between 8:00-14:00 h; and 655 between 14:00 h and midnight. Axillary temperature was measured at admission. At this time, blood samples were collected for biomarker analysis (TNF-α, IL-1ß, IL-6, IL-10, and glutamate). Temperature was higher in patients admitted from 8:00 h to midnight (p < 0.0001). However, the percentage of poor outcome at 3 months was highest in patients from midnight to 8:00 h (57.7%, p < 0.001). The association between temperature and mortality was highest during night time (OR: 2.79; CI 95%: 2.36-3.28; p < 0.001). These patients exhibited high glutamate (220.2 ± 140.2 µM), IL-6 (32.8 ± 14.3 pg/mL) and low IL-10 (9.7 ± 14.3 pg/mL) levels. Therefore, temperature chronobiology could have a significant impact on stroke onset and functional outcome. Superficial body hyperthermia during sleep seems to be more dangerous than during wakefulness. Further studies will be necessary to confirm our data.

Need for a Paradigm Shift in the Treatment of Ischemic Stroke: The Blood-Brain Barrier.

Blood-brain barrier (BBB) integrity is essential to maintaining brain health. Aging-related alterations could lead to chronic progressive leakiness of the BBB, which is directly correlated with cerebrovascular diseases. Indeed, the BBB breakdown during acute ischemic stroke is critical. It remains unclear, however, whether BBB dysfunction is one of the first events that leads to brain disease or a down-stream consequence. This review will focus on the BBB dysfunction associated with cerebrovascular disease. An added difficulty is its association with the deleterious or reparative effect, which depends on the stroke phase. We will first outline the BBB structure and function. Then, we will focus on the spatiotemporal chronic, slow, and progressive BBB alteration related to ischemic stroke. Finally, we will propose a new perspective on preventive therapeutic strategies associated with brain aging based on targeting specific components of the BBB. Understanding BBB age-evolutions will be beneficial for new drug development and the identification of the best performance window times. This could have a direct impact on clinical translation and personalised medicine.