Introduction: Recurrent hemodialysis (HD)-induced ischemia has emerged as a mechanism responsible for cognitive impairment in HD patients. Impairment of cerebrovascular function in HD patients may render the brain vulnerable to HD-induced ischemic injury. Cerebrovascular reactivity to CO 2 (CVR) is a noninvasive marker of cerebrovascular function. Whether CVR is impaired in HD patients is unknown. In this study, we compared CVR between healthy participants, HD patients, and chronic kidney disease (CKD)patients not yet requiring dialysis.Methods: This was a single-center prospective observational study carried out at Kidney Clinical Research Unit in London, Canada. We used carefully controlled hypercapnia to interrogate brain vasomotor control. Transcranial Doppler was combined with 10-mm Hg step changes in CO 2 from baseline to hypercapnia (intervention) and back to baseline (recovery) to assess CVR in 8 HD, 10 CKD, and 17 heathy participants.Results: HD patients had lower CVR than CKD or healthy participants during both intervention and recovery (P < 0.0001). There were no differences in CVR between healthy and CKD participants during either intervention (P ¼ 0.88) or recovery (P ¼ 0.99). The impaired CVR in HD patients was independent of CO 2induced changes in blood pressure, heart rate, cardiac output, or dialysis vintage. In the CKD group, CVR was not associated with the estimated glomerular filtration rate.Conclusions: Our study shows that HD patients have impaired CVR relative to CKD and healthy participants. This renders HD patients vulnerable to ischemic injury during circulatory stress of dialysis and may contribute to the pathogenesis of cognitive impairment.

Microvascular blood flow is crucial for tissue and organ function and is often severely affected by diseases. Therefore, investigating the microvasculature under different pathological circumstances is essential to understand the role of the microcirculation in health and sickness. Microvascular blood flow is generally investigated with Intravital Video Microscopy (IVM), and the captured images are stored on a computer for later off-line analysis. The analysis of these images is a manual and challenging process, evaluating experiments very time consuming and susceptible to human error. Since more advanced digital cameras are used in IVM, the experimental data volume will also increase significantly. This study presents a new two-step image processing algorithm that uses a trained Convolutional Neural Network (CNN) to functionally analyze IVM microscopic images without the need for manual analysis. While the first step uses a modified vessel segmentation algorithm to extract the location of vessel-like structures, the second step uses a 3D-CNN to assess whether the vessel-like structures have blood flowing in it or not. We demonstrate that our two-step algorithm can efficiently analyze IVM image data with high accuracy (83%). To our knowledge, this is the first application of machine learning for the functional analysis of microvascular blood flow in vivo.

Background: Ischemic and hyperemic injury have emerged as biologic mechanisms that contribute to cognitive impairment in critically ill patients. Spontaneous deviations in cerebral blood flow (CBF) beyond ischemic and hyperemic thresholds may represent an insult that contributes to this brain injury, especially if they accumulate over time and coincide with impaired autoregulation.Methods: We used transcranial Doppler to measure the proportion of time that CBF velocity (CBFv) deviated beyond previously reported ischemic and hyperemic thresholds in a cohort of critically ill patients with respiratory failure and/or shock within 48 h of ICU admission. We also assessed whether these CBFv deviations were more common during periods of impaired dynamic autoregulation, and whether they are explained by concurrent variations in mean arterial pressure (MAP) and end-tidal PCO2 (PetCO2).Results: We enrolled 12 consecutive patients (three females) who were monitored for a mean duration of 462.6 ± 39.8 min. Across patients, CBFv deviated by more than 20–30% from its baseline for 17–24% of the analysis time. These CBFv deviations occurred equally during periods of preserved and impaired autoregulation, while concurrent variations in MAP and PetCO2 explained only 13–21% of these CBFv deviations.Conclusion: CBFv deviations beyond ischemic and hyperemic thresholds are common in critically ill patients with respiratory failure or shock. These deviations occur irrespective of the state of dynamic autoregulation and are not explained by changes in MAP and CO2. Future studies should explore mechanisms responsible for these CBFv deviations and establish whether their cumulative burden predicts poor neurocognitive outcomes.

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