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Maintaining cerebral perfusion pressure in the brain when a carotid artery is closed during vascular surgery is critical for avoiding intraoperative hypoperfusion and risk of ischemic stroke. Here we propose and evaluate a method based on computational fluid dynamics for predicting patient-specific cerebral perfusion pressures at carotid clamping during carotid endarterectomy. The study consisted of 22 patients with symptomatic carotid stenosis who underwent carotid endarterectomy (73 ± 5 years, 59–80 years, 17 men). The geometry of the circle of Willis was obtained preoperatively from computed tomography angiography and corresponding flow rates from four-dimensional flow magnetic resonance imaging. The patients were also classified as having a present or absent ipsilateral posterior communicating artery based on computed tomography angiography. The predicted mean stump pressures from computational fluid dynamics were compared with intraoperatively measured stump pressures from carotid endarterectomy. On group level, there was no difference between the predicted and measured stump pressures (−0.5 ± 13 mmHg, P = 0.86) and the pressures were correlated (r = 0.44, P = 0.039). Omitting two outliers, the correlation increased to r = 0.78 (P < 0.001) (−1.4 ± 8.0 mmHg, P = 0.45). Patients with a present ipsilateral posterior communicating artery (n = 8) had a higher measured stump pressure than those with an absent artery (n = 12) (P < 0.001). The stump pressure agreement indicates that the computational fluid dynamics approach was promising in predicting cerebral perfusion pressures during carotid clamping, which may prove useful in the preoperative planning of vascular interventions. • Predicting cerebral perfusion pressures by computational fluid dynamics. • Intraoperatively measure stump pressures from carotid endarterectomy as reference. • 4D flow MRI allows for patient-specific model characterization. • Good group-level agreement, with predicted and reference pressures well correlated. • Approach may prove useful in preoperative planning of vascular interventions. [ABSTRACT FROM AUTHOR]

Selective antegrade cerebral perfusion (SACP) is a protective procedure to ascertain adequate brain perfusion during aortic arch surgeries requiring moderate hypothermic circulatory arrest. SACP entails catheterization of arteries feeding the brain, which can be done bilaterally (bSACP) or unilaterally (uSACP), but there is no consensus on when to use each approach. bSACP may increase the risk of embolization, while uSACP risks hypoperfusion due to insufficient perfusion pressure in the contralateral hemisphere, since a single catheter must perfuse both hemispheres. We developed and tested the feasibility of a new method for predicting cerebral perfusion pressures (CPP) during SACP, which could potentially aid clinicians in preoperatively identifying which SACP approach to use. Feasibility of the method was evaluated in five patients eligible for aortic arch surgery (65 ± 7 years, 3 men). Patients were investigated preoperatively with computed tomography angiography (CTA) and 4D flow magnetic resonance imaging (MRI) to assess patient-specific arterial anatomy and blood flows. From the imaging, computational fluid dynamics (CFD) simulations estimated the patients' vascular resistances. Applying these resistances and intraoperative SACP pressure/flow settings to the model's boundary conditions allowed for predictions of contralateral CPP during SACP. Predicted pressures were compared to corresponding intraoperative pressure measurements. The method showed promise for predicting contralateral CPP during both uSACP (median error (range): 2.4 (-0.2-18.0) mmHg) and bSACP (0.8 (-3.3-5.4) mmHg). Predictions were most sensitive to collateral artery size. This study showed the feasibility of CPP predictions of SACP, and presents key features needed for accurate modelling., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Higher-Level Gait Disorder (HLGD) is a type of gait disorder estimated to affect up to 6% of the older population. By definition, its symptoms originate from the higher-level nervous system, yet its association with brain morphology remains unclear. This study hypothesizes that there are patterns in brain morphology linked to HLGD. For the first time in the literature, this work investigates whether deep learning, in the form of convolutional neural networks, can capture patterns in magnetic resonance images to identify individuals affected by HLGD. To handle this new classification task, we propose setting up an ensemble of models. This leverages the benefits of combining classifiers instead of determining which network is the most suitable, developing a new architecture, or customizing an existing one. We introduce a computationally cost-effective search algorithm to find the optimal ensemble by leveraging a cost function of both traditional performance scores and the diversity among the models. Using a unique dataset from a large population-based cohort (VESPR), the ensemble identified by our algorithm demonstrated superior performance compared to single networks, other ensemble fusion techniques, and the best linear radiological measure. This emphasizes the importance of implementing diversity into the cost function. Furthermore, the results indicate significant morphological differences in brain structure between HLGD-affected individuals and controls, motivating research about which areas the networks base their classifications on, to get a better understanding of the pathophysiology of HLGD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Over the last decade, it has become evident that cerebrospinal fluid (CSF) plays a pivotal role in brain solute clearance through perivascular pathways and interactions between the brain and meningeal lymphatic vessels. Whereas most of this fundamental knowledge was gained from rodent models, human brain clearance imaging has provided important insights into the human system and highlighted the existence of important interspecies differences. Current gold standard techniques for human brain clearance imaging involve the injection of gadolinium-based contrast agents and monitoring their distribution and clearance over a period from a few hours up to 2 days. With both intrathecal and intravenous injections being used, which each have their own specific routes of distribution and thus clearance of contrast agent, a clear understanding of the kinetics associated with both approaches, and especially the differences between them, is needed to properly interpret the results. Because it is known that intrathecally injected contrast agent reaches the blood, albeit in small concentrations, and that similarly some of the intravenously injected agent can be detected in CSF, both pathways are connected and will, in theory, reach the same compartments. However, because of clear differences in relative enhancement patterns, both injection approaches will result in varying sensitivities for assessment of different subparts of the brain clearance system. In this opinion review article, the "EU Joint Programme - Neurodegenerative Disease Research (JPND)" consortium on human brain clearance imaging provides an overview of contrast agent pharmacokinetics in vivo following intrathecal and intravenous injections and what typical concentrations and concentration-time curves should be expected. This can be the basis for optimizing and interpreting contrast-enhanced MRI for brain clearance imaging. Furthermore, this can shed light on how molecules may exchange between blood, brain, and CSF., (© 2024 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.)

Cerebrovascular resistance (CVR) regulates blood flow in the brain, but little is known about the vascular resistances of the individual cerebral territories. We present a method to calculate these resistances and investigate how CVR varies in the hemodynamically disturbed brain. We included 48 patients with stroke/TIA (29 with symptomatic carotid stenosis). By combining flow rate (4D flow MRI) and structural computed tomography angiography (CTA) data with computational fluid dynamics (CFD) we computed the perfusion pressures out from the circle of Willis, with which CVR of the MCA, ACA, and PCA territories was estimated. 56 controls were included for comparison of total CVR (tCVR). CVR were 33.8 ± 10.5, 59.0 ± 30.6, and 77.8 ± 21.3 mmHg s/ml for the MCA, ACA, and PCA territories. We found no differences in tCVR between patients, 9.3 ± 1.9 mmHg s/ml, and controls, 9.3 ± 2.0 mmHg s/ml (p = 0.88), nor in territorial CVR in the carotid stenosis patients between ipsilateral and contralateral hemispheres. Territorial resistance associated inversely to territorial brain volume (p < 0.001). These resistances may work as reference values when modelling blood flow in the circle of Willis, and the method can be used when there is need for subject-specific analysis., (© 2024. The Author(s).)

Alterations in cerebral blood flow are common in several neurological diseases among the elderly including stroke, cerebral small vessel disease, vascular dementia, and Alzheimer's disease. 4D flow magnetic resonance imaging (MRI) is a relatively new technique to investigate cerebrovascular disease, and makes it possible to obtain time-resolved blood flow measurements of the entire cerebral arterial venous vasculature and can be used to derive a repertoire of hemodynamic biomarkers indicative of cerebrovascular health. The information that can be obtained from one single 4D flow MRI scan allows both the investigation of aberrant flow patterns at a focal location in the vasculature as well as estimations of brain-wide disturbances in blood flow. Such focal and global hemodynamic biomarkers show the potential of being sensitive to impending cerebrovascular disease and disease progression and can also become useful during planning and follow-up of interventions aiming to restore a normal cerebral circulation. Here, we describe 4D flow MRI approaches for analyzing the cerebral vasculature. We then survey key hemodynamic biomarkers that can be reliably assessed using the technique. Finally, we highlight cerebrovascular diseases where one or multiple hemodynamic biomarkers are of central interest., (© 2021 The Authors. Journal of Internal Medicine published by John Wiley & Sons Ltd on behalf of Association for Publication of The Journal of Internal Medicine.)

The dopamine (DA) system plays an important role in cognition. Accordingly, normal variation in DA genes has been found to predict individual differences in cognitive performance. However, little is known of the impact of genetic differences on the link between empirical indicators of the DA system and cognition in humans. The present work used PET with 11 C-raclopride to assess DA D2-receptor binding potential (BP) and links to episodic memory, working memory, and perceptual speed in 179 healthy adults aged 64-68 years. Previously, the T-allele of a DA D2-receptor single-nucleotide polymorphism, C957T, was associated with increased apparent affinity of 11 C-raclopride, giving rise to higher BP values despite similar receptor density values between allelic groups. Consequently, we hypothesized that 11 C-raclopride BP measures inflated by affinity rather than D2-receptor density in T-allele carriers would not be predictive of DA integrity and therefore prevent finding an association between 11 C-raclopride BP and cognitive performance. In accordance with previous findings, we show that 11 C-raclopride BP was increased in T-homozygotes. Importantly, 11 C-raclopride BP was only associated with cognitive performance in groups with low or average ligand affinity (C-allele carriers of C957T, n = 124), but not in the high-affinity group (T-homozygotes, n = 55). The strongest 11 C-raclopride BP-cognition associations and the highest level of performance were found in C-homozygotes. These findings show that genetic differences modulate the link between BP and cognition and thus have important implications for the interpretation of DA assessments with PET and 11 C-raclopride in multiple disciplines ranging from cognitive neuroscience to psychiatry and neurology.

Dopamine (DA) modulates corticostriatal connections. Studies in which imaging of the DA system is integrated with functional imaging during cognitive performance have yielded mixed findings. Some work has shown a link between striatal DA (measured by PET) and fMRI activations, whereas others have failed to observe such a relationship. One possible reason for these discrepant findings is differences in task demands, such that a more demanding task with greater prefrontal activations may yield a stronger association with DA. Moreover, a potential DA-BOLD association may be modulated by task performance. We studied 155 (104 normal-performing and 51 low-performing) healthy older adults (43% females) who underwent fMRI scanning while performing a working memory (WM) n -back task along with DA D 2/3 PET assessment using [ 11 C]raclopride. Using multivariate partial-least-squares analysis, we observed a significant pattern revealing positive associations of striatal as well as extrastriatal DA D 2/3 receptors to BOLD response in the thalamo-striatal-cortical circuit, which supports WM functioning. Critically, the DA-BOLD association in normal-performing, but not low-performing, individuals was expressed in a load-dependent fashion, with stronger associations during 3-back than 1-/2-back conditions. Moreover, normal-performing adults expressing upregulated BOLD in response to increasing task demands showed a stronger DA-BOLD association during 3-back, whereas low-performing individuals expressed a stronger association during 2-back conditions. This pattern suggests a nonlinear DA-BOLD performance association, with the strongest link at the maximum capacity level. Together, our results suggest that DA may have a stronger impact on functional brain responses during more demanding cognitive tasks. SIGNIFICANCE STATEMENT Dopamine (DA) is a major neuromodulator in the CNS and plays a key role in several cognitive processes via modulating the blood oxygenation level-dependent (BOLD) signal. Some studies have shown a link between DA and BOLD, whereas others have failed to observe such a relationship. A possible reason for the discrepancy is differences in task demands, such that a more demanding task with greater prefrontal activations may yield a stronger association with DA. We examined the relationship of DA to BOLD response during working memory under three load conditions and found that the DA-BOLD association is expressed in a load-dependent fashion. These findings may help explain the disproportionate impairment evident in more effortful cognitive tasks in normal aging and in those suffering dopamine-dependent neurodegenerative diseases (e.g., Parkinson's disease)., (Copyright © 2019 Salami et al.)

Evidence suggests that associations between the neurotransmitter dopamine and cognition are nonmonotonic and open to modulation by various other factors. The functional implications of a given level of dopamine may therefore differ from person to person. By applying latent-profile analysis to a large (n = 181) sample of adults aged 64-68 years, we probabilistically identified 3 subgroups that explain the multivariate associations between dopamine D2/3R availability (probed with 11C-raclopride-PET, in cortical, striatal, and hippocampal regions) and cognitive performance (episodic memory, working memory, and perceptual speed). Generally, greater receptor availability was associated with better cognitive performance. However, we discovered a subgroup of individuals for which high availability, particularly in striatum, was associated with poor performance, especially for working memory. Relative to the rest of the sample, this subgroup also had lower education, higher body-mass index, and lower resting-state connectivity between caudate nucleus and dorsolateral prefrontal cortex. We conclude that a smaller subset of individuals induces a multivariate non-linear association between dopamine D2/3R availability and cognitive performance in this group of older adults, and discuss potential reasons for these differences that await further empirical scrutiny.