While COVID-19 is primarily considered a respiratory disease, it has been shown to affect the central nervous system. Mounting evidence shows that COVID-19 is associated with neurological complications as well as effects thought to be related to neuroinflammatory processes. Due to the novelty of COVID-19, there is a need to better understand the possible long-term effects it may have on patients, particularly linkage to neuroinflammatory processes. Perivascular spaces (PVS) are small fluid-filled spaces in the brain that appear on MRI scans near blood vessels and are believed to play a role in modulation of the immune response, leukocyte trafficking, and glymphatic drainage. Some studies have suggested that increased number or presence of PVS could be considered a marker of increased blood-brain barrier permeability or dysfunction and may be involved in or precede cascades leading to neuroinflammatory processes. Due to their size, PVS are better detected on MRI at ultrahigh magnetic field strengths such as 7 Tesla, with improved sensitivity and resolution to quantify both concentration and size. As such, the objective of this prospective study was to leverage a semi-automated detection tool to identify and quantify differences in perivascular spaces between a group of 10 COVID-19 patients and a similar subset of controls to determine whether PVS might be biomarkers of COVID-19-mediated neuroinflammation. Results demonstrate a detectable difference in neuroinflammatory measures in the patient group compared to controls. PVS count and white matter volume were significantly different in the patient group compared to controls, yet there was no significant association between PVS count and symptom measures. Our findings suggest that the PVS count may be a viable marker for neuroinflammation in COVID-19, and other diseases which may be linked to neuroinflammatory processes.

AbstractIntroductionEmerging evidence in depression suggests that blood–brain barrier (BBB) breakdown and elevated inflammatory cytokines in states of persistent stress or trauma may contribute to the development of symptoms. Signal‐to‐noise ratio afforded by ultra‐high field MRI may aid in the detection of maladaptations of the glymphatic system related to BBB integrity that may not be visualized at lower field strengths.MethodsWe investigated the link between glymphatic neuroanatomy via perivascular spaces (PVS) and trauma experience in patients with major depressive disorder (MDD) and in healthy controls using 7‐Tesla MRI and a semi‐automated segmentation algorithm.ResultsAfter controlling for age and gender, the number of traumatic events was correlated with total PVS volume in MDD patients (r = 0.50, p = .028) and the overall population (r = 0.34, p = .024). The number of traumatic events eliciting horror was positively correlated with total PVS volume in MDD patients (r = 0.50, p = .030) and the overall population (r = 0.32, p = .023). Age correlated positively with PVS count, PVS total volume, and PVS density in all participants (r > 0.35, p < .01).ConclusionsThese results suggest a relationship between glymphatic dysfunction related to BBB integrity and psychological trauma, and that glymphatic impairment may play a role in trauma‐related symptomatology.

Insight into motivational processes may be gained by examining measures of willingness to exert effort for rewards, which have been linked to neuropsychiatric symptoms of anhedonia and apathy. However, while much work has focused on the development of models of motivation based on classic tasks of externally-generated levels of effort for reward, there has been less focus on the question of self-generated motivation or volition. We developed a task that aims to capture separate measures of self-generated and externally-generated motivation, with two task variants for physical and cognitive effort, and sought to test and validate this measure in two populations of healthy volunteers (N = 27 and N = 28). Similar to previous reports, a sigmoid function represented a better overall fit to the effort-reward data than a linear or Weibull model. Individual sigmoid function shapes were governed by two free parameters: bias (the amount of reward needed for effort initiation) and reward insensitivity (the amount of increase in reward needed to accelerate effort expenditure). For both physical and cognitive effort, bias was higher in the self-generated condition, indicating reduced self-generated volitional effort initiation, compared to externally-generated effort initiation, across effort domains. Bias against initial effort initiation in the self-generated condition was related to a specific dimensional measure of anticipatory anhedonia. For physical effort only, reward insensitivity was also higher in the self-generated condition compared to the externally-generated motivation condition, indicating lower self-generated effort acceleration. This work provides a novel objective measure of self-generated motivation that may provide insights into mechanisms of anhedonia and related symptoms.

Summary Objective In this study, we validate and describe a user-friendly tool for PVS tracing that uses a Frangi-based detection algorithm; which will be made freely available to aid in future clinical and research applications. All PVS detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset. Methods We deployed a Frangi-based filter using a pre-existing Matlab toolbox. The PVSSAS tool pre-processes the images and is optimized for maximum effectiveness in this application. A user-friendly GUI was developed to aid the speed and ease in marking large numbers of PVS across the entire brain at once. Results Using a tolerance of 0.7 cm, 83% of all PVSs detected by the semi-automated method had a match with the manual dataset and 94% of the manual PVS had a match within the semi-automated dataset. As shown in figure 3, there was generally excellent agreement between the manual and semi-automated markings in any given slice. Significance The primary benefit of PVSSAS will be time saved marking PVS. Clinical MRI use is likely to become more widespread in the diagnosis, treatment, and study of MS and other degenerative neurological conditions in the coming years. Tools like the one presented here will be invaluable in ensuring that the tracing and quantitative analysis of these PVS does not act as a bottle neck to treatment and further research.

The locus coeruleus (LC) has a long-established role in the attentional and arousal response to threat, and in the emergence of pathological anxiety in pre-clinical models. However, human evidence of links between LC function and pathological anxiety has been restricted by limitations in discerning LC with current neuroimaging techniques. We combined ultra-high field 7-Tesla and 0.4 x 0.4 x 0.5 mm quantitative MR imaging with a computational LC localization and segmentation algorithm to delineate the LC in 29 human subjects including subjects with and without an anxiety or stress-related disorder. Our automated, data-driven LC segmentation algorithm provided LC delineations that corresponded well with postmortem anatomic definitions of the LC. There was variation of LC size in healthy subjects (125.7 +/- 59.3 mm(3)), which recapitulates histological reports. Patients with an anxiety or stress-related disorder had larger LC compared to controls (Cohen's d = 1.08, p = 0.024). Larger LC was additionally associated with poorer attentional and inhibitory control and higher anxious arousal (FDR-corrected p's < 0.025), trans-diagnostically across the full sample. This study combined high-resolution and quantitative MR with a mixture of supervised and unsupervised computational techniques to provide robust, sub-millimeter measurements of the LC in vivo, which were additionally related to common psychopathology. This work has wide-reaching applications for a range of neurological and psychiatric disorders characterized by expected LC dysfunction.

The locus coeruleus (LC), a small set of bilateral norepinephrine -neuron containing nuclei located in the brainstem pons, has an established role in the normal attentional and arousal responses to threat and has long been implicated in the emergence of pathological anxiety and hyper-arousal in pre-clinical models. However, human evidence of links between LC dysfunction and pathological anxiety has been restricted by limitations in discerning LC with current neuroimaging techniques.