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Abstract Autism spectrum disorder (ASD) is diagnosed using comprehensive behavioral information. Neuroimaging offers additional information but lacks clinical utility for diagnosis. This study investigates whether multi-forms of magnetic resonance imaging (MRI) contrast can be used individually and in combination to produce a categorical classification of young individuals with ASD. MRI data were accessed from the Autism Brain Imaging Data Exchange (ABIDE). Young participants (ages 2–30) were selected, and two group cohorts consisted of 702 participants: 351 ASD and 351 controls. Image-based classification was performed using one-channel and two-channel inputs to 3D-DenseNet deep learning networks. The models were trained and tested using tenfold cross-validation. Two-channel models were twinned with combinations of structural MRI (sMRI) maps and amplitude of low-frequency fluctuations (ALFF) or fractional ALFF (fALFF) maps from resting-state functional MRI (rs-fMRI). All models produced classification accuracy that exceeded 65.1%. The two-channel ALFF-sMRI model achieved the highest mean accuracy of 76.9% ± 2.34. The one-channel ALFF-based model alone had mean accuracy of 72% ± 3.1. This study leveraged the ABIDE dataset to produce ASD classification results that are comparable and/or exceed literature values. The deep learning approach was conducive to diverse neuroimaging inputs. Findings reveal that the ALFF-sMRI two-channel model outperformed all others.

Abstract Background Major depressive disorder (MDD) is a leading cause of disability worldwide across domains of health and cognition, affecting overall quality of life. Approximately one third of individuals with depression do not fully respond to treatments (e.g., conventional antidepressants, psychotherapy) and alternative strategies are needed. Recent early phase trials suggest psilocybin may be a safe and efficacious intervention with rapid-acting antidepressant properties. Psilocybin is thought to exert therapeutic benefits by altering brain network connectivity and inducing neuroplastic changes that endure for weeks post-treatment. Although early clinical results are encouraging, psilocybin’s acute neurobiological effects on neuroplasticity have not been fully investigated. We aim to examine for the first time how psilocybin acutely (intraday) and subacutely (weeks) alters functional brain networks implicated in depression. Methods Fifty participants diagnosed with MDD or persistent depressive disorder (PDD) will be recruited from a tertiary mood disorders clinic and undergo 1:1 randomization into either an experimental or control arm. Participants will be given either 25 mg psilocybin or 25 mg microcrystalline cellulose (MCC) placebo for the first treatment. Three weeks later, those in the control arm will transition to receiving 25 mg psilocybin. We will investigate whether treatments are associated with changes in arterial spin labelling and blood oxygenation level-dependent contrast neuroimaging assessments at acute and subacute timepoints. Primary outcomes include testing whether psilocybin demonstrates acute changes in (1) cerebral blood flow and (2) functional brain activity in networks associated with mood regulation and depression when compared to placebo, along with changes in MADRS score over time compared to placebo. Secondary outcomes include changes across complementary clinical psychiatric, cognitive, and functional scales from baseline to final follow-up. Serum peripheral neurotrophic and inflammatory biomarkers will be collected at baseline and follow-up to examine relationships with clinical response, and neuroimaging measures. Discussion This study will investigate the acute and additive subacute neuroplastic effects of psilocybin on brain networks affected by depression using advanced serial neuroimaging methods. Results will improve our understanding of psilocybin’s antidepressant mechanisms versus placebo response and whether biological measures of brain function can provide early predictors of treatment response. Trial registration ClinicalTrials.gov Identifier: NCT06072898. Registered on 6 October 2023.

Abstract Background Mitochondrial dysfunction is implicated in the neuropathology of bipolar disorder (BD). Higher circulating cell-free mitochondrial DNA (ccf-mtDNA), generally reflecting poorer mitochondrial health, has been associated with greater symptoms severity in BD. The current study examines the association of serum ccf-mtDNA and brain structure in relation to youth BD. We hypothesized that higher ccf-mtDNA will be associated with measures of lower brain structure, particularly in the BD group. Methods Participants included 40 youth (BD, n = 19; Control group [CG], n = 21; aged 13–20 years). Serum ccf-mtDNA levels were assayed. T1-weighted brain images were acquired using 3T-MRI. Region of interest (ROI) analyses examined prefrontal cortex (PFC) and whole brain gray matter, alongside exploratory vertex-wise analyses. Analyses examined ccf-mtDNA main-effects and ccf-mtDNA-by-diagnosis interaction effects controlling for age, sex, and intracranial volume. Results There was no significant difference in ccf-mtDNA levels between BD and CG. In ROI analyses, higher ccf-mtDNA was associated with higher PFC surface area (SA) (β = 0.32 p

IntroductionPost-acute COVID syndrome (PACS) is a growing concern, given its impact on mental health and quality of life. However, its effects on cerebral white matter remain poorly understood, particularly in non-hospitalized cohorts. The goals of this cross-sectional, observational study were to examine (1) whether PACS was associated with distinct alterations in white matter microstructure, compared to symptom-matched non-COVID viral infection; and (2) whether microstructural alterations correlated with indices of post-COVID emotional health.MethodsData were collected for 54 symptomatic individuals who tested positive for COVID-19 (mean age 41 ± 12 yrs., 36 female) and 14 controls who tested negative for COVID-19 (mean age 41 ± 14 yrs., 8 female), with both groups assessed an average of 4–5 months after COVID testing. Diffusion magnetic resonance imaging data were collected, and emotional health was assessed via the NIH emotion toolbox, with summary scores indexing social satisfaction, well-being and negative affect.ResultsDespite similar symptoms, the COVID-19 group had reduced mean and axial diffusivity, along with increased mean kurtosis and neurite dispersion, in deep white matter. After adjusting for social satisfaction, higher levels of negative affect in the COVID-19 group were also correlated with increased mean kurtosis and reduced free water in white matter.DiscussionThese results provide preliminary evidence that indices of white matter microstructure distinguish PACS from symptomatic non-COVID infection. Moreover, white matter effects seen in PACS correlate with the severity of emotional sequelae, providing novel insights into this highly prevalent disorder.

Standard treatment of patients with glioblastoma includes surgical resection of the tumor. The extent of resection (EOR) achieved during surgery significantly impacts prognosis and is used to stratify patients in clinical trials. In this study, we developed a U-Net-based deep-learning model to segment contrast-enhancing tumor on post-operative MRI exams taken within 72 h of resection surgery and used these segmentations to classify the EOR as either maximal or submaximal. The model was trained on 122 multiparametric MRI scans from our institution and achieved a mean Dice score of 0.52 ± 0.03 on an external dataset (n = 248), a performance ­on par with the interrater agreement between expert annotators as reported in literature. We obtained an EOR classification precision/recall of 0.72/0.78 on the internal test dataset (n = 462) and 0.90/0.87 on the external dataset. Furthermore, Kaplan-Meier curves were used to compare the overall survival between patients with maximal and submaximal resection in the internal test dataset, as determined by either clinicians or the model. There was no significant difference between the survival predictions using the model's and clinical EOR classification. We find that the proposed segmentation model is capable of reliably classifying the EOR of glioblastoma tumors on early post-operative MRI scans. Moreover, we show that stratification of patients based on the model's predictions offers at least the same prognostic value as when done by clinicians.

Abstract There is a gap in knowledge regarding the polygenic underpinnings of brain anomalies observed in youth bipolar disorder (BD). This study examined the association of a polygenic risk score for BD (BD-PRS) with grey matter structure and white matter integrity in youth with and without BD. 113 participants were included in the analyses, including 78 participants with both T1-weighted and diffusion-weighted MRI images, 32 participants with T1-weighted images only, and 3 participants with diffusion-weighted images only. BD-PRS was calculated using PRS-CS-auto and was based on independent adult genome-wide summary statistics. Vertex- and voxel-wise analyses examined the associations of BD-PRS with grey matter metrics (cortical volume [CV], cortical surface area [CSA], cortical thickness [CTh]) and fractional anisotropy [FA] in the combined sample, and separately in BD and HC. In the combined sample of participants with T1-weighted images (n = 110, 66 BD, 44 HC), higher BD-PRS was associated with smaller grey matter metrics in frontal and temporal regions. In within-group analyses, higher BD-PRS was associated with lower CTh of frontal, temporal, and fusiform gyrus in BD, and with lower CV and CSA of superior frontal gyrus in HC. In the combined sample of participants with diffusion-weighted images (n = 81, 49 BD, 32 HC), higher BD-PRS was associated with lower FA in widespread white matter regions. In summary, BD-PRS calculated based on adult genetic data was negatively associated with grey matter structure and FA in youth in regions implicated in BD, which may suggest neuroimaging markers of vulnerability to BD. Future longitudinal studies are needed to examine whether BD-PRS predicts neurodevelopmental changes in BD vs. HC and its interaction with course of illness and long-term medication use.

Abstract Introduction Post‐acute coronavirus disease 2019 (COVID‐19) syndrome (PACS) is a growing concern, with headache being a particularly debilitating symptom with high prevalence. The long‐term effects of COVID‐19 and post‐COVID headache on brain function remain poorly understood, particularly among non‐hospitalized individuals. This study focused on the power‐law scaling behavior of functional brain dynamics, indexed by the Hurst exponent (H). This measure is suppressed during physiological and psychological distress and was thus hypothesized to be reduced in individuals with post‐COVID syndrome, with greatest reductions among those with persistent headache. Methods Resting‐state blood oxygenation level‐dependent (BOLD) functional magnetic resonance imaging data were collected for 57 individuals who had COVID‐19 (32 with no headache, 14 with ongoing headache, 11 recovered) and 17 controls who had cold and flu‐like symptoms but tested negative for COVID‐19. Individuals were assessed an average of 4–5 months after COVID testing, in a cross‐sectional, observational study design. Results No significant differences in H values were found between non‐headache COVID‐19 and control groups., while those with ongoing headache had significantly reduced H values, and those who had recovered from headache had elevated H values, relative to non‐headache groups. Effects were greatest in temporal, sensorimotor, and insular brain regions. Reduced H in these regions was also associated with decreased BOLD activity and local functional connectivity. Conclusions These findings provide new insights into the neurophysiological mechanisms that underlie persistent post‐COVID headache, with reduced BOLD scaling as a potential biomarker that is specific to this debilitating condition.

Background The exercise strategy that yields the greatest improvement in both cardiorespiratory fitness (V̇O2peak$$ \dot{\mathrm{V}}{\mathrm{O}}_{2\mathrm{peak}} $$) and walking capacity poststroke has not been determined. This study aimed to determine whether conventional moderate‐intensity continuous training (MICT) or high‐intensity interval training (HIIT) have different effects on V̇O2peak$$ \dot{\mathrm{V}}{\mathrm{O}}_{2\mathrm{peak}} $$ and 6‐minute walk distance (6MWD). Methods and Results In this 24‐week superiority trial, people with poststroke gait dysfunction were randomized to MICT (5 days/week) or HIIT (3 days/week with 2 days/week of MICT). MICT trained to target intensity at the ventilatory anaerobic threshold. HIIT trained at the maximal tolerable treadmill speed/grade using a novel program of 2 work‐to‐recovery protocols: 30:60 and 120:180 seconds. V̇O2 and heart rate was measured during performance of the exercise that was prescribed at 8 and 24 weeks for treatment fidelity. Main outcomes were change in V̇O2peak$$ \dot{\mathrm{V}}{\mathrm{O}}_{2\mathrm{peak}} $$ and 6MWD. Assessors were blinded to the treatment group for V̇O2peak$$ \dot{\mathrm{V}}{\mathrm{O}}_{2\mathrm{peak}} $$ but not 6MWD. Secondary outcomes were change in ventilatory anaerobic threshold, cognition, gait‐economy, 10‐meter gait‐velocity, balance, stair‐climb performance, strength, and quality‐of‐life. Among 47 participants randomized to either MICT (n=23) or HIIT (n=24) (mean age, 62±11 years; 81% men), 96% completed training. In intention‐to‐treat analysis, change in V̇O2peak$$ \dot{\mathrm{V}}{\mathrm{O}}_{2\mathrm{peak}} $$ for MICT versus HIIT was 2.4±2.7 versus 5.7±3.1 mL·kg−1·min−1 (mean difference, 3.2 [95% CI, 1.5–4.8]; P

IntroductionRadiological assessment is necessary to diagnose spontaneous intracerebral hemorrhage (ICH) and traumatic brain injury intracranial hemorrhage (TBI-bleed). Artificial intelligence (AI) deep learning tools provide a means for decision support. This study evaluates the hemorrhage segmentations produced from three-dimensional deep learning AI model that was developed using non-contrast computed tomography (CT) imaging data external to the current study.MethodsNon-contrast CT imaging data from 1263 patients were accessed across seven data sources (referred to as sites) in Norway and Sweden. Patients were included based on ICH, TBI-bleed, or mild TBI diagnosis. Initial non-contrast CT images were available for all participants. Hemorrhage location frequency maps were generated. The number of estimated haematoma clusters was correlated with the total haematoma volume. Ground truth expert annotations were available for one ICH site; hence, a comparison was made with the estimated haematoma volumes. Segmentation volume estimates were used in a receiver operator characteristics (ROC) analysis for all samples (i.e., bleed detected) and then specifically for one site with few TBI-bleed cases.ResultsThe hemorrhage frequency maps showed spatial patterns of estimated lesions consistent with ICH or TBI-bleed presentations. There was a positive correlation between the estimated number of clusters and total haematoma volume for each site (correlation range: 0.45–0.74; each p-value < 0.01) and evidence of ICH between-site differences. Relative to hand-drawn annotations for one ICH site, the VIOLA-AI segmentation mask achieved a median Dice Similarity Coefficient of 0.82 (interquartile range: 0.78 and 0.83), resulting in a small overestimate in the haematoma volume by a median of 0.47 mL (interquartile range: 0.04 and 1.75 mL). The bleed detection ROC analysis for the whole sample gave a high area-under-the-curve (AUC) of 0.92 (with sensitivity and specificity of 83.28% and 95.41%); however, when considering only the mild head injury site, the TBI-bleed detection gave an AUC of 0.70.DiscussionAn open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.

Abstract Background CACNA1C rs1006737 A allele, identified as a genetic risk variant for bipolar disorder (BD), is associated with anomalous functional connectivity in adults with and without BD. Studies have yet to investigate the association of CACNA1C rs1006737 with resting-state functional connectivity (rsFC) in youth BD. Methods Participants included 139 youth with BD-I, -II, or -not otherwise specified, ages 13–20 years, including 27 BD A-carriers, 41 BD non-carriers, 32 healthy controls (HC) A-carriers, and 39 HC non-carriers. Anterior cingulate cortex (ACC), amygdala, and orbitofrontal cortex (OFC) were examined as regions-of-interest in seed-to-voxel analyses. General linear models included main effects of diagnosis and rs1006737, and an interaction term, controlling for age, sex, and race. Results We observed a main effect of BD diagnosis on rsFC between the right amygdala and the right occipital pole (p = 0.02), and a main effect of rs1006737 genotypes on rsFC between the right OFC and bilateral occipital cortex (p

BackgroundConventional cerebrovascular reactivity (CVR) estimation has demonstrated that many brain diseases and/or conditions are associated with altered CVR. Despite the clinical potential of CVR, characterization of temporal features of a CVR challenge remains uncommon. This work is motivated by the need to develop CVR parameters that characterize individual temporal features of a CVR challenge.MethodsData were collected from 54 adults and recruited based on these criteria: (1) Alzheimer’s disease diagnosis or subcortical Vascular Cognitive Impairment, (2) sleep apnea, and (3) subjective cognitive impairment concerns. We investigated signal changes in blood oxygenation level dependent (BOLD) contrast images with respect to hypercapnic and normocapnic CVR transition periods during a gas manipulation paradigm. We developed a model-free, non-parametric CVR metric after considering a range of responses through simulations to characterize BOLD signal changes that occur when transitioning from normocapnia to hypercapnia. The non-parametric CVR measure was used to examine regional differences across the insula, hippocampus, thalamus, and centrum semiovale. We also examined the BOLD signal transition from hypercapnia back to normocapnia.ResultsWe found a linear association between isolated temporal features of successive CO2 challenges. Our study concluded that the transition rate from hypercapnia to normocapnia was significantly associated with the second CVR response across all regions of interest (p

Measurement(s) stroke lesion Technology Type(s) manual segmentation in ITK-SNAP Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment brain

IntroductionThe long-term impact of COVID-19 on brain function remains poorly understood, despite growing concern surrounding post-acute COVID-19 syndrome (PACS). The goal of this cross-sectional, observational study was to determine whether there are significant alterations in resting brain function among non-hospitalized individuals with PACS, compared to symptomatic individuals with non-COVID infection.MethodsData were collected for 51 individuals who tested positive for COVID-19 (mean age 41±12 yrs., 34 female) and 15 controls who had cold and flu-like symptoms but tested negative for COVID-19 (mean age 41±14 yrs., 9 female), with both groups assessed an average of 4-5 months after COVID testing. None of the participants had prior neurologic, psychiatric, or cardiovascular illness. Resting brain function was assessed via functional magnetic resonance imaging (fMRI), and self-reported symptoms were recorded.ResultsIndividuals with COVID-19 had lower temporal and subcortical functional connectivity relative to controls. A greater number of ongoing post-COVID symptoms was also associated with altered functional connectivity between temporal, parietal, occipital and subcortical regions.DiscussionThese results provide preliminary evidence that patterns of functional connectivity distinguish PACS from non-COVID infection and correlate with the severity of clinical outcome, providing novel insights into this highly prevalent disorder.

Abstract Background Encouraging upper limb use and increasing intensity of practice in rehabilitation are two important goals for optimizing upper limb recovery post stroke. Feedback from novel wearable sensors may influence practice behaviour to promote achieving these goals. A wearable sensor can potentially be used in conjunction with a virtually monitored home program for greater patient convenience, or due to restrictions that preclude in-person visits, such as COVID-19. This trial aims to (1) determine the efficacy of a virtual behaviour change program that relies on feedback from a custom wearable sensor to increase use and function of the upper limb post stroke; and (2) explore the experiences and perceptions of using a program coupled with wearable sensors to increase arm use from the perspective of people with stroke. Methods This mixed-methods study will utilize a prospective controlled trial with random allocation to immediate or 3-week delayed entry to determine the efficacy of a 3-week behaviour change program with a nested qualitative description study. The intervention, the Virtual Arm Boot Camp (V-ABC) features feedback from a wearable device, which is intended to increase upper limb use post stroke, as well as 6 virtual sessions with a therapist. Sixty-four adults within 1-year post stroke onset will be recruited from seven rehabilitation centres. All outcomes will be collected virtually. The primary outcome measure is upper limb use measured by grasp counts over 3 days from the wearable sensor (TENZR) after the 3-week intervention. Secondary outcomes include upper limb function (Arm Capacity and Movement Test) and self-reported function (Hand Function and Strength subscale from the Stroke Impact Scale). Outcome data will be collected at baseline, post-intervention and at 2 months retention. The qualitative component will explore the experiences and acceptability of using a home program with a wearable sensor for increasing arm use from the point of view of individuals with stroke. Semi-structured interviews will be conducted with participants after they have experienced the intervention. Qualitative data will be analysed using content analysis. Discussion This study will provide novel information regarding the efficacy and acceptability of virtually delivered programs to improve upper extremity recovery, and the use of wearable sensors to assist with behaviour change. Trial registration ClinicalTrials.gov NCT04232163 . January 18, 2020.

An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer’s disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models—one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed—were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining.

Abstract Background The Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog) is used to assess decline in memory, language, and praxis in Alzheimer's disease (AD). Methods A latent state–trait model with autoregressive effects was used to determine how much of the ADAS‐Cog item measurement was reliable, and of that, how much of the information was occasion specific (state) versus consistent (trait or accumulated from one visit to the next). Results Participants with mild AD (n = 341) were assessed four times over 24 months. Praxis items were generally unreliable as were some memory items. Language items were generally the most reliable, and this increased over time. Only two ADAS‐Cog items showed reliability >0.70 at all four assessments, word recall (memory) and naming (language). Of the reliable information, language items exhibited greater consistency (63.4% to 88.2%) than occasion specificity, and of the consistent information, language items tended to reflect effects of AD progression that accumulated from one visit to the next (35.5% to 45.3%). In contrast, reliable information from praxis items tended to come from trait information. The reliable information in the memory items reflected more consistent than occasion‐specific information, but they varied between items in the relative amounts of trait versus accumulated effects. Conclusions Although the ADAS‐Cog was designed to track cognitive decline, most items were unreliable, and each item captured different amounts of information related to occasion‐specific, trait, and accumulated effects of AD over time. These latent properties complicate the interpretation of trends seen in ordinary statistical analyses of trials and other clinical studies with repeated ADAS‐Cog item measures. Highlights Studies have described unfavorable psychometric properties of the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog), bringing into question its ability to track changes in cognition uniformly over time. There remains a need to estimate how much of the ADAS‐Cog measurement is reliable, of that how much is occasion specific versus consistent, and of the consistent information, how much represents enduring traits versus autoregressive effects (i.e., effects of Alzheimer's disease [AD] progression carried over from one assessment to the next). A latent state–trait model with autoregressive effects in mild AD found most items to be unreliable, and each item to capture different amounts of occasion‐specific, trait, and autoregressive information. Language items, specifically, naming and the memory item word recall, were the most reliable. Psychometric idiosyncrasies of individual items complicate the interpretation of their summed score, biasing ordinary statistical analyses of repeated measures in mild AD. Future studies should consider item trajectories individually.

The choroid plexus (ChP) of the cerebral ventricles is a source of cerebrospinal fluid (CSF) production and also plays a key role in immune surveillance at the level of blood-to-CSF-barrier (BCSFB). In this study, we quantify ChP blood perfusion and BCSFB mediated water exchange from arterial blood into ventricular CSF using non-invasive continuous arterial spin labelling magnetic resonance imaging (CASL-MRI). Systemic administration of anti-diuretic hormone (vasopressin) was used to validate BCSFB water flow as a metric of choroidal CSF secretory function. To further investigate the coupling between ChP blood perfusion and BCSFB water flow, we characterized the effects of two anesthetic regimens known to have large-scale differential effects on cerebral blood flow. For quantification of ChP blood perfusion a multi-compartment perfusion model was employed, and we discovered that partial volume correction improved measurement accuracy. Vasopressin significantly reduced both ChP blood perfusion and BCSFB water flow. ChP blood perfusion was significantly higher with pure isoflurane anesthesia (2-2.5%) when compared to a balanced anesthesia with dexmedetomidine and low-dose isoflurane (1.0 %), and significant correlation between ChP blood perfusion and BCSFB water flow was observed, however there was no significant difference in BCSFB water flow. In summary, here we introduce a non-invasive, robust, and spatially resolved in vivo imaging platform to quantify ChP blood perfusion as well as BCSFB water flow which can be applied to study coupling of these two key parameters in future clinical translational studies.

Research imaging in healthy and clinical youth populations yields incidental findings that require a management strategy. Our primary objective was to document the frequency and nature of incidental findings within a research group integrating multiple imaging modalities. A second objective was to describe the evolution of an approach to handling incidental findings. A case example was included to display the intricacies of some of these scenarios. Youth, ages 13–20 years, with bipolar disorder, familial risk for bipolar disorder, or healthy controls, obtained one or a combination of neuroimaging, cardio-thoracic imaging, retinal imaging, and carotid imaging. All images were systematically reviewed for incidental findings. Overall, of 223 participants (n = 102 healthy controls), 59% (n = 131) had a brain magnetic resonance imaging (MRI) incidental finding and 27% (n = 60) had at least one incidental brain finding requiring non-urgent follow-up. In addition, of 109 participants with chest/cardiac MRI and carotid ultrasound, 3% (n = 3) had chest findings, 2% (n = 2) had cardiac findings, and 1% (n = 1) had a carotid finding. Of 165 youth with retinal imaging, 1% (n = 2) had incidental findings. While the vast majority of these incidental findings were of a non-serious, non-urgent nature, there were noteworthy exceptions. Imaging research groups need a system that emphasizes the value of clinical review of research images and one that is collaborative and responsive in order to inform follow-up plans. Rating systems that have been developed and used in neuroimaging for the classification of incidental findings can be adapted for use in areas other than the brain. Regardless of severity, incidental findings may raise anxiety in youth participants and their parents. The optimal threshold is one that balances transparency with utility.

Background Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P

Objective: The increased prevalence rate of white matter hyperintensities is one of the most consistently reported brain abnormalities in adults with bipolar disorder. However, findings in children and adolescents with bipolar disorder are less consistent. Prior studies have been constrained by small sample sizes and/or poor age- and sex-matching of healthy controls. We examined this topic in the largest sample of adolescents with bipolar disorder to date. Methods: T2-weighted 3-Tesla magnetic resonance imaging data were acquired for 83 adolescents with bipolar disorder diagnosed via the Kiddie Schedule for Affective Disorders and the Schizophrenia, Present and Lifetime version semi-structured interview and 64 age- and sex-matched healthy controls. All acquired scans were examined by neuroradiologists and the presence or absence of white matter hyperintensities was determined for each participant. Results: The prevalence of white matter hyperintensities did not differ between adolescents with bipolar disorder (13.3%) and controls (21.9%; χ2 = 1.90; p = 0.168). Conclusion: In contrast to the study hypothesis, the prevalence of white matter hyperintensities was not higher in adolescents with bipolar disorder than controls. The large sample size and good matching for age and sex bolster the reliability of this negative finding. Future studies are warranted to evaluate the prevalence, incidence, and predictors of white matter hyperintensities in early-onset bipolar disorder prospectively.

Abstract Introduction Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. Methods Surveys, teleconferences, and an in‐person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. Results A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness‐neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. Conclusions The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Abstract Objectives Vascular‐brain associations are well established in adults but neglected in youth and psychiatric populations, who are at greater cardiovascular risk. We therefore examined the association of retinal vascular caliber with regional brain structure in adolescents with and without bipolar disorder (BD). Methods One hundred and three adolescents (n = 51 BD, n = 52 healthy control [HC]) completed retinal fundus imaging, yielding arteriolar and venular diameters, followed by T1‐weighted 3‐Tesla MRI. Region of interest (ROI) analyses examined ventrolateral prefrontal cortex (vlPFC) and ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), amygdala, and hippocampus, complemented by vertex‐wise analyses. Linear regression assessed the association between retinal measures and brain structure, adjusting for covariates including age, sex, BMI, and intracranial volume (ICV). Results In the overall sample, arteriolar caliber was negatively associated with ACC volume (β = −0.20, puncorrected = .046) and surface area (β = −0.19, puncorrected = .049). There were no other significant ROI findings. Vertex‐wise analyses detected several significant positive bilateral associations of arteriovenous ratio (AVR) with volume and surface area in regions including rostral middle frontal gyrus (left p = .001; right p = .006), isthmus cingulate cortex (left and right p

The Trail Making Test (TMT) is widely used to probe brain function and is performed with pen and paper, involving Parts A (linking numbers) and B (alternating between linking numbers and letters). The relationship between TMT performance and the underlying brain activity remains to be characterized in detail. Accordingly, sixteen healthy young adults performed the TMT using a touch-sensitive tablet to capture enhanced performance metrics, such as the speed of linking movements, during simultaneous electroencephalography (EEG). Linking and non-linking periods were derived as estimates of the time spent executing and preparing movements, respectively. The seconds per link (SPL) was also used to quantify TMT performance. A strong effect of TMT Part A and B was observed on the SPL value as expected (Part B showing increased SPL value); whereas the EEG results indicated robust effects of linking and non-linking periods in multiple frequency bands, and effects consistent with the underlying cognitive demands of the test.

Abstract Background Cardiovascular conditions contribute to brain volume loss, reduced cerebrovascular health, and increased dementia risk in aging adults. Altered hippocampal connectivity has also been observed in individuals with cardiovascular conditions, yet the functional consequences of these changes remain unclear. In the present study, we collected functional magnetic resonance imaging data during memory encoding and used a psychophysiological interaction analysis to examine whether cardiovascular burden, indexed using the Framingham risk score, was associated with encoding-related hippocampal connectivity and task performance in cognitively-intact older adults between 65 and 85 years of age. Our goal was to better understand the early functional consequences of vascular and metabolic dysfunction in those at risk for cognitive decline. Results High Framingham risk scores were associated with lower total brain volumes. In addition, those with high Framingham risk scores showed an altered relationship between left hippocampal-medial prefrontal coupling and task performance compared to those with low Framingham risk scores. Specifically, we found a significant interaction of Framingham risk and learning on connectivity between the left hippocampus and primarily left midline prefrontal regions comprising the left ventral anterior cingulate cortex and medial prefrontal cortex. Those with lower Framingham risk scores showed a pattern of weaker connectivity between left hippocampal and medial prefrontal regions associated with better task performance. Those with higher Framingham risk scores showed the opposite pattern; stronger connectivity was associated with better performance. Conclusions Findings from the current study show that amongst older adults with cardiovascular conditions, higher Framingham risk is associated with lower brain volume and altered left hippocampal-medial prefrontal coupling during task performance compared to those with lower Framingham risk scores. This may reflect a compensatory mechanism in support of memory function and suggests that older adults with elevated cardiovascular risk are vulnerable to early Alzheimer disease-like dysfunction within the episodic memory system.

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners.The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice.ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow.ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Introduction: Depressive symptoms predominate in the course of bipolar disorder (BD) and there is an urgent need to evaluate novel application of repurposed compounds that act on pre-specified treatment targets. Several lines of reasoning suggest that nitrous oxide (N2O) is an ideal medication to study as a potential treatment and as a strategy to identify the underlying pathophysiology of bipolar depression. N2O is a potent cerebral vasodilator and there is compelling evidence of reduced frontal cerebral blood flow (CBF; i.e. hypoperfusion) in depression. Therefore, N2O may increase CBF and thereby improve symptoms of depression. The goal of this randomized, double-blind trial is to study the effect of a single administration of N2O versus the active comparator midazolam on mood and CBF in adults with treatment-resistant bipolar depression. Methods: Participants with BD-I/-II currently experiencing a major depressive episode will be randomized to one of two conditions (n = 20/group): 1) inhaled N2O plus intravenous saline, or 2) inhaled room air plus intravenous midazolam. Montgomery-Asberg Depression Rating Scale scores will serve as the primary endpoint. CBF will be measured via arterial spin labelling magnetic resonance imaging. Conclusions: N2O is a potential novel treatment for bipolar depression, as it causes cerebral vasodilation. This proof-of-concept study will provide valuable information regarding the acute impact of N2O on mood and on CBF. If N2O proves to be efficacious in future larger-scale trials, its ubiquity, safety, low cost, and ease of use suggest that it has great potential to become a game-changing acute treatment for bipolar depression.

BackgroundGait deficits are associated with brain atrophy and white matter hyperintensities (WMH) – both markers of underlying cerebral small vessel disease (SVD). Given reduced subcortical cerebral blood flow (CBF) is prevalent in SVD, we tested the hypothesis that regional CBF is positively associated with gait performance among older adults.MethodsThirty-two older adults (55–80 years) with at least one vascular risk factor were recruited. We assessed gait during 2 consecutive walking sequences using a GAITRite system: (1) at a self-selected pace, and (2) while performing a serial subtraction dual-task challenge. We quantified CBF using pseudo-continuous arterial spin labeling MRI within 4 regions of interest: putamen, pallidum, thalamus, and hippocampus. We investigated associations between gait characteristics and overall CBF adjusting for age, sex, and height in an omnibus approach using multivariate analysis of variance, followed by regression analysis with each individual region. We also conducted further regression analyses to investigate associations between gait characteristics and frontal lobe CBF. Sensitivity analyses examined how the observed associations were modified by WMH, executive function, and depressive symptoms. A change of 10% in the model’s adjusted r2 and effect size was considered as a threshold for confounding.ResultsOverall subcortical CBF was not associated with self-paced gait. When examining individual ROI, gait velocity was directly related to thalamic CBF (p = 0.026), and across all gait variables the largest effect sizes were observed in relation to thalamic CBF. In the dual-task condition, gait variables were not related to CBF in either the omnibus approach or individual multiple regressions. Furthermore, no significant associations were observed between frontal CBF and gait variables in either the self-paced or dual-task condition. Sensitivity analyses which were restricted to examine the association of velocity and thalamic CBF identified a cofounding effect of depressive symptoms which increased the effect size of the CBF-gait association by 12%.ConclusionSubcortical hypoperfusion, particularly in regions that comprise central input/output tracts to the cortical tissue, may underlie the association between gait deficits and brain aging.

Introduction: This study investigated whether brain tissue pulsatility is associated with features of disease severity in Parkinson's disease (PD). Methods: Data were extracted from the Parkinson's Progression Markers Initiative among 81 adults with PD (confirmed with DATSCAN™). Brain tissue pulsatility was computed using resting state blood oxygenation level dependent (BOLD) MRI in white matter (WM), referred to as BOLDTP. Motor impairment was assessed using the Movement Disorders Society unified Parkinson's disease rating scale. Factor analysis generated composite scores for cognition and vascular risk burden. A linear regression model examined the association of BOLDTP with age, sex, motor impairment, cognition, vascular risk burden and PD duration. In addition, we investigated whether BOLDTP relates to WM hyperintensity (WMH) volume, WM fractional anisotropy (WM-FA) and striatal binding ratio (SBR) of dopamine transporter. Results: Motor impairment (t = 2.3, p = .02), vascular burden (t = 2.4, p = .02) and male sex (t = 3.0, p = .003) were independently associated with BOLDTP (r2 = 0.40, p .1). In addition, BOLDTP (t = 2.76, p = .008) and SBR (t = −2.04, p = .04) were independently related to motor impairment (r2 = 0.18, p = .006). Conclusion: Our findings show that brain tissue pulsatility from BOLD images in WM is related to neurological and vascular features in PD. BOLDTP may be useful in PD to study small vessel alterations that appear distinct from WM structural changes. Keywords: Brain tissue pulsatility, Parkinson's disease, White matter, Vascular risk factors, Blood oxygenation level dependent MRI

Knowledge gaps exist in how we implement aerobic exercise programs during the early phases post-stroke. Therefore, the objective of this review was to provide evidence-based guidelines for pre-participation screening, mobilization, and aerobic exercise training in the hyper-acute and acute phases post-stroke. In reviewing the literature to determine safe timelines of when to initiate exercise and mobilization we considered the following factors: arterial blood pressure dysregulation, cardiac complications, blood-brain barrier disruption, hemorrhagic stroke transformation, and ischemic penumbra viability. These stroke-related impairments could intensify with inappropriate mobilization/aerobic exercise, hence we deemed the integrity of cerebral autoregulation to be an essential physiological consideration to protect the brain when progressing exercise intensity. Pre-participation screening criteria are proposed and countermeasures to protect the brain from potentially adverse circulatory effects before, during, and following mobilization/exercise sessions are introduced. For example, prolonged periods of standing and static postures before and after mobilization/aerobic exercise may elicit blood pooling and/or trigger coagulation cascades and/or cerebral hypoperfusion. Countermeasures such as avoiding prolonged standing or incorporating periodic lower limb movement to activate the venous muscle pump could counteract blood pooling after an exercise session, minimize activation of the coagulation cascade, and mitigate potential cerebral hypoperfusion. We discuss patient safety in light of the complex nature of stroke presentations (i.e., type, severity, and etiology), medical history, comorbidities such as diabetes, cardiac manifestations, medications, and complications such as anemia and dehydration. The guidelines are easily incorporated into the care model, are low-risk, and use minimal resources. These and other strategies represent opportunities for improving the safety of the activity regimen offered to those in the early phases post-stroke. The timeline for initiating and progressing exercise/mobilization parameters are contingent on recovery stages both from neurobiological and cardiovascular perspectives, which to this point have not been specifically considered in practice. This review includes tailored exercise and mobilization prescription strategies and precautions that are not resource intensive and prioritize safety in stroke recovery.

Background: Regional cerebral blood flow (CBF) is reportedly altered in both adolescents and adults with bipolar disorder (BD). Whether these CBF differences are part of an overall imbalance in cerebral energy homeostasis remains unknown. Therefore, we examined global cerebral metabolic rate of oxygen consumption (CMRO2) as a physiological index of brain metabolism in adolescents with and without BD.Methods: One hundred and fifteen adolescents (mean age 17.3 ± 1.4 years), including 58 BD (type I, II, or not otherwise specified [NOS]) and 57 age-matched healthy controls (HCs) participated in this magnetic resonance imaging (MRI) study. Global estimates for venous blood oxygenation (Yv) and grey matter CBF were measured using T2-relaxation-under-spin-tagging (TRUST) and arterial spin labeling (ASL) MRI, respectively. CMRO2 was calculated using the Fick principle of arteriovenous difference to test for a group difference. We also examined CMRO2 in relation to mood states (i.e. euthymic, depressed, or hypomanic/mixed).Results: Although CBF was significantly higher in BD compared to HCs, there was no group difference in global CMRO2, nor Yv. Meanwhile, Yv significantly decreased with age, and females tended to have greater CBF and CMRO2 in comparison to males. Lastly, there was no significant association between CMRO2 and mood states.Conclusions: Our results indicate a potential mismatch between cerebral blood supply and oxygen metabolism in BD, suggesting inefficiency in energy homeostasis in the brain. Mapping CMRO2 would provide the spatial resolution to investigate regional alterations in metabolism, particularly in the brain regions where CBF is increased.

Cognitive decline is often undetectable in the early stages of accelerated vascular aging. Attentional processes are particularly affected in older adults with white matter hyperintensities (WMH), although specific neurovascular mechanisms have not been elucidated. We aimed to identify differences in attention-related neurofunctional activation and behavior between adults with and without WMH. Older adults with moderate to severe WMH (n = 18, mean age = 70 years), age-matched adults (n = 28, mean age = 72), and healthy younger adults (n = 19, mean age = 25) performed a modified flanker task during multi-echo blood oxygenation level dependent functional magnetic resonance imaging. Task-related activation was assessed using a weighted-echo approach. Healthy older adults had more widespread response and higher amplitude of activation compared to WMH adults in fronto-temporal and parietal cortices. Activation associated with processing speed was absent in the WMH group, suggesting attention-related activation deficits that may be a consequence of cerebral small vessel disease. WMH adults had greater executive contrast activation in the precuneous and posterior cingulate gyrus compared to HYA, despite no performance benefits, reinforcing the network dysfunction theory in WMH.

Background: Fatigue and depressive symptoms are common and often inter-related stroke sequelae. This study investigates how they are related, directly or indirectly, to mobility and cognitive outcomes within 6 months of stroke.Methods: Participants were recruited from 4 stroke centers in Ontario, Canada. Post-stroke fatigue was assessed using the Fatigue Assessment Scale (FAS). Depressive symptoms were screened using the Center for Epidemiological Studies Scale for Depression (CES-D). Factor analyses were used to construct scores from mobility (distance traveled during a 2-min walk test, Chedoke-McMaster Stroke Assessment leg score, and Berg Balance Scale total score) and cognitive (Montreal Cognitive Assessment, Trail-Making Tests A and B, and five-word free recall) tests. Direct associations were assessed in linear regression models and indirect effects were assessed in path models. Covariates were age, sex, education, antidepressant use, days since stroke, and stroke severity (National Institute of Health Stroke Severity Scale score).Results: Fatigue and depressive symptoms were highly correlated (r > 0.51, p < 0.0001). Depressive symptoms were associated with cognition (β = −0.184, p = 0.04) and indirectly with mobility, mediated by fatigue (indirect effect = −0.0142, 95% CI: −0.0277 to −0.0033). Fatigue was associated with mobility (β = −0.253, p = 0.01), and indirectly with cognition, mediated by depressive symptoms (indirect effect = −0.0113, 95% CI: −0.0242 to −0.0023).Conclusions: Fatigue and depressive symptoms are related distinctly to cognitive and mobility impairments post-stroke. Fatigue was associated with poorer lower limb motor function, and with cognition indirectly via depressive symptoms.

Exercise is increasingly recommended as an essential component of stroke rehabilitation, yet uncertainty remains with respect to its direct effect on the cerebral vasculature. The current study first demonstrated the repeatability of pseudo-continuous arterial spin labeling (ASL) magnetic resonance imaging (MRI) in older adults with stroke, and then investigated the change in cerebrovascular function following a 6-month cardiovascular rehabilitation program. In the repeatability study, 12 participants at least 3 months post-stroke underwent two ASL imaging scans 1 month apart. In the prospective observational study, eight individuals underwent ASL imaging and aerobic fitness testing before and after a 6-month cardiovascular rehabilitation program. Cerebral blood flow (CBF) and the spatial coefficient of variation of CBF (sCoV) were quantified to characterize tissue-level perfusion and large cerebral artery transit time properties, respectively. In repeat scanning, intraclass correlation (ICC) indicated moderate test-retest reliability for global gray matter CBF (ICC = 0.73) and excellent reliability for sCoV (ICC = 0.94). In the observational study, gray matter CBF increased after training (baseline: 40 ± 13 vs. 6-month: 46 ± 12 ml·100 g−1·min−1, P = 0.036). The greatest change occurred in the parietal lobe (+18 ± 12%). Gray matter sCoV, however, did not change following training (P = 0.31). This study provides preliminary evidence that exercise-based rehabilitation in chronic stroke enhances tissue-level perfusion, without changing the relative hemodynamic properties of the large cerebral arteries.

Objective: Type 2 diabetes mellitus is characterized by metabolic dysregulation in the form of hyperglycemia and insulin resistance and can have a profound impact on brain structure and vasculature. The primary aim of this study was to identify brain regions where the combined effects of type 2 diabetes and hypertension on brain health exceed those of hypertension alone. A secondary objective was to test whether vascular impairment and structural brain measures in this population are associated with cognitive function. Research design and methods: We enrolled 18 diabetic participants with hypertension (HTN + T2DM, 7 women, 71.8 ± 5.6 years) and 22 participants with hypertension only (HTN, 12 women, 73.4 ± 6.2 years). Cerebrovascular reactivity (CVR) was assessed using blood oxygenation level dependent (BOLD) MRI during successive breath holds. Gray matter structure was evaluated using cortical thickness (CThk) measures estimated from T1-weighted images. Analyses of cognitive and blood data were also performed. Results: Compared to HTN, HTN + T2DM had decreased CVR and CThk in a spatially overlapping region of the right occipital lobe (P 0.05), CThk in the right lingual gyrus ROI and regions resulting from a vertex-wise analysis (including posterior cingulate, precuneus, superior and middle frontal, and middle and inferior temporal regions (P