High-fidelity intravoxel incoherent motion parameter mapping using locally low-rank and subspace modeling.

PURPOSE: Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods. METHODS: To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise. RESULTS: Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction. CONCLUSION: The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.

Brain elastography in aging relates to fluid/solid trendlines.

The relatively new tools of brain elastography have established a general trendline for healthy, aging adult humans, whereby the brain's viscoelastic properties 'soften' over many decades. Earlier studies of the aging brain have demonstrated a wide spectrum of changes in morphology and composition towards the later decades of lifespan. This leads to a major question of causal mechanisms: of the many changes documented in structure and composition of the aging brain, which ones drive the long term trendline for viscoelastic properties of grey matter and white matter? The issue is important for illuminating which factors brain elastography is sensitive to, defining its unique role for study of the brain and clinical diagnoses of neurological disease and injury. We address these issues by examining trendlines in aging from our elastography data, also utilizing data from an earlier landmark study of brain composition, and from a biophysics model that captures the multiscale biphasic (fluid/solid) structure of the brain. Taken together, these imply that long term changes in extracellular water in the glymphatic system of the brain along with a decline in the extracellular matrix have a profound effect on the measured viscoelastic properties. Specifically, the trendlines indicate that water tends to replace solid fraction as a function of age, then grey matter stiffness decreases inversely as water fraction squared, whereas white matter stiffness declines inversely as water fraction to the 2/3 power, a behavior consistent with the cylindrical shape of the axons. These unique behaviors point to elastography of the brain as an important macroscopic measure of underlying microscopic structural change, with direct implications for clinical studies of aging, disease, and injury.

Brain white matter pathways of resilience to chronic back pain: a multisite validation.

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have shown that brain characteristics can serve as robust predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over six- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~ 0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.

Diffusion-Weighted Imaging Reveals Impaired Glymphatic Clearance in Idiopathic Intracranial Hypertension.

BACKGROUND AND PURPOSE: The pathophysiology underlying idiopathic intracranial hypertension (IIH) remains incompletely understood. While one theory postulates impaired cerebral glymphatic clearance in IIH, there is a paucity of methods to quantify glymphatic activity in human brains. The purpose of this study was to use advanced diffusion-weighed imaging to evaluate the glymphatic clearance of IIH patients and how it may relate to clinical severity. MATERIALS AND METHODS: DWI was used to separately evaluate the diffusivity along the cerebral perivascular spaces and lateral association and projection fibers, with the degree of diffusivity used as a surrogate for glymphatic function (diffusion tensor image analysis along the perivascular space. Patients with IIH were compared with normal controls. Glymphatic clearance was correlated with several clinical metrics, including lumbar puncture opening pressure and Frisen papilledema grade (low grade: 0-2; high grade: 3-5). RESULTS: In total, 99 patients with IIH were identified and compared with 6 healthy controls. Overall, patients with IIH had significantly lower glymphatic clearance based on DWI-derived diffusivity compared with controls (P = .005). Additionally, in patients with IIH, there was a significant association between declining glymphatic clearance and increasing Frisen papilledema grade (P = .046) but no correlation between opening pressure and glymphatic clearance (P = .27). Furthermore, healthy controls had significantly higher glymphatic clearance compared with patients with IIH and low-grade papilledema (P = .015) and high-grade papilledema (P = .002). Lastly, patients with IIH and high-grade papilledema had lower glymphatic clearance compared with patients with IIH and low-grade papilledema (P = .005). CONCLUSIONS: Patients with IIH possess impaired glymphatic clearance, which is directly related to the extent of clinical severity. The DWI-derived parameters can be used for clinical diagnosis or to assess response to treatment.

Association of Radiation Dose to the Amygdala-Orbitofrontal Network with Emotion Recognition Task Performance in Patients with Low-Grade and Benign Brain Tumors.

BACKGROUND: Although data are limited, difficulty in social cognition occurs in up to 83% of patients with brain tumors. It is unknown whether cranial radiation therapy (RT) dose to the amygdala-orbitofrontal network can impact social cognition. METHODS: We prospectively enrolled 51 patients with low-grade and benign brain tumors planned for cranial RT. We assessed longitudinal changes on an emotion recognition task (ERT) that measures the ability to recognize emotional states by displaying faces expressing six basic emotions and their association with the RT dose to the amygdala-orbitofrontal network. ERT outcomes included the median time to choose a response (ERTOMDRT) or correct response (ERTOMDCRT) and total correct responses (ERTHH). RESULTS: The RT dose to the amygdala-orbitofrontal network was significantly associated with longer median response times on the ERT. Increases in median response times occurred at lower doses than decreases in total correct responses. The medial orbitofrontal cortex was the most important variable on regression trees predicting change in the ERTOMDCRT. DISCUSSION: This is, to our knowledge, the first study to show that off-target RT dose to the amygdala-orbitofrontal network is associated with performance on a social cognition task, a facet of cognition that has previously not been mechanistically studied after cranial RT.

Correlations Between Quantitative EEG Parameters and Cortical Blood Flow in Patients Undergoing Extracorporeal Membrane Oxygenation With and Without Encephalopathy.

PURPOSE: The neurologic examination of patients undergoing extracorporeal membrane oxygenation (ECMO) is crucial for evaluating irreversible encephalopathy but is often obscured by sedation or neuromuscular blockade. Noninvasive neuromonitoring modalities including diffuse correlation spectroscopy and EEG measure cerebral perfusion and neuronal function, respectively. We hypothesized that encephalopathic ECMO patients with greater degree of irreversible cerebral injury demonstrate less correlation between electrographic activity and cerebral perfusion than those whose encephalopathy is attributable to medications. METHODS: We performed a prospective observational study of adults undergoing ECMO who underwent simultaneous continuous EEG and diffuse correlation spectroscopy monitoring. (Alpha + beta)/delta ratio and alpha/delta Rartio derived from quantitative EEG analysis were correlated with frontal cortical blood flow index. Patients who awakened and followed commands during sedation pauses were included in group 1, whereas patients who could not follow commands for most neuromonitoring were placed in group 2. (Alpha + beta)/delta ratio-blood flow index and ADR-BFI correlations were compared between the groups. RESULTS: Ten patients (five in each group) underwent 39 concomitant continuous EEG and diffuse correlation spectroscopy monitoring sessions. Four patients (80%) in each group received some form of analgosedation during neuromonitoring. (Alpha + beta)/delta ratio-blood flow index correlation was significantly lower in group 2 than group 1 (left: 0.05 vs. 0.52, P = 0.03; right: -0.12 vs. 0.39, P = 0.04). Group 2 ADR-BFI correlation was lower only over the right hemisphere (-0.06 vs. 0.47, P = 0.04). CONCLUSIONS: Correlation between (alpha + beta)/delta ratio and blood flow index were decreased in encephalopathic ECMO patients compared with awake ones, regardless of the analgosedation use. The combined use of EEG and diffuse correlation spectroscopy may have utility in monitoring cerebral function in ECMO patients.

Heart rate and autonomic biomarkers distinguish convulsive epileptic vs. functional or dissociative seizures.

OBJECTIVE: 20-40% of individuals whose seizures are not controlled by anti-seizure medications exhibit manifestations comparable to epileptic seizures (ES), but there are no EEG correlates. These events are called functional or dissociative seizures (FDS). Due to limited access to EEG-monitoring and inconclusive results, we aimed to develop an alternative diagnostic tool that distinguishes ES vs. FDS. We evaluated the temporal evolution of ECG-based measures of autonomic function (heart rate variability, HRV) to determine whether they distinguish ES vs. FDS. METHODS: The prospective study includes patients admitted to the University of Rochester Epilepsy Monitoring Unit. Participants are 18-65 years old, without therapies or co-morbidities associated with altered autonomics. A habitual ES or FDS is recorded during admission. HRV analysis is performed to evaluate the temporal changes in autonomic function during the peri­ictal period (150-minutes each pre-/post-ictal). We determined if autonomic measures distinguish ES vs. FDS. RESULTS: The study includes 53 ES and 46 FDS. Temporal evolution of HR and autonomics significantly differ surrounding ES vs. FDS. The pre-to-post-ictal change (delta) in HR differs surrounding ES vs. FDS, stratified for convulsive and non-convulsive events. Post-ictal HR, total autonomic (SDNN & Total Power), vagal (RMSSD & HF), and baroreflex (LF) function differ for convulsive ES vs. convulsive FDS. HR distinguishes non-convulsive ES vs. non-convulsive FDS with ROC>0.7, sensitivity>70%, but specificity<50%. HR-delta and post-ictal HR, SDNN, RMSSD, LF, HF, and Total Power each distinguish convulsive ES vs. convulsive FDS (ROC, 0.83-0.98). Models with HR-delta and post-ictal HR provide the highest diagnostic accuracy for convulsive ES vs. convulsive FDS: 92% sensitivity, 94% specificity, ROC 0.99). SIGNIFICANCE: HR and HRV measures accurately distinguish convulsive, but not non-convulsive, events (ES vs. FDS). Results establish the framework for future studies to apply this diagnostic tool to more heterogeneous populations, and on out-of-hospital recordings, particularly for populations without access to epilepsy monitoring units.

Initiation of combined antiretroviral therapy confers suboptimal beneficial effects on neurovascular function in people with HIV.

Introduction: Due to advances in combined anti-retroviral treatment (cART), there is an increased burden of age-related cerebrovascular disease (CBVD), in people living with HIV (PWH). The underlying CNS injury can be assessed by measuring cerebral blood flow (CBF) and cerebrovascular reactivity (CVR). Methods: 35 treatment-naïve PWH and 53 HIV negative controls (HC) were enrolled in this study. Study participants underwent T1-weighted anatomical, pseudo-continuous arterial spin labeling, and resting-state functional MRI to obtain measures of CBF and CVR prior to starting cART treatment and at two-time points (12 weeks and 2 years) post-cART initiation. Controls were scanned at the baseline and 2-year visits. We also measured plasma levels of microparticles of endothelial and glial origin and well-known endothelial inflammation markers, ICAM-1 and VCAM-1, to assess HIV-associated endothelial inflammation and the interaction of these peripheral markers with brain neurovascular function. Results: HIV infection was found to be associated with reduced CVR and increased levels of endothelial and glial microparticles (MPs) prior to initiation of cART. Further, CVR correlated negatively with peripheral MP levels in PWH. Discussion: Our results suggest that while cART treatment has a beneficial effect on the neurovascular function after initiation, these benefits are suboptimal over time.

Validation of deep learning techniques for quality augmentation in diffusion MRI for clinical studies.

The objective of this study is to evaluate the efficacy of deep learning (DL) techniques in improving the quality of diffusion MRI (dMRI) data in clinical applications. The study aims to determine whether the use of artificial intelligence (AI) methods in medical images may result in the loss of critical clinical information and/or the appearance of false information. To assess this, the focus was on the angular resolution of dMRI and a clinical trial was conducted on migraine, specifically between episodic and chronic migraine patients. The number of gradient directions had an impact on white matter analysis results, with statistically significant differences between groups being drastically reduced when using 21 gradient directions instead of the original 61. Fourteen teams from different institutions were tasked to use DL to enhance three diffusion metrics (FA, AD and MD) calculated from data acquired with 21 gradient directions and a b-value of 1000 s/mm2. The goal was to produce results that were comparable to those calculated from 61 gradient directions. The results were evaluated using both standard image quality metrics and Tract-Based Spatial Statistics (TBSS) to compare episodic and chronic migraine patients. The study results suggest that while most DL techniques improved the ability to detect statistical differences between groups, they also led to an increase in false positive. The results showed that there was a constant growth rate of false positives linearly proportional to the new true positives, which highlights the risk of generalization of AI-based tasks when assessing diverse clinical cohorts and training using data from a single group. The methods also showed divergent performance when replicating the original distribution of the data and some exhibited significant bias. In conclusion, extreme caution should be exercised when using AI methods for harmonization or synthesis in clinical studies when processing heterogeneous data in clinical studies, as important information may be altered, even when global metrics such as structural similarity or peak signal-to-noise ratio appear to suggest otherwise.

Artificial intelligence for diffusion MRI-based tissue microstructure estimation in the human brain: an overview.

Artificial intelligence (AI) has made significant advances in the field of diffusion magnetic resonance imaging (dMRI) and other neuroimaging modalities. These techniques have been applied to various areas such as image reconstruction, denoising, detecting and removing artifacts, segmentation, tissue microstructure modeling, brain connectivity analysis, and diagnosis support. State-of-the-art AI algorithms have the potential to leverage optimization techniques in dMRI to advance sensitivity and inference through biophysical models. While the use of AI in brain microstructures has the potential to revolutionize the way we study the brain and understand brain disorders, we need to be aware of the pitfalls and emerging best practices that can further advance this field. Additionally, since dMRI scans rely on sampling of the q-space geometry, it leaves room for creativity in data engineering in such a way that it maximizes the prior inference. Utilization of the inherent geometry has been shown to improve general inference quality and might be more reliable in identifying pathological differences. We acknowledge and classify AI-based approaches for dMRI using these unifying characteristics. This article also highlighted and reviewed general practices and pitfalls involving tissue microstructure estimation through data-driven techniques and provided directions for building on them.

Monocyte-derived Dll4 is a novel contributor to persistent systemic inflammation in HIV patients.

Background: In people living with HIV (PLWH) on combination antiretroviral therapy (cART), persistent systemic inflammation is a driving force for the progression of comorbidities, such as cardiovascular and cerebrovascular diseases. In this context, monocyte- and macrophage-related inflammation rather than T cell activation is a major cause of chronic inflammation. However, the underlying mechanism of how monocytes cause persistent systemic inflammation in PLWH is elusive. Methods and Results: In vitro, we demonstrated that lipopolysaccharides (LPS) or tumor necrosis factor alpha (TNFα), induced a robust increase of Delta-like ligand 4 (Dll4) mRNA and protein expression in human monocytes and Dll4 secretion (extracellular Dll4, exDll4) from monocytes. Enhanced membrane-bound Dll4 (mDll4) expression in monocytes triggered Notch1 activation to promote pro-inflammatory factors expression. Dll4 silencing and inhibition of Nocth1 activation diminished the LPS or TNFα -induced inflammation. exDll4 releases in response to cytokines occurred in monocytes but not endothelial cells or T cells. In clinical specimens, we found that PLWH, both male and female, on cART, showed a significant increase in mDll4 expression, activation of Dll4-Notch1 signaling, and inflammatory markers in monocytes. Although there was no sex effect on mDII4 in PLWH, plasma exDll4 was significantly elevated in males but not females compared to HIV uninfected individuals. Furthermore, exDll4 plasma levels paralleled with monocytes mDll4 in male PLWH. Circulating exDll4 was also positively associated with pro-inflammatory monocytes phenotype and negatively associated with classic monocytes phenotype in male PLWH. Conclusion: Pro-inflammatory stimuli increase Dll4 expression and Dll4-Notch1 signaling activation in monocytes and enhance monocyte proinflammatory phenotype, contributing to persistent systemic inflammation in male and female PLWH. Therefore, monocyte mDll4 could be a potential biomarker and therapeutic target of systemic inflammation. Plasma exDll4 may also play an additional role in systemic inflammation but primarily in men.

Role of non-classical monocytes in HIV-associated vascular cognitive impairment.

Despite antiretroviral treatment (cART), people living with HIV (PLWH) are more susceptible to neurocognitive impairment (NCI), probably due to synergistic/additive contribution of traditional cerebrovascular risk factors. Specifically, altered blood brain barrier (BBB) and transmigration of inflammatory monocytes are risk factors for developing cerebral small vessel disease (CSVD). In order to investigate if inflammatory monocytes exacerbate CSVD and cognitive impairment, 110 PLWH on cART and 110 age-, sex- and Reynold’s cardiovascular risk score-matched uninfected individuals were enrolled. Neuropsychological testing, brain magnetic resonance imaging and whole blood analyses to measure platelet-monocyte interaction and monocyte, endothelial activation were performed. Results demonstrated that PLWH exhibited increased levels of platelet-monocyte complexes (PMCs) and higher expression of activation molecules on PMCs. PLWH with CSVD had the poorest cognitive performance and the highest circulating levels of non-classical monocytes which exhibited significant inverse correlation with each other. Furthermore, markers of monocyte and endothelium activation were significantly positively correlated indicating BBB impairment. Our results confirm that interaction with platelets activates and drives monocytes towards an inflammatory phenotype in PLWH. In particular, elevated levels of non-classical monocytes may represent a common pathway to neuroinflammation, CSVD and subsequent cognitive impairment, warranting further longitudinal studies to evaluate responsiveness of this potential biomarker.

Cognitive and neuroimaging outcomes in individuals with benign and low-grade brain tumours receiving radiotherapy: a protocol for a prospective cohort study.

INTRODUCTION: Radiation-induced cognitive decline (RICD) occurs in 50%-90% of adult patients 6 months post-treatment. In patients with low-grade and benign tumours with long expected survival, this is of paramount importance. Despite advances in radiation therapy (RT) treatment delivery, better understanding of structures important for RICD is necessary to improve cognitive outcomes. We hypothesise that RT may affect network topology and microstructural integrity on MRI prior to any gross anatomical or apparent cognitive changes. In this longitudinal cohort study, we aim to determine the effects of RT on brain structural and functional integrity and cognition. METHODS AND ANALYSIS: This study will enroll patients with benign and low-grade brain tumours receiving partial brain radiotherapy. Patients will receive either hypofractionated (>2 Gy/fraction) or conventionally fractionated (1.8-2 Gy/fraction) RT. All participants will be followed for 12 months, with MRIs conducted pre-RT and 6-month and 12 month post-RT, along with a battery of neurocognitive tests and questionnaires. The study was initiated in late 2018 and will continue enrolling through 2024 with final follow-ups completing in 2025. The neurocognitive battery assesses visual and verbal memory, attention, executive function, processing speed and emotional cognition. MRI protocols incorporate diffusion tensor imaging and resting state fMRI to assess structural connectivity and functional connectivity, respectively. We will estimate the association between radiation dose, imaging metrics and cognitive outcomes. ETHICS AND DISSEMINATION: This study has been approved by the Research Subjects Review Board at the University of Rochester (STUDY00001512: Cognitive changes in patients receiving partial brain radiation). All results will be published in peer-reviewed journals and at scientific conferences. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT04390906.

Brain iron imaging markers in the presence of white matter hyperintensities.

PURPOSE: To investigate the relationship between pathological brain iron deposition and white matter hyperintensities (WMHs) in cerebral small vessel disease (CSVD), via Monte Carlo simulations of magnetic susceptibility imaging and the development of a novel imaging marker called the Expected Iron Coefficient (EIC). METHODS: A synthetic pathological model of a different number of impenetrable spheres at random locations was employed to represent pathological iron deposition. The diffusion process was simulated with a Monte Carlo method with adjustable parameters to manipulate sphere size, distribution, and extracellular properties. Quantitative susceptibility mapping (QSM) was performed in a clinical dataset to study CSVD to derive and evaluate QSM, R2*, the iron microenvironment coefficient (IMC), and the EIC in the presence of WMHs. RESULTS: The simulations show that QSM signals increase in the presence of increased tissue iron, confirming that the EIC increases with pathology. Clinical results demonstrate that while QSM, R2*, and the IMC do not show significant differences in brain iron, the EIC does in the context of CSVD. CONCLUSION: The EIC is more sensitive to subtle changes in brain iron deposition caused by pathology, even when QSM, R2*, and the IMC fail.

Longitudinal Effects of Combination Antiretroviral Therapy on Cognition and Neuroimaging Biomarkers in Treatment-Naive People With HIV.

BACKGROUND AND OBJECTIVES: While combination antiretroviral therapy (cART) has dramatically increased the life expectancy of people with HIV (PWH), nearly 50% develop HIV-associated neurocognitive disorders. This may be due to previously uncontrolled HIV viral replication, immune activation maintained by residual viral replication or activation from other sources, or cART-associated neurotoxicity. The aim of this study was to determine the effect of cART on cognition and neuroimaging biomarkers in PWH before and after initiation of cART compared with that in HIV-negative controls (HCs) and HIV elite controllers (ECs) who remain untreated. METHODS: We recruited 3 groups of participants from the University of Rochester, McGovern Medical School, and SUNY Upstate Medical University: (1) ART treatment-naive PWH; (2) age-matched HCs; and (3) ECs. Participants underwent brain MRI and clinical and neuropsychological assessments at baseline, 1 year, and 2 years. PWH were also assessed 12 weeks after initiating cART. Volumetric analysis and fractal dimensionality (FD) were calculated for cortical and subcortical regions. Mixed effect regressions examined the effect of group and imaging variables on cognition. RESULTS: We enrolled 47 PWH, 58 HCs, and 10 ECs. At baseline, PWH had worse cognition and lower cortical volumes than HCs. Cognition improved after initiation of cART and remained stable over time. Greater cortical thickness was associated with better cognition at baseline; greater FD of parietal, temporal, and occipital lobes was associated with better cognition at baseline and longitudinally. At baseline, ECs had worse cognition, lower cortical thickness, and lower FD in all 4 lobes and caudate than PWH and HCs. Greater cortical thickness, hippocampal volumes, and FD of frontal, temporal, and occipital lobes were associated with better cognition longitudinally. DISCUSSION: Initiation of cART in PWH is associated with improvement in brain structure and cognition. However, significant differences persist over time when compared with HCs. Similar trends in ECs suggest that results are due to HIV infection rather than treatment. Stronger associations between cognition and FD suggest this imaging metric may be a more sensitive marker of neuronal injury than cortical thickness and volumetric measures.

Longitudinal Cognitive Outcomes in Children With HIV in Zambia: 2-Year Outcomes From the HIV-Associated Neurocognitive Disorders in Zambia (HANDZ) Study.

OBJECTIVE: To describe longitudinal outcomes and predictors of cognitive outcomes in children with HIV in Zambia. BACKGROUND: Multiple studies have shown that children with HIV are at risk for impaired cognition. However, there are limited data on longitudinal cognitive outcomes in children with HIV. METHODS: We conducted a prospective cohort study of 208 perinatally infected children with HIV ages 8-17 years, all treated with antiretroviral therapy, and 208 HIV-exposed uninfected controls. Participants were followed for 2 years. Cognition was assessed with a custom NIH Toolbox Cognition Battery, and tests were combined to generate a Summary Cognition Score (SCS). The contribution of potential risk factors to outcomes was explored using regression models and group-based trajectory modeling. RESULTS: HIV was strongly associated with lower SCS at baseline [ß-14, 95% confidence interval (CI): -20 to -7, P < 0.001]. Change scores over time were similar between groups, but poorer average performance in children with HIV persisted at the 2-year follow-up visit (adjusted ß = -11, 95% CI: -22 to -0.3, P = 0.04). Other than HIV, the strongest predictors of baseline SCS included socioeconomic status index (ß =3, 95% CI: 1, 5, P = 0.004), history of growth stunting (ß=-14, 95% CI: -23 to -6, P = 0.001), history of CD4 count below 200 (ß = -19, 95% CI: -35 to -2, P = 0.02), and history of World Health Organization stage 4 disease (ß = -10, 95% CI: -19 to -0.2, P = 0.04). In the group-based trajectory model, HIV+ status predicted membership in the lowest performing trajectory group (odds ratio 2.5, 95% CI: 1.2 to 5.1, P = 0.01). CONCLUSIONS: Children with HIV are at risk of poor cognitive outcomes, despite chronic treatment with antiretroviral therapy.

Executable models of immune signaling pathways in HIV-associated atherosclerosis.

Atherosclerosis (AS)-associated cardiovascular disease is an important cause of mortality in an aging population of people living with HIV (PLWH). This elevated risk has been attributed to viral infection, anti-retroviral therapy, chronic inflammation, and lifestyle factors. However, the rates at which PLWH develop AS vary even after controlling for length of infection, treatment duration, and for lifestyle factors. To investigate the molecular signaling underlying this variation, we sequenced 9368 peripheral blood mononuclear cells (PBMCs) from eight PLWH, four of whom have atherosclerosis (AS+). Additionally, a publicly available dataset of PBMCs from persons before and after HIV infection was used to investigate the effect of acute HIV infection. To characterize dysregulation of pathways rather than just measuring enrichment, we developed the single-cell Boolean Omics Network Invariant Time Analysis (scBONITA) algorithm. scBONITA infers executable dynamic pathway models and performs a perturbation analysis to identify high impact genes. These dynamic models are used for pathway analysis and to map sequenced cells to characteristic signaling states (attractor analysis). scBONITA revealed that lipid signaling regulates cell migration into the vascular endothelium in AS+ PLWH. Pathways implicated included AGE-RAGE and PI3K-AKT signaling in CD8+ T cells, and glucagon and cAMP signaling pathways in monocytes. Attractor analysis with scBONITA facilitated the pathway-based characterization of cellular states in CD8+ T cells and monocytes. In this manner, we identify critical cell-type specific molecular mechanisms underlying HIV-associated atherosclerosis using a novel computational method.

Cerebral Blood Flow Hemispheric Asymmetry in Comatose Adults Receiving Extracorporeal Membrane Oxygenation.

Peripheral veno-arterial extracorporeal membrane oxygenation (ECMO) artificially oxygenates and circulates blood retrograde from the femoral artery, potentially exposing the brain to asymmetric perfusion. Though ECMO patients frequently experience brain injury, neurologic exams and imaging are difficult to obtain. Diffuse correlation spectroscopy (DCS) non-invasively measures relative cerebral blood flow (rBF) at the bedside using an optical probe on each side of the forehead. In this study we observed interhemispheric rBF differences in response to mean arterial pressure (MAP) changes in adult ECMO recipients. We recruited 13 subjects aged 21-78 years (7 with cardiac arrest, 4 with acute heart failure, and 2 with acute respiratory distress syndrome). They were dichotomized via Glasgow Coma Scale Motor score (GCS-M) into comatose (GCS-M ≤ 4; n = 4) and non-comatose (GCS-M > 4; n = 9) groups. Comatose patients had greater interhemispheric rBF asymmetry (ASYMrBF) vs. non-comatose patients over a range of MAP values (29 vs. 11%, p = 0.009). ASYMrBF in comatose patients resolved near a MAP range of 70-80 mmHg, while rBF remained symmetric through a wider MAP range in non-comatose patients. Correlations between post-oxygenator pCO2 or pH vs. ASYMrBF were significantly different between comatose and non-comatose groups. Our findings indicate that comatose patients are more likely to have asymmetric cerebral perfusion.

Single-shell NODDI using dictionary-learner-estimated isotropic volume fraction.

Neurite orientation dispersion and density imaging (NODDI) enables the assessment of intracellular, extracellular, and free water signals from multi-shell diffusion MRI data. It is an insightful approach to characterize brain tissue microstructure. Single-shell reconstruction for NODDI parameters has been discouraged in previous studies caused by failure when fitting, especially for the neurite density index (NDI). Here, we investigated the possibility of creating robust NODDI parameter maps with single-shell data, using the isotropic volume fraction (fISO ) as a prior. Prior estimation was made independent of the NODDI model constraint using a dictionary learning approach. First, we used a stochastic sparse dictionary-based network (DictNet), which is trained with data obtained from in vivo and simulated diffusion MRI data, to predict fISO . In single-shell cases, the mean diffusivity and raw T2 signal with no diffusion weighting (S0 ) was incorporated in the dictionary for the fISO estimation. Then, the NODDI framework was used with the known fISO to estimate the NDI and orientation dispersion index (ODI). The fISO estimated using our model was compared with other fISO estimators in the simulation. Further, using both synthetic data simulation and human data collected on a 3 T scanner (both high-quality HCP and clinical dataset), we compared the performance of our dictionary-based learning prior NODDI (DLpN) with the original NODDI for both single-shell and multi-shell data. Our results suggest that DLpN-derived NDI and ODI parameters for single-shell protocols are comparable with original multi-shell NODDI, and the protocol with b = 2000 s/mm2 performs the best (error ~ 5% in white and gray matter). This may allow NODDI evaluation of studies on single-shell data by multi-shell scanning of two subjects for DictNet fISO training.