The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [18F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown. Here, using two multimodal datasets of healthy participants, we built a multivariable multilevel model of functional-metabolic associations, assessing multiple functional features, describing the 1) rs-fMRI signal, 2) hemodynamic response, 3) static and 4) time-varying functional connectivity, as predictors of the human brain's metabolic architecture. The full model was trained on one dataset and tested on the other to assess its reproducibility. We found that functional-metabolic spatial coupling is nonlinear and heterogeneous across the brain, and that local measures of rs-fMRI activity and synchrony are more tightly coupled to local metabolism. In the testing dataset, the degree of functional-metabolic spatial coupling was also related to peripheral metabolism. Overall, although a significant proportion of regional metabolic variability can be described by measures of spontaneous activity, additional efforts are needed to explain the remaining variance in the brain's 'dark energy'.

MRI-Based Brain Volume Scoring in Cerebral Malaria Is Externally Valid and Applicable to Lower-Resolution Images.

BACKGROUND AND PURPOSE: Children with cerebral malaria have an elevated risk of mortality and neurologic morbidity. Both mortality and morbidity are associated with initially increased brain volume on MR imaging, as graded by the Brain Volume Score, a subjective ordinal rating scale created specifically for brain MRIs in children with cerebral malaria. For the Brain Volume Score to be more widely clinically useful, we aimed to determine its independent reproducibility and whether it can be applicable to lower-resolution MRIs. MATERIALS AND METHODS: To assess the independent reproducibility of the Brain Volume Score, radiologists not associated with the initial study were trained to score MRIs from a new cohort of patients with cerebral malaria. These scores were then compared with survival and neurologic outcomes. To assess the applicability to lower-resolution MRI, we assigned Brain Volume Scores to brain MRIs degraded to simulate a very-low-field (64 mT) portable scanner and compared these with the original scores assigned to the original nondegraded MRIs. RESULTS: Brain Volume Scores on the new cohort of patients with cerebral malaria were highly associated with outcomes (OR for mortality = 16, P < .001). Scoring of the simulated degraded images remained consistent with the Brain Volume Scores assigned to the original higher-quality (0.35 T) images (intraclass coefficients > 0.86). CONCLUSIONS: Our findings demonstrate that the Brain Volume Score is externally valid in reproducibly predicting outcomes and can be reliably assigned to lower-resolution images.

Accuracy of TrUE-Net in comparison to established white matter hyperintensity segmentation methods: An independent validation study.

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the established relationship between WMH burden and age. We found that TrUE-Net was highly reliable at identifying WMH regions with low false positive rates, when compared to semi-manual segmentation as the reference standard. TrUE-Net performed similarly or favorably when compared to the other automated techniques. Moreover, TrUE-Net was able to detect relationships between WMH and age to a similar degree as the reference standard semi-manual segmentation at both the global and regional level. These results support the use of TrUE-Net for identifying WMH at the global or regional level, including in large, combined datasets.

Central Vein Sign in Pediatric Multiple Sclerosis and Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease.

BACKGROUND: The central vein sign (CVS) on brain magnetic resonance imaging (MRI) is a promising diagnostic marker for distinguishing adult multiple sclerosis (MS) from other demyelinating conditions, but its prevalence is not well-established in pediatric-onset multiple sclerosis (POMS) versus myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). MOGAD can mimic MS radiologically. This study seeks to determine the utility of CVS, together with other radiological findings, in distinguishing POMS from MOGAD in children. METHODS: Children with POMS or MOGAD were identified in a pediatric demyelinating database. Two reviewers, blinded to diagnosis, fused fluid-attenuated inversion recovery sequences and susceptibility-weighted imaging from clinical imaging to identify CVS. Agreement in CVS number was reported using intraclass correlation coefficients (ICC). We performed topographic analyses as well as characterization of the clinical information and lesions on brain, spinal cord, and orbital MRI when available. RESULTS: Twenty children, 10 with POMS and 10 with MOGAD, were assessed. The median lesion percentage of CVS was higher in POMS versus MOGAD for both raters (rater 1: 80% vs 9.8%; rater 2: 22.7% vs 7.5%). Inter-rater reliability for identifying total white matter lesions was strong (ICC 0.94 [95% confidence interval [CI] 0.84, 0.97]); however, it was poor for detecting CVS lesions (ICC -0.17 [95% CI: -0.37, 0.58]). CONCLUSION: The CVS can be a useful diagnostic tool for differentiating POMS from MOGAD. However, advanced clinical imaging tools that can better detect CVS are needed to increase inter-rater reliability before clinical application.

A universal neocortical mask for Centiloid quantification.

INTRODUCTION: The Centiloid (CL) project was developed to harmonize the quantification of amyloid beta (Aß) positron emission tomography (PET) scans to a unified scale. The CL neocortical mask was defined using 11C Pittsburgh compound B (PiB), overlooking potential differences in regional distribution among Aß tracers. We created a universal mask using an independent dataset of five Aß tracers, and investigated its impact on inter-tracer agreement, tracer variability, and group separation. METHODS: Using data from the Alzheimer's Dementia Onset and Progression in International Cohorts (ADOPIC) study (Australian Imaging Biomarkers and Lifestyle + Alzheimer's Disease Neuroimaging Initiative + Open Access Series of Imaging Studies), age-matched pairs of mild Alzheimer's disease (AD) and healthy controls (HC) were selected: 18F-florbetapir (N = 147 pairs), 18F-florbetaben (N = 22), 18F-flutemetamol (N = 10), 18F-NAV (N = 42), 11C-PiB (N = 63). The images were spatially and standardized uptake value ratio normalized. For each tracer, the mean AD-HC difference image was thresholded to maximize the overlap with the standard neocortical mask. The universal mask was defined as the intersection of all five masks. It was evaluated on the Global Alzheimer's Association Interactive Network (GAAIN) head-to-head datasets in terms of inter-tracer agreement and variance in the young controls (YC) and on the ADOPIC dataset comparing separation between HC/AD and HC/mild cognitive impairment (MCI). RESULTS: In the GAAIN dataset, the universal mask led to a small reduction in the variance of the YC, and a small increase in the inter-tracer agreement. In the ADOPIC dataset, it led to a better separation between HC/AD and HC/MCI at baseline. DISCUSSION: The universal CL mask led to an increase in inter-tracer agreement and group separation. Those increases were, however, very small, and do not provide sufficient benefits to support departing from the existing standard CL mask, which is suitable for the quantification of all Aß tracers. HIGHLIGHTS: This study built an amyloid universal mask using a matched cohort for the five most commonly used amyloid positron emission tomography tracers.There was a high overlap between each tracer-specific mask.Differences in quantification and group separation between the standard and universal mask were small.The existing standard Centiloid mask is suitable for the quantification of all amyloid beta tracers.

A new framework for metabolic connectivity mapping using bolus [18F]FDG PET and kinetic modeling.

Metabolic connectivity (MC) has been previously proposed as the covariation of static [18F]FDG PET images across participants, i.e., across-individual MC (ai-MC). In few cases, MC has been inferred from dynamic [18F]FDG signals, i.e., within-individual MC (wi-MC), as for resting-state fMRI functional connectivity (FC). The validity and interpretability of both approaches is an important open issue. Here we reassess this topic, aiming to 1) develop a novel wi-MC methodology; 2) compare ai-MC maps from standardized uptake value ratio (SUVR) vs. [18F]FDG kinetic parameters fully describing the tracer behavior (i.e., Ki, K1, k3); 3) assess MC interpretability in comparison to structural connectivity and FC. We developed a new approach based on Euclidean distance to calculate wi-MC from PET time-activity curves. The across-individual correlation of SUVR, Ki, K1, k3 produced different networks depending on the chosen [18F]FDG parameter (k3 MC vs. SUVR MC, r = 0.44). We found that wi-MC and ai-MC matrices are dissimilar (maximum r = 0.37), and that the match with FC is higher for wi-MC (Dice similarity: 0.47-0.63) than for ai-MC (0.24-0.39). Our analyses demonstrate that calculating individual-level MC from dynamic PET is feasible and yields interpretable matrices that bear similarity to fMRI FC measures.

Silent findings: Examination of asymptomatic demyelination in a pediatric US cohort.

BACKGROUND AND OBJECTIVES: Limited data is available on children with evidence of silent central nervous system demyelination on MRI. We sought to characterize the population in a US cohort and identify predictors of clinical and radiologic outcomes. METHODS: We identified 56 patients such patients who presented with incidental MRI findings suspect for demyelination, enrolled through our US Network of Pediatric Multiple Sclerosis Centers, and conducted a retrospective review of 38 patients with MR images, and examined risk factors for development of first clinical event or new MRI activity. MRI were rated based on published MS and radiologically isolated syndrome (RIS) imaging diagnostic criteria. RESULTS: One-third had a clinical attack and ¾ developed new MRI activity over a mean follow-up time of 3.7 years. Individuals in our cohort shared similar demographics to those with clinically definite pediatric-onset MS. We show that sex, presence of infratentorial lesions, T1 hypointense lesions, juxtacortical lesion count, and callosal lesions were predictors of disease progression. Interestingly, the presence of T1 hypointense and infratentorial lesions typically associated with worse outcomes were instead predictive of delayed disease progression on imaging in subgroup analysis. Additionally, currently utilized diagnostic criteria (both McDonald 2017 and RIS criteria) did not provide statistically significant benefit in risk stratification. CONCLUSION: Our findings underscore the need for further study to determine if criteria currently used for pediatric patients with purely radiographic evidence of demyelination are sufficient.

Brain aerobic glycolysis and resilience in Alzheimer disease.

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aß) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process.

Automated analysis of low-field brain MRI in cerebral malaria.

A central challenge of medical imaging studies is to extract biomarkers that characterize disease pathology or outcomes. Modern automated approaches have found tremendous success in high-resolution, high-quality magnetic resonance images. These methods, however, may not translate to low-resolution images acquired on magnetic resonance imaging (MRI) scanners with lower magnetic field strength. In low-resource settings where low-field scanners are more common and there is a shortage of radiologists to manually interpret MRI scans, it is critical to develop automated methods that can augment or replace manual interpretation, while accommodating reduced image quality. We present a fully automated framework for translating radiological diagnostic criteria into image-based biomarkers, inspired by a project in which children with cerebral malaria (CM) were imaged using low-field 0.35 Tesla MRI. We integrate multiatlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We also propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers have excellent classification performance for determining severe brain swelling due to CM.

MOG and AQP4 Antibodies among Children with Multiple Sclerosis and Controls.

OBJECTIVE: The purpose of this study was to determine the frequency of myelin oligodendrocyte glycoprotein (MOG)-IgG and aquaporin-4 (AQP4)-IgG among patients with pediatric-onset multiple sclerosis (POMS) and healthy controls, to determine whether seropositive cases fulfilled their respective diagnostic criteria, to compare characteristics and outcomes in children with POMS versus MOG-IgG-associated disease (MOGAD), and identify clinical features associated with final diagnosis. METHODS: Patients with POMS and healthy controls were enrolled at 14 US sites through a prospective case-control study on POMS risk factors. Serum AQP4-IgG and MOG-IgG were assessed using live cell-based assays. RESULTS: AQP4-IgG was negative among all 1,196 participants, 493 with POMS and 703 healthy controls. MOG-IgG was positive in 30 of 493 cases (6%) and zero controls. Twenty-five of 30 patients positive with MOG-IgG (83%) had MOGAD, whereas 5 of 30 (17%) maintained a diagnosis of multiple sclerosis (MS) on re-review of records. MOGAD cases were more commonly in female patients (21/25 [84%] vs 301/468 [64%]; p = 0.044), younger age (mean = 8.2 ± 4.2 vs 14.7 ± 2.6 years; p < 0.001), more commonly had initial optic nerve symptoms (16/25 [64%] vs 129/391 [33%]; p = 0.002), or acute disseminated encephalomyelitis (ADEM; 8/25 [32%] vs 9/468 [2%]; p < 0.001), and less commonly had initial spinal cord symptoms (3/20 [15%] vs 194/381 [51%]; p = 0.002), serum Epstein-Barr virus (EBV) positivity (11/25 [44%] vs 445/468 [95%]; p < 0.001), or cerebrospinal fluid oligoclonal bands (5/25 [20%] vs 243/352 [69%]; p < 0.001). INTERPRETATION: MOG-IgG and AQP4-IgG were not identified among healthy controls confirming their high specificity for pediatric central nervous system (CNS) demyelinating disease. Five percent of those with prior POMS diagnoses ultimately had MOGAD; and none had AQP4-IgG positivity. Clinical features associated with a final diagnosis of MOGAD in those with suspected MS included initial ADEM phenotype, younger age at disease onset, and lack of EBV exposure. ANN NEUROL 2023;93:271-284.

Location-atypical lesions in non-ketotic hyperglycemic epilepsy: expanding the clinico-radiographic phenotype

Non-ketotic hyperglycemia (NKH) is associated with a spectrum of symptoms and radiographic findings due to poorly-controlled diabetes mellitus. These lesions, which predominantly affect the parieto-occipital cortex, are commonly missed by neurologists and neuroradiologists due to their subtle hypointense appearance on T2-based imaging. We report four atypical cases of this syndrome to highlight its subtle, protean presentation in order to aid timely diagnosis. Based on our institutional case series, we describe four cases of NKH with atypical presentation and lesion burden affecting the anterior cortex. We review the clinical presentations, laboratory abnormalities, neuroimaging, and corresponding electroencephalography. Four patients with atypical NKH were characterized in our series. Presenting symptoms ranged from rhythmic hand-tapping to generalized tonic-clonic status epilepticus. Laboratory values were notable for marked hyperglycemia (range: 447 - 627 mg/dL), mild pseudo-hyponatremia (range: 127 - 136 mmol/L), and elevated hemoglobin A1C levels (range: 10.9 - 16.1%). All patients were found to have the classically described pattern of T2-based hypointensity; three with atypical distributions involving the "anterior" cortex. These lesions corresponded to the electrographic nidus of seizure burden. During follow-up, both seizures and T2-based hypointensity resolved within weeks of serum glucose normalization. Our series of four NKH patients with atypical findings of T2-based signal abnormalities expands the clinico-radiographic phenotype revealing a more protean distribution than previously described. Knowledge of these atypical imaging features will aid both the neurologist and radiologist in timely diagnosis and care of these patients.

Modeling venous plasma samples in [18F] FDG PET studies: a nonlinear mixed-effects approach.

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant. In this work, we used the nonlinear mixed-effects modeling approach to develop a model which infers venous tracer kinetics by using venous samples obtained from a population of healthy individuals and integrating subject-specific covariates. Population parameters (fixed effects), their between-subject variability (random effects), and the effects of covariates were estimated. The selected model will allow to reliably infer venous tracer kinetics in subjects with missing measurements. Clinical relevance - The derived model will be relevant for fully noninvasive dynamic FDG PET quantification using image-derived input functions in both healthy and patient populations when hemodynamics is not impaired.

Mechanisms of Transcranial Doppler Ultrasound phenotypes in paediatric cerebral malaria remain elusive.

BACKGROUND: Cerebral malaria (CM) results in significant paediatric death and neurodisability in sub-Saharan Africa. Several different alterations to typical Transcranial Doppler Ultrasound (TCD) flow velocities and waveforms in CM have been described, but mechanistic contributors to these abnormalities are unknown. If identified, targeted, TCD-guided adjunctive therapy in CM may improve outcomes. METHODS: This was a prospective, observational study of children 6 months to 12 years with CM in Blantyre, Malawi recruited between January 2018 and June 2021. Medical history, physical examination, laboratory analysis, electroencephalogram, and magnetic resonance imaging were undertaken on presentation. Admission TCD results determined phenotypic grouping following a priori definitions. Evaluation of the relationship between haemodynamic, metabolic, or intracranial perturbations that lead to these observed phenotypes in other diseases was undertaken. Neurological outcomes at hospital discharge were evaluated using the Paediatric Cerebral Performance Categorization (PCPC) score. RESULTS: One hundred seventy-four patients were enrolled. Seven (4%) had a normal TCD examination, 57 (33%) met criteria for hyperaemia, 50 (29%) for low flow, 14 (8%) for microvascular obstruction, 11 (6%) for vasospasm, and 35 (20%) for isolated posterior circulation high flow. A lower cardiac index (CI) and higher systemic vascular resistive index (SVRI) were present in those with low flow than other groups (p < 0.003), though these values are normal for age (CI 4.4 [3.7,5] l/min/m2, SVRI 1552 [1197,1961] dscm-5m2). Other parameters were largely not significantly different between phenotypes. Overall, 118 children (68%) had a good neurological outcome. Twenty-three (13%) died, and 33 (19%) had neurological deficits. Outcomes were best for participants with hyperaemia and isolated posterior high flow (PCPC 1-2 in 77 and 89% respectively). Participants with low flow had the least likelihood of a good outcome (PCPC 1-2 in 42%) (p < 0.001). Cerebral autoregulation was significantly better in children with good outcome (transient hyperemic response ratio (THRR) 1.12 [1.04,1.2]) compared to a poor outcome (THRR 1.05 [0.98,1.02], p = 0.05). CONCLUSIONS: Common pathophysiological mechanisms leading to TCD phenotypes in non-malarial illness are not causative in children with CM. Alternative mechanistic contributors, including mechanical factors of the cerebrovasculature and biologically active regulators of vascular tone should be explored.

Performance of Automated RAPID Intracranial Hemorrhage Detection in Real-World Practice: A Single-Institution Experience.

BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) is a common finding in patients presenting to the emergency department with acute neurological symptoms. Noncontrast head computed tomography (NCCT) is the primary modality for assessment and detection of ICH in the acute setting. RAPID ICH software aims to automatically detect ICH on NCCT and was previously shown to have high accuracy when applied to a curated test data set. Here, we measured the test performance characteristics of RAPID ICH software in detecting ICH on NCCT performed in patients undergoing emergency stroke evaluation at a tertiary academic comprehensive stroke center. MATERIALS AND METHODS: This retrospective study assessed consecutive patients over a 6-month period who presented with acute neurological symptoms suspicious for stroke and underwent NCCT with RAPID ICH postprocessing. RAPID ICH detection was compared with the interpretation of a reference standard comprising a board-certified or board-eligible neuroradiologist, or in cases of discrepancy, adjudicated by a consensus panel of 3 neuroradiologists. Accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of RAPID ICH for ICH detection were determined. RESULTS: Three hundred seven NCCT scans were included in the study. RAPID ICH correctly identified 34 of 37 cases with ICH and 228 of 270 without ICH. RAPID ICH had a sensitivity of 91.9% (78.1%-98.3%), specificity of 84.4% (79.6%-88.6%), NPV of 98.7% (96.3%-99.6%), PPV of 44.7% (37.6%-52.1%), and overall accuracy of 85.3% (80.9%-89.1%). CONCLUSIONS: In a real-world scenario, RAPID ICH software demonstrated high NPV but low PPV for the presence of ICH when evaluating possible stroke patients.

Cranial vault imaging for pediatric head trauma using a radial VIBE MRI sequence.

OBJECTIVE: Head trauma is the most common indication for a CT scan. In this pilot study, the authors assess the feasibility of a 5-minute high-resolution 3D golden-angle (GA) stack-of-stars radial volumetric interpolated breath-hold examination (VIBE) MRI sequence (GA-VIBE) to obtain clinically acceptable cranial bone images and identify cranial vault fractures compared to CT. METHODS: Patients younger than 18 years of age presenting after head trauma were eligible for the study. Three clinicians reviewed and assessed 1) slice-by-slice volumetric CT and inverted MR images, and 2) 3D reconstructions obtained from inverted MR images and the gold standard (CT). For each image set, reviewers noted on 5-point Likert scales whether they recommended that a repeat scan be performed and the presence or absence of cranial vault fractures. RESULTS: Thirty-one patients completed MRI after a clinical head CT scan was performed. Based on CT imaging, 8 of 31 patients had cranial fractures. Two of 31 patients were sedated as part of their clinical MRI scan. In 30 (97%) of 31 MRI reviews, clinicians agreed (or strongly agreed) that the image quality was acceptable for clinical diagnosis. Overall, comparing MRI to acceptable gold-standard CT, sensitivity and specificity of fracture detection were 100%. Furthermore, there were no discrepancies between CT and MRI in classification of fracture type or location. CONCLUSIONS: When compared with the gold standard (CT), the volumetric and 3D reconstructed images using the GA-VIBE sequence were able to produce clinically acceptable cranial images with excellent ability to detect cranial vault fractures.

Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease.

BACKGROUND: Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis. OBJECTIVE: To apply a recently developed quantitative Gradient Recalled Echo (qGRE) MRI technique for in vivo evaluation of neuronal loss in human hippocampus. METHODS: Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®) = 0, amyloid ß (Aß)-negative, n = 34]; Preclinical AD (CDR = 0, Aß-positive, n = 19); and mild AD (CDR = 0.5 or 1, Aß-positive, n = 17). RESULTS: In hippocampal tissue, qGRE identified two types of regions: one, practically devoid of neurons, we designate as "Dark Matter", and the other, with relatively preserved neurons, "Viable Tissue". Data showed a greater loss of neurons than defined by atrophy in the mild AD group compared with the healthy control group; neuronal loss ranged between 31% and 43%, while volume loss ranged only between 10% and 19%. The concept of Dark Matter was confirmed with histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration. CONCLUSION: In vivo qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by MRI measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.

Increased white matter glycolysis in humans with cerebral small vessel disease.

White matter lesions in cerebral small vessel disease are related to ischemic injury and increase the risk of stroke and cognitive decline. Pathological changes due to cerebral small vessel disease are increasingly recognized outside of discrete lesions, but the metabolic alterations in nonlesional tissue has not been described. Aerobic glycolysis is critical to white matter myelin homeostasis and repair. In this study, we examined cerebral metabolism of glucose and oxygen as well as blood flow in individuals with and without cerebral small vessel disease using multitracer positron emission tomography. We show that glycolysis is relatively elevated in nonlesional white matter in individuals with small vessel disease relative to healthy, age-matched controls. On the other hand, in young healthy individuals, glycolysis is relatively low in areas of white matter susceptible to lesion formation. These results suggest that increased white matter glycolysis is a marker of pathology associated with small vessel disease.