Faculty Bibliography

Head computed tomography (CT) imaging is a widely used imaging modality with multitudes of medical indications, particularly in assessing pathology of the brain, skull and cerebrovascular system. It is commonly used as the first-line imaging in neurologic emergencies given its rapidity of image acquisition, safety, cost and ubiquity. Deep learning models may facilitate detection of a wide range of diseases. However, the scarcity of high-quality labels and annotations, particularly among less common conditions, substantially hinders the development of powerful models. To address this challenge, we introduce FM-HCT, a Foundation Model for Head CT for generalizable disease detection, trained using self-supervised learning. Our approach pretrains a deep learning model on a large, diverse dataset of 361,663 non-contrast 3D head CT scans without the need for manual annotations, enabling the model to learn robust, generalizable features. Our results demonstrate that the self-supervised foundation model substantially improves performance on downstream diagnostic tasks compared to models trained from scratch and previous 3D CT foundation models trained on scarce annotated datasets.

INTRODUCTION/BACKGROUND:Measuring plasma biomarkers effectively assesses early-stage Alzheimer's disease. METHODS:Subjects were categorized as cognitively unimpaired (CU) (n = 66), CU with subjective cognitive decline (SCD) (n = 100), and mild cognitive impairment (MCI) (n = 25). Plasma biomarkers measured were amyloid beta (Aβ) 40, Aβ42, neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), tau phosphorylated at threonine 181 (pTau181), neuroinflammatory biomarkers, and blood-brain barrier biomarkers. Amyloid and tau positron emission tomography (PET) imaging was performed in 186 and 144 subjects, respectively. RESULTS:Comparing those having MCI, both CU and SCD participants had significantly lower amyloid PET standardized uptake value ratio (SUVR) (p < 0.001; p = 0.005). Higher amyloid PET SUVR was significantly associated with higher pTau181 (p = 0.001) and a higher pTau181/Aβ42 ratio (p < 0.001). Higher tau PET SUVR was associated with lower plasma Aβ42 (p = 0.020), older age (p = 0.005), higher GFAP (p = 0.020), and lower interleukin-8 levels (p < 0.001). DISCUSSION/CONCLUSIONS:Our study supports plasma biomarker monitoring of at-risk patients at various stages of pre-dementia.

Reliable structural brain measurements are essential for studying neurodegeneration and for designing adequately powered aging and Alzheimer's disease (AD) research. We evaluated the test-retest reliability of FreeSurfer 7.1 morphometric measures in 100 older adults (mean age 73.5 years) ranging from cognitively unimpaired to dementia. Each participant underwent two T1-weighted 3T MRI scans on the same scanner within a short interval (mean 5.5 weeks), minimizing biological change. Segmentation was performed in both standard cross-sectional and longitudinal FreeSurfer modes, focusing on AD-relevant volumes of entorhinal cortex, hippocampus, lateral ventricles, choroid plexus, and the AD cortical thickness signature. Reliability was quantified using absolute and root-mean-square test-retest differences, standard deviation of differences, and intraclass correlation coefficients. Longitudinal processing improved precision by 15-50% across most measures compared with cross-sectional processing, with the largest gain observed for entorhinal thickness. Larger, anatomically well-defined regions (e.g., hippocampus, AD signature) demonstrated higher reliability than small structures or those with complex geometry (e.g., entorhinal cortex, choroid plexus). Image quality, indexed by the Euler characteristic, was the only factor significantly associated with measurement variability; reliability was unrelated to age, sex, cognitive status, inter-scan interval, or amyloid/tau PET burden. Power analyses indicated that detecting a 1% within-individual change requires sample sizes ranging from 36 (AD signature) to >300 (entorhinal cortex). We observed low reliability of choroid plexus volumetry by FreeSurfer 7. These results provide practical benchmarks for expected FreeSurfer measurement variability in older adults. They highlight the advantages of longitudinal processing and rigorous quality control for research on brain aging and AD.

INTRODUCTION/BACKGROUND:Though brain fog is common in Long-coronavirus disease 2019 (Long-COVID), the incidence of mild cognitive impairment (MCI) is unknown. METHODS:In an observational cohort study, recovered COVID-positive, Long-COVID, and COVID-negative subjects underwent blinded evaluation using National Alzheimer's Coordinating Center (NACC) and National Institute on Aging (NIA) -Alzheimer's Association diagnostic criteria for dementia and MCI. The cumulative incidence of MCI was calculated for each group, and the hazard of MCI was compared between groups. RESULTS:Among 260 subjects, the cumulative incidence of MCI over 4.4 years was higher with Long-COVID (27%) versus recovered-COVID (5%) or COVID-negative status (1%). There was a higher hazard of MCI for patients with Long-COVID compared to those without (hazard ratio [HR] 3.93, 95% confidence interval [CI] 1.86-8.31, p < 0.001), and specifically for the Alzheimer's disease (AD) -related MCI subtype (HR 3.20, 95% confidence interval [CI] 1.14-9.00, p = 0.027). DISCUSSION/CONCLUSIONS:The cumulative incidence and adjusted hazard of MCI (and specifically AD-related MCI) at 4.4 years was significantly higher among Long-COVID patients compared to recovered-COVID and COVID-negative controls.

Neurodegeneration, along with amyloid and tau, define the AT(N) framework of Alzheimer's disease that has shaped the development of diagnostics and therapeutics. Yet, biomarker development for neurodegeneration has lagged behind that for amyloid and tau, with limited definition of its heterogeneous microstructural aspects that may each serve as critical measures. In this issue of the JCI, Gong et al. leveraged diffusion MRI to derive a unique measure of axonal injury or axonal density index (ADI). Through cross-sectional and longitudinal analyses, they demonstrated that the ADI has superior performance in detecting, tracking, and predicting clinical impairment compared with prior diffusion MRI methods to evaluate axonal health and standard biomarkers of amyloid and tau. As such, the ADI measure may serve as an important expansion of the neurodegeneration biomarker repertoire.

INTRODUCTION/BACKGROUND:Choroid plexus (ChP) enlargement is a neuroimaging biomarker of neuroinflammation and neurodegeneration. However, evidence of ChP structural and perfusion alterations in long coronavirus disease (COVID) and their clinical relevance remains limited. METHODS:This study included 86 long COVID, 67 recovered COVID, and 26 COVID-negative healthy controls (HCs). ChP volume and cerebral blood flow (CBF) were quantified, and their associations with Alzheimer's disease (AD) symptoms and plasma biomarkers were examined. RESULTS:Both patient groups showed higher ChP volume and lower CBF than HC. Relative to recovered COVID, long COVID patients had a larger ChP volume, but no significant difference in CBF. ChP volume correlated positively with glial fibrillary acidic protein (r = 0.35) and phosphorylated tau217 (p-tau217; r = 0.54), while CBF correlated negatively with p-tau217 (r = -0.56). Both ChP volume and CBF were associated with cognitive decline measured with Mini-Mental State Examination and Clinical Dementia Rating. DISCUSSION/CONCLUSIONS:These findings suggest that ChP differences in long COVID are associated with AD-related cognitive decline and increased plasma biomarkers. HIGHLIGHTS/CONCLUSIONS:Long coronavirus disease (COVID) patients show choroid plexus (ChP) enlargement and reduced cerebral blood flow. ChP alterations are associated with Alzheimer's disease (AD)-related symptoms and plasma biomarker changes. ChP alterations on magnetic resonance imaging may serve as imaging markers for tracking neurological symptoms and AD-related pathology in post-COVID patients.

BACKGROUND:Identifying early neuropathological changes in Alzheimer's disease (AD) is important for improving treatment efficacy. Among quantitative MRI measures, transverse relaxation time (T2) has been shown to reflect tissue microstructure relevant in aging and neurodegeneration; however, findings regarding T2 changes in both normal aging and AD have been inconsistent. The association between T2 and amyloid-beta (Aβ) accumulation, a hallmark of AD pathology, is also unclear, particularly in cognitively normal individuals who may be in preclinical stages of the disease. PURPOSE/OBJECTIVE:To investigate longitudinal hippocampal T2 changes in a cognitively normal cohort of older adults and their association with global Aβ accumulation. STUDY TYPE/METHODS:Retrospective, longitudinal. SUBJECTS/METHODS:56 cognitively normal adults between 55 and 90 years of age (17 males and 39 females). FIELD STRENGTH/SEQUENCE/UNASSIGNED:3 Tesla; multi-echo spin echo sequence for T2 mapping; 18F-florbetaben positron emission tomography for Aβ measurement. ASSESSMENT/RESULTS:Bilateral hippocampal T2 and volume were extracted to relate to Aβ PET measurements. To understand variations in AD risk, participants were separated into Aβ-high and Aβ-low subgroups using a predetermined threshold. STATISTICAL TESTS/METHODS:Linear mixed-effect models and general linear models were used. A p-value < 0.025 was considered significant to account for bilateral comparisons. RESULTS:Older age was associated with increased T2 in the bilateral hippocampus (left: β = 0.30, right: β = 0.25) and smaller hippocampal volume on the left (β = -0.12). In the Aβ-low subgroup, both longitudinal T2 increase rates (β = 0.65) in the left hippocampus and bilateral cross-sectional T2 (left: β = 0.64, right: β = 0.46) were positively correlated with Aβ PET, independent of hippocampal volume. DATA CONCLUSION/CONCLUSIONS:This study provided in vivo evidence linking hippocampal T2 to Aβ accumulation in cognitively normal aging individuals, suggesting that quantitative T2 may be sensitive to microstructural changes accompanying early Aβ pathology, such as neuroinflammation, demyelination, and reduced tissue integrity. EVIDENCE LEVEL/METHODS:3. TECHNICAL EFFICACY/UNASSIGNED:Stage 2.

INTRODUCTION/BACKGROUND:The Consortium for Clarity in Alzheimer's disease related dementias (ADRD) Research Through Imaging (CLARiTI) is a study that aims to collect standardized imaging and plasma biomarkers on 2000 Clinical Core participants enrolled across all Alzheimer's Disease Research Centers (ADRC) sites. We sought to summarize the known heterogeneity across centers regarding scientific focus and initial enrollment plans for CLARiTI. METHODS:We developed and distributed a survey capturing information on the 36 CLARiTI site's theme/expertise, recruitment plans, and the intersection of CLARiTI with other ADRC imaging efforts. RESULTS:Anticipated CLARiTI enrollees spanned 11 different categories of suspected etiologies underlying impairment. A wide range of risk factors were endorsed across sites regarding the enrollment of unimpaired individuals. Variability also existed regarding site-level strategies in enrollment into CLARiTI versus other imaging efforts. DISCUSSION/CONCLUSIONS:We anticipate that the 2000 individuals that will enroll into CLARiTI will reflect the clinical heterogeneity already in place across the ADRC network. HIGHLIGHTS/CONCLUSIONS:The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will leverage and contribute to the existing Alzheimer's Disease Research Centers (ADRC) program by supporting standardized imaging and plasma collection across all centers. We summarize the variation in scientific focus and enrollment plans across ADRC sites participating in CLARiTI. The anticipated CLARiTI cohort will reflect the clinical heterogeneity that already exists across the ADRC network. CLARiTI will contribute to scientific goals related to the detection of multi-etiological signatures relevant for Alzheimer's disease and related disorders (ADRDs).

INTRODUCTION/UNASSIGNED:White matter hyperintensity (WMH) is a hallmark imaging biomarker of cerebral small vessel disease and are strongly associated with vascular cognitive impairment in the elderly. Morphological changes in large extracranial brain-feeding arteries, such as the internal carotid (ICA) and vertebral arteries (VA), may alter intracranial hemodynamics and contribute to WMH development. This study examined the relationship between arterial tortuosity and WMHs using magnetic resonance angiography (MRA). METHODS/UNASSIGNED:Seventy-eight participants underwent time-of-flight (TOF) MRA and phase-contrast (PC) MRI to assess arterial morphology and blood flow. After excluding three for poor image quality, 75 subjects were analyzed. Arterial tortuosity was quantified using the inflection count metric (ICM) and ICA angle. Global cerebral blood flow (CBF) was estimated with PC-MRI and compared against pseudo-continuous arterial spin labeling (pCASL) to determine whether it could be a reliable surrogate measurement to reflect intracranial blood supply. RESULTS/UNASSIGNED:Participants with severe WMHs (Fazekas ≥2) demonstrated greater tortuosity (higher ICM and larger ICA angles) and lower blood flow than those with mild WMHs. Females showed more tortuous arteries, greater WMH burden, and higher susceptibility to hypoperfusion. Correlation analyses revealed a positive association between tortuosity and WMH volume. DISCUSSION/UNASSIGNED:These findings highlight the role of extracranial arterial tortuosity in WMH burden and reveal sex-specific differences in vascular vulnerability. The results underscore the need for further investigation into how age-related vascular remodeling contributes to WMH development and cognitive decline.

Synaptic spine loss is an early pathophysiologic hallmark of Alzheimer disease (AD) that precedes overt loss of dendritic architecture and frank neurodegeneration. While spine loss signifies a decreased engagement of postsynaptic neurons by presynaptic targets, the degree to which loss of spines and their passive components impacts the excitability of postsynaptic neurons and responses to surviving synaptic inputs is unclear. Using passive multicompartmental models of CA1 pyramidal neurons (PNs), implicated in early AD, we find that spine loss alone drives a boosting of remaining inputs to their proximal and distal dendrites, targeted by CA3 and entorhinal cortex (EC), respectively. This boosting effect is higher in distal versus proximal dendrites and can be mediated by spine loss restricted to the distal compartment, enough to impact synaptic input integration, somatodendritic backpropagation, and plateau potential generation. This has particular relevance to very early stages of AD in which pathophysiology extends from EC to CA1.