The biomedical research community is motivated to share and reuse data from studies and projects by funding agencies and publishers. Effectively combining and reusing neuroimaging data from publicly available datasets, requires the capability to query across datasets in order to identify cohorts that match both neuroimaging and clinical/behavioral data criteria. Critical barriers to operationalizing such queries include, in part, the broad use of undefined study variables with limited or no annotations that make it difficult to understand the data available without significant interaction with the original authors. Using the Brain Imaging Data Structure (BIDS) to organize neuroimaging data has made querying across studies for specific image types possible at scale. However, in BIDS, beyond file naming and tightly controlled imaging directory structures, there are very few constraints on ancillary variable naming/meaning or experiment-specific metadata. In this work, we present NIDM-Terms, a set of user-friendly terminology management tools and associated software to better manage individual lab terminologies and help with annotating BIDS datasets. Using these tools to annotate BIDS data with a Neuroimaging Data Model (NIDM) semantic web representation, enables queries across datasets to identify cohorts with specific neuroimaging and clinical/behavioral measurements. This manuscript describes the overall informatics structures and demonstrates the use of tools to annotate BIDS datasets to perform integrated cross-cohort queries.

Significant resources around the world have been invested in neuroimaging studies of brain function and disease. Easier access to this large body of work should have profound impact on research in cognitive neuroscience and psychiatry, leading to advances in the diagnosis and treatment of psychiatric and neurological disease. A trend toward increased sharing of neuroimaging data has emerged in recent years. Nevertheless, a number of barriers continue to impede momentum. Many researchers and institutions remain uncertain about how to share data or lack the tools and expertise to participate in data sharing. The use of electronic data capture (EDC) methods for neuroimaging greatly simplifies the task of data collection and has the potential to help standardize many aspects of data sharing. We review here the motivations for sharing neuroimaging data, the current data sharing landscape, and the sociological or technical barriers that still need to be addressed. The INCF Task Force on Neuroimaging Datasharing, in conjunction with several collaborative groups around the world, has started work on several tools to ease and eventually automate the practice of data sharing. It is hoped that such tools will allow researchers to easily share raw, processed, and derived neuroimaging data, with appropriate metadata and provenance records, and will improve the reproducibility of neuroimaging studies. By providing seamless integration of data sharing and analysis tools within a commodity research environment, the Task Force seeks to identify and minimize barriers to data sharing in the field of neuroimaging.

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html.

The MarkVCID consortium was formed under cooperative agreements with the National Institute of Neurologic Diseases and Stroke (NINDS) and National Institute on Aging (NIA) in 2016 with the goals of developing and validating biomarkers for the cerebral small vessel diseases associated with the vascular contributions to cognitive impairment and dementia (VCID). Rigorously validated biomarkers have consistently been identified as crucial for multicenter studies to identify effective strategies to prevent and treat VCID, specifically to detect increased VCID risk, diagnose the presence of small vessel disease and its subtypes, assess prognosis for disease progression or response to treatment, demonstrate target engagement or mechanism of action for candidate interventions, and monitor disease progression during treatment. The seven project sites and central coordinating center comprising MarkVCID, working with NINDS and NIA, identified a panel of 11 candidate fluid- and neuroimaging-based biomarker kits and established harmonized multicenter study protocols (see companion paper "MarkVCID cerebral small vessel consortium: I. Enrollment, clinical, fluid protocols" for full details). Here we describe the MarkVCID neuroimaging protocols with specific focus on validating their application to future multicenter trials. MarkVCID procedures for participant enrollment; clinical and cognitive evaluation; and collection, handling, and instrumental validation of fluid samples are described in detail in a companion paper. Magnetic resonance imaging (MRI) has long served as the neuroimaging modality of choice for cerebral small vessel disease and VCID because of its sensitivity to a wide range of brain properties, including small structural lesions, connectivity, and cerebrovascular physiology. Despite MRI's widespread use in the VCID field, there have been relatively scant data validating the repeatability and reproducibility of MRI-based biomarkers across raters, scanner types, and time intervals (collectively defined as instrumental validity). The MRI protocols described here address the core MRI sequences for assessing cerebral small vessel disease in future research studies, specific sequence parameters for use across various research scanner types, and rigorous procedures for determining instrumental validity. Another candidate neuroimaging modality considered by MarkVCID is optical coherence tomography angiography (OCTA), a non-invasive technique for directly visualizing retinal capillaries as a marker of the cerebral capillaries. OCTA has theoretical promise as a unique opportunity to visualize small vessels derived from the cerebral circulation, but at a considerably earlier stage of development than MRI. The additional OCTA protocols described here address procedures for determining OCTA instrumental validity, evaluating sources of variability such as pupil dilation, and handling data to maintain participant privacy. MRI protocol and instrumental validation The core sequences selected for the MarkVCID MRI protocol are three-dimensional T1-weighted multi-echo magnetization-prepared rapid-acquisition-of-gradient-echo (ME-MPRAGE), three-dimensional T2-weighted fast spin echo fluid-attenuated-inversion-recovery (FLAIR), two-dimensional diffusion-weighted spin-echo echo-planar imaging (DWI), three-dimensional T2*-weighted multi-echo gradient echo (3D-GRE), three-dimensional T₂ -weighted fast spin-echo imaging (T2w), and two-dimensional T2*-weighted gradient echo echo-planar blood-oxygenation-level-dependent imaging with brief periods of CO₂ inhalation (BOLD-CVR). Harmonized parameters for each of these core sequences were developed for four 3 Tesla MRI scanner models in widespread use at academic medical centers. MarkVCID project sites are trained and certified for their instantiation of the consortium MRI protocols. Sites are required to perform image quality checks every 2 months using the Alzheimer's Disease Neuroimaging Initiative phantom. Instrumental validation for MarkVCID MRI-based biomarkers is operationally defined as inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility. Assessments of these instrumental properties are performed on individuals representing a range of cerebral small vessel disease from mild to severe. Inter-rater reliability is determined by distribution of an independent dataset of MRI scans to each analysis site. Test-retest repeatability is determined by repeat MRI scans performed on individual participants on a single MRI scanner after a short (1- to 14-day) interval. Inter-scanner reproducibility is determined by repeat MRI scans performed on individuals performed across four MRI scanner models. OCTA protocol and instrumental validation The MarkVCID OCTA protocol uses a commercially available, Food and Drug Administration-approved OCTA apparatus. Imaging is performed on one dilated and one undilated eye to assess the need for dilation. Scans are performed in quadruplicate. MarkVCID project sites participating in OCTA validation are trained and certified by this biomarker's lead investigator. Inter-rater reliability for OCTA is assessed by distribution of OCTA datasets to each analysis site. Test-retest repeatability is assessed by repeat OCTA imaging on individuals on the same day as their baseline OCTA and a different-day repeat session after a short (1- to 14-day) interval. Methods were developed to allow the OCTA data to be de-identified by the sites before transmission to the central data management system. The MarkVCID neuroimaging protocols, like the other MarkVCID procedures, are designed to allow translation to multicenter trials and as a template for outside groups to generate directly comparable neuroimaging data. The MarkVCID neuroimaging protocols are available to the biomedical community and intended to be shared. In addition to the instrumental validation procedures described here, each of the neuroimaging MarkVCID kits will undergo biological validation to determine its ability to measure important aspects of VCID such as cognitive function. The analytic methods for the neuroimaging-based kits and the results of these validation studies will be published separately. The results will ultimately determine the neuroimaging kits' potential usefulness for multicenter interventional trials in small vessel disease-related VCID.

The diffusion tensor image analysis along the perivascular space (DTI-ALPS) method was proposed to evaluate glymphatic system (GS) function. However, few studies have validated its reliability and reproducibility. Fifty participants' DTI data from the MarkVCID consortium were included in this study. Two pipelines by using DSI studio and FSL software were developed for data processing and ALPS index calculation. The ALPS index was obtained by the average of bilateral ALPS index and was used for testing the cross-vendor, inter-rater and test-retest reliability by using R studio software. The ALPS index demonstrated favorable inter-scanner reproducibility (ICC=0.77 to 0.95, P< 0.001), inter-rater reliability (ICC=0.96 to 1, P< 0.001) and test-retest repeatability (ICC=0.89 to 0.95, P< 0.001), offering a potential biomarker for in vivo evaluation of GS function.

Introduction

To describe the protocol and findings of the instrumental validation of three imaging-based biomarker kits selected by the MarkVCID consortium: free water (FW) and peak width of skeletonized mean diffusivity (PSMD), both derived from diffusion tensor imaging (DTI), and white matter hyperintensity (WMH) volume derived from fluid attenuation inversion recovery and T1-weighted imaging.

Methods

The instrumental validation of imaging-based biomarker kits included inter-rater reliability among participating sites, test-retest repeatability, and inter-scanner reproducibility across three types of magnetic resonance imaging (MRI) scanners using intra-class correlation coefficients (ICC).

Results

The three biomarkers demonstrated excellent inter-rater reliability (ICC >0.94, P-values < .001), very high agreement between test and retest sessions (ICC >0.98, P-values < .001), and were extremely consistent across the three scanners (ICC >0.98, P-values < .001).

Discussion

The three biomarker kits demonstrated very high inter-rater reliability, test-retest repeatability, and inter-scanner reproducibility, offering robust biomarkers suitable for future multi-site observational studies and clinical trials in the context of vascular cognitive impairment and dementia (VCID).

Introduction

To evaluate the clinical validity of free water (FW), a diffusion tensor imaging-based biomarker kit proposed by the MarkVCID consortium, by investigating the association between mean FW (mFW) and executive function.

Methods

Baseline mFW was related to a baseline composite measure of executive function (EFC), adjusting for relevant covariates, in three MarkVCID sub-cohorts, and replicated in five, large, independent legacy cohorts. In addition, we tested whether baseline mFW predicted accelerated EFC score decline (mean follow-up time: 1.29 years).

Results

Higher mFW was found to be associated with lower EFC scores in MarkVCID legacy and sub-cohorts (p-values < 0.05). In addition, higher baseline mFW was associated significantly with accelerated decline in EFC scores (p = 0.0026).

Discussion

mFW is a sensitive biomarker of cognitive decline, providing a strong clinical rational for its use as a marker of white matter (WM) injury in multi-site observational studies and clinical trials of vascular cognitive impairment and dementia (VCID).

INTRODUCTION: Vascular contributions to cognitive impairment and dementia (VCID) represent a major factor in cognitive decline in older adults. The present study examined the relationship between cerebrovascular reactivity (CVR) measured by magnetic resonance imaging (MRI) and cognitive function in a multi-site study, using a predefined hypothesis. METHODS: We conducted the study in a total of three analysis sites and 263 subjects. Each site performed an identical CVR MRI procedure using 5% carbon dioxide inhalation. A global cognitive measure of Montreal Cognitive Assessment (MoCA) and an executive function measure of item response theory (IRT) score were used as outcomes. RESULTS: CVR and MoCA were positively associated, and this relationship was reproduced at all analysis sites. CVR was found to be positively associated with executive function. DISCUSSION: The predefined hypothesis on the association between CVR and a global cognitive score was validated in three independent analysis sites, providing support for CVR as a biomarker in VCID. HIGHLIGHTS: This study measured a novel functional index of small arteries referred to as cerebrovascular reactivity (CVR). CVR was positively associated with global cognition in older adults. This finding was observed in three independent cohorts at three sites. Our statistical analysis plan was predefined before beginning data collection.

Background

White matter hyperintensities (WMH) that occur in the setting of vascular cognitive impairment and dementia (VCID) may be dynamic increasing or decreasing volumes or stable over time. Quantifying such changes may prove useful as a biomarker for clinical trials designed to address vascular cognitive-impairment and dementia and Alzheimer's Disease.

Objective

Conducting multi-site cross-site inter-rater and test-retest reliability of the MarkVCID white matter hyperintensity growth and regression protocol.

Methods

The NINDS-supported MarkVCID Consortium evaluated a neuroimaging biomarker developed to track WMH change. Test-retest and cross-site inter-rater reliability of the protocol were assessed. Cognitive test scores were analyzed in relation to WMH changes to explore its construct validity.

Results

ICC values for test-retest reliability of WMH growth and regression were 0.969 and 0.937 respectively, while for cross-site inter-rater ICC values for WMH growth and regression were 0.995 and 0.990 respectively. Word list long-delay free-recall was negatively associated with WMH growth (p < 0.028) but was not associated with WMH regression.

Conclusions

The present data demonstrate robust ICC validity of a WMH growth/regression protocol over a one-year period as measured by cross-site inter-rater and test-retest reliability. These data suggest that this approach may serve an important role in clinical trials of disease-modifying agents for VCID that may preferentially affect WMH growth, stability, or regression.

Importance

Most research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.

Objective

To identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.

Design, setting, and participants

Multicenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.

Exposure

SARS-CoV-2 infection.

Main outcomes and measures

PASC and 89 prolonged symptoms across 9 symptom domains.

Results

A total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.

Conclusions and relevance

This study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.