Distinct spatial contributions of amyloid pathology and cerebral small vessel disease to hippocampal morphology.

INTRODUCTION: Cerebral small vessel disease (SVD) and amyloid beta (Aß) pathology frequently co-exist. The impact of concurrent pathology on the pattern of hippocampal atrophy, a key substrate of memory impacted early and extensively in dementia, remains poorly understood. METHODS: In a unique cohort of mixed Alzheimer's disease and moderate-severe SVD, we examined whether total and regional neuroimaging measures of SVD, white matter hyperintensities (WMH), and Aß, as assessed by 18F-AV45 positron emission tomography, exert additive or synergistic effects on hippocampal volume and shape. RESULTS: Frontal WMH, occipital WMH, and Aß were independently associated with smaller hippocampal volume. Frontal WMH had a spatially distinct impact on hippocampal shape relative to Aß. In contrast, hippocampal shape alterations associated with occipital WMH spatially overlapped with Aß-vulnerable subregions. DISCUSSION: Hippocampal degeneration is differentially sensitive to SVD and Aß pathology. The pattern of hippocampal atrophy could serve as a disease-specific biomarker, and thus guide clinical diagnosis and individualized treatment strategies for mixed dementia.

Effect of MR head coil geometry on deep-learning-based MR image reconstruction.

PURPOSE: To investigate whether parallel imaging-imposed geometric coil constraints can be relaxed when using a deep learning (DL)-based image reconstruction method as opposed to a traditional non-DL method. THEORY AND METHODS: Traditional and DL-based MR image reconstruction approaches operate in fundamentally different ways: Traditional methods solve a system of equations derived from the image data whereas DL methods use data/target pairs to learn a generalizable reconstruction model. Two sets of head coil profiles were evaluated: (1) 8-channel and (2) 32-channel geometries. A DL model was compared to conjugate gradient SENSE (CG-SENSE) and L1-wavelet compressed sensing (CS) through quantitative metrics and visual assessment as coil overlap was increased. RESULTS: Results were generally consistent between experiments. As coil overlap increased, there was a significant (p < 0.001) decrease in performance in most cases for all methods. The decrease was most pronounced for CG-SENSE, and the DL models significantly outperformed (p < 0.001) their non-DL counterparts in all scenarios. CS showed improved robustness to coil overlap and signal-to-noise ratio (SNR) versus CG-SENSE, but had quantitatively and visually poorer reconstructions characterized by blurriness as compared to DL. DL showed virtually no change in performance across SNR and very small changes across coil overlap. CONCLUSION: The DL image reconstruction method produced images that were robust to coil overlap and of higher quality than CG-SENSE and CS. This suggests that geometric coil design constraints can be relaxed when using DL reconstruction methods.

Mismatch between clinically defined classification of ALS stage and the burden of cerebral pathology.

This study aimed to investigate the clinical stratification of amyotrophic lateral sclerosis (ALS) patients in relation to in vivo cerebral degeneration. One hundred forty-nine ALS patients and one hundred forty-four healthy controls (HCs) were recruited from the Canadian ALS Neuroimaging Consortium (CALSNIC). Texture analysis was performed on T1-weighted scans to extract the texture feature "autocorrelation" (autoc), an imaging biomarker of cerebral degeneration. Patients were stratified at baseline into early and advanced disease stages based on criteria adapted from ALS clinical trials and the King's College staging system, as well as into slow and fast progressors (disease progression rates, DPR). Patients had increased autoc in the internal capsule. These changes extended beyond the internal capsule in early-stage patients (clinical trial-based criteria), fast progressors, and in advanced-stage patients (King's staging criteria). Longitudinal increases in autoc were observed in the postcentral gyrus, corticospinal tract, posterior cingulate cortex, and putamen; whereas decreases were observed in corpus callosum, caudate, central opercular cortex, and frontotemporal areas. Both longitudinal increases and decreases of autoc were observed in non-overlapping regions within insula and precentral gyrus. Within-criteria comparisons of autoc revealed more pronounced changes at baseline and longitudinally in early- (clinical trial-based criteria) and advanced-stage (King's staging criteria) patients and fast progressors. In summary, comparative patterns of baseline and longitudinal progression in cerebral degeneration are dependent on sub-group selection criteria, with clinical trial-based stratification insufficiently characterizing disease stage based on pathological cerebral burden.

The relationship of small vessel disease burden on cerebral and regional brain atrophy rates and cognitive performance over one year of follow-up after transient ischemic attack.

Background: Stroke, even when minor, increases the risk of dementia. We aimed to determine whether patients with transient ischaemic attack (TIA) exhibit higher rates of cerebral and regional atrophy 1-year after first stroke symptoms and evaluate the relationship with small vessel disease and cognitive performance. Methods: TIA patients and controls without cognitive symptoms underwent high-resolution T1-weighted MRI and cognitive testing at baseline and 1-year. Percent brain volume change (PBVC) was measured, and the location of regional atrophy and small vessel disease (CSVD) burden was evaluated. Neuropsychological testing assessed memory, processing speed, and executive function. Results: A total of 76 TIA patients and 53 controls of mean age 67 (SD = 8) and 68 years (SD = 8) were recruited. TIA patients demonstrated greater improvement of visual memory and executive function at 1-year. TIA patients had greater median PBVC/year compared to controls (-0.79% [(-1.22)-(-0.38)] vs. -0.41% [(-0.62)-0.19]; p < 0.001), and higher rates of volume loss (ml/year) in subcortical gray (-0.53 [(-1.09)-(-0.06)] vs. -0.13 [(-0.61)-0.31]; p < 0.05) and white matter (-2.21 [-5.47, 0.40] vs. -0.93 [(-3.43)-2.10]; p < 0.05). Linear regression showed that TIA, age, and systolic blood pressure (SBP) were associated with greater cerebral volume loss over 1-year. There was no significant relationship between PBVC and 1-year cognition. Conclusion: A near two-fold increase in rate of cerebral atrophy 1-year after TIA is associated with higher SBP emphasizing the need for improved treatment of SBP. Cerebral and regional atrophy rates may be used to select patients for vascular risk reduction trials or novel therapeutics in future dementia prevention trials.

SF2Former: Amyotrophic lateral sclerosis identification from multi-center MRI data using spatial and frequency fusion transformer.

Amyotrophic Lateral Sclerosis (ALS) is a complex neurodegenerative disorder characterized by motor neuron degeneration. Significant research has begun to establish brain magnetic resonance imaging (MRI) as a potential biomarker to diagnose and monitor the state of the disease. Deep learning has emerged as a prominent class of machine learning algorithms in computer vision and has shown successful applications in various medical image analysis tasks. However, deep learning methods applied to neuroimaging have not achieved superior performance in classifying ALS patients from healthy controls due to insignificant structural changes correlated with pathological features. Thus, a critical challenge in deep models is to identify discriminative features from limited training data. To address this challenge, this study introduces a framework called SF2Former, which leverages the power of the vision transformer architecture to distinguish ALS subjects from the control group by exploiting the long-range relationships among image features. Additionally, spatial and frequency domain information is combined to enhance the network's performance, as MRI scans are initially captured in the frequency domain and then converted to the spatial domain. The proposed framework is trained using a series of consecutive coronal slices and utilizes pre-trained weights from ImageNet through transfer learning. Finally, a majority voting scheme is employed on the coronal slices of each subject to generate the final classification decision. The proposed architecture is extensively evaluated with multi-modal neuroimaging data (i.e., T1-weighted, R2*, FLAIR) using two well-organized versions of the Canadian ALS Neuroimaging Consortium (CALSNIC) multi-center datasets. The experimental results demonstrate the superiority of the proposed strategy in terms of classification accuracy compared to several popular deep learning-based techniques.

Neuroimaging standards for research into small vessel disease-advances since 2013.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Subcortical volumes in cerebral amyloid angiopathy compared with Alzheimer's disease and controls.

Background: Previous reports have suggested that patients with cerebral amyloid angiopathy (CAA) may harbor smaller white matter, basal ganglia, and cerebellar volumes compared to age-matched healthy controls (HC) or patients with Alzheimer's disease (AD). We investigated whether CAA is associated with subcortical atrophy. Methods: The study was based on the multi-site Functional Assessment of Vascular Reactivity cohort and included 78 probable CAA (diagnosed according to the Boston criteria v2.0), 33 AD, and 70 HC. Cerebral and cerebellar volumes were extracted from brain 3D T1-weighted MRI using FreeSurfer (v6.0). Subcortical volumes, including total white matter, thalamus, basal ganglia, and cerebellum were reported as proportion (%) of estimated total intracranial volume. White matter integrity was quantified by the peak width of skeletonized mean diffusivity. Results: Participants in the CAA group were older (74.0 ± 7.0, female 44%) than the AD (69.7 ± 7.5, female 42%) and HC (68.8 ± 7.8, female 69%) groups. CAA participants had the highest white matter hyperintensity volume and worse white matter integrity of the three groups. After adjusting for age, sex, and study site, CAA participants had smaller putamen volumes (mean differences, -0.024% of intracranial volume; 95% confidence intervals, -0.041% to -0.006%; p = 0.005) than the HCs but not AD participants (-0.003%; -0.024 to 0.018%; p = 0.94). Other subcortical volumes including subcortical white matter, thalamus, caudate, globus pallidus, cerebellar cortex or cerebellar white matter were comparable between all three groups. Conclusion: In contrast to prior studies, we did not find substantial atrophy of subcortical volumes in CAA compared to AD or HCs, except for the putamen. Differences between studies may reflect heterogeneity in CAA presenting syndromes or severity.

Brain iron content in cerebral amyloid angiopathy using quantitative susceptibility mapping.

Introduction: Cerebral amyloid angiopathy (CAA) is a small vessel disease that causes covert and symptomatic brain hemorrhaging. We hypothesized that persons with CAA would have increased brain iron content detectable by quantitative susceptibility mapping (QSM) on magnetic resonance imaging (MRI), and that higher iron content would be associated with worse cognition. Methods: Participants with CAA (n = 21), mild Alzheimer's disease with dementia (AD-dementia; n = 14), and normal controls (NC; n = 83) underwent 3T MRI. Post-processing QSM techniques were applied to obtain susceptibility values for regions of the frontal and occipital lobe, thalamus, caudate, putamen, pallidum, and hippocampus. Linear regression was used to examine differences between groups, and associations with global cognition, controlling for multiple comparisons using the false discovery rate method. Results: No differences were found between regions of interest in CAA compared to NC. In AD, the calcarine sulcus had greater iron than NC (ß = 0.99 [95% CI: 0.44, 1.53], q < 0.01). However, calcarine sulcus iron content was not associated with global cognition, measured by the Montreal Cognitive Assessment (p > 0.05 for all participants, NC, CAA, and AD). Discussion: After correcting for multiple comparisons, brain iron content, measured via QSM, was not elevated in CAA compared to NC in this exploratory study.

Arterial spin labelling reveals multi-regional cerebral hypoperfusion in patients with transient ischemic attack that are unrelated to ischemia location: A proof-of-concept study.

Background and Aims: Patients with transient ischemic attack (TIA) have a substantially increased risk of early dementia. In this exploratory study, we aim to determine whether patients with TIA have 1) measurable regional cerebral hypoperfusion unrelated to the location of ischemia, and 2) determine the relationship of regional cerebral blood flow (rCBF) with their cognitive profiles. Methods: Patients with TIA (N = 49) and seventy-nine (N = 79) age and sex matched controls underwent formal neuropsychological testing and MRI. Quantitative arterial spin labelling rCBF maps (mL/min/100 g) were registered to the corresponding high resolution T1-weighted image. Linear regression was used to determine the association between demographic, clinical and cognitive variables and rCBF. Results: Patients with TIA had significantly (p < 0.05) lower cognitive scores in the MMSE, MOCA, ACE-R, WAIS-IV DS Coding and Trail Making Tests A and B compared to controls. TIA patients had significantly lower rCBF in the left entorhinal cortex (p = 0.03), right posterior cingulate (p = 0.04), and right precuneus (p = 0.05), after adjusting for age and sex, that were unrelated to the regional anatomical volume and DWI positivity. Regional hypoperfusion in the right posterior cingulate and right precuneus was associated with impaired visual memory (BVMT total, p = 0.05 for both regions) and slower processing speed (TMT A, p = 0.04 and p = 0.01), respectively after adjusting for age and sex. Conclusions: TIA patients have patterns of regional hypoperfusion in multiple cortical regions unrelated to the parcellated regional anatomical volume or the presence of a DWI lesion. Regional hypoperfusion in patients with TIA may be an early marker conferring risk of future cognitive decline that needs to be confirmed by future studies.

Amyloid-PET of the white matter: Relationship to free water, fiber integrity, and cognition in patients with dementia and small vessel disease.

White matter (WM) injury is frequently observed along with dementia. Positron emission tomography with amyloid-ligands (Aß-PET) recently gained interest for detecting WM injury. Yet, little is understood about the origin of the altered Aß-PET signal in WM regions. Here, we investigated the relative contributions of diffusion MRI-based microstructural alterations, including free water and tissue-specific properties, to Aß-PET in WM and to cognition. We included a unique cohort of 115 participants covering the spectrum of low-to-severe white matter hyperintensity (WMH) burden and cognitively normal to dementia. We applied a bi-tensor diffusion-MRI model that differentiates between (i) the extracellular WM compartment (represented via free water), and (ii) the fiber-specific compartment (via free water-adjusted fractional anisotropy [FA]). We observed that, in regions of WMH, a decrease in Aß-PET related most closely to higher free water and higher WMH volume. In contrast, in normal-appearing WM, an increase in Aß-PET related more closely to higher cortical Aß (together with lower free water-adjusted FA). In relation to cognitive impairment, we observed a closer relationship with higher free water than with either free water-adjusted FA or WM PET. Our findings support free water and Aß-PET as markers of WM abnormalities in patients with mixed dementia, and contribute to a better understanding of processes giving rise to the WM PET signal.

Can quantitative susceptibility mapping help diagnose and predict recovery of concussion in children? An A-CAP study.

BACKGROUND: Quantitative susceptibility mapping (QSM) is an MRI technique that is a potential biomarker for concussion. We performed QSM in children following concussion or orthopaedic injury (OI), to assess QSM performance as a diagnostic and prognostic biomarker. METHODS: Children aged 8-17 years with either concussion (N=255) or OI (N=116) were recruited from four Canadian paediatric emergency departments and underwent QSM postacutely (2-33 days postinjury) using 3 Tesla MRI. QSM Z-scores within nine regions of interest (ROI) were compared between groups. QSM Z-scores were also compared with the 5P score, the current clinical benchmark for predicting persistent postconcussion symptoms (PPCS), at 4 weeks postinjury, with PPCS defined using reliable change methods based on both participant and parent reports. RESULTS: Concussion and OI groups did not differ significantly in QSM Z-scores for any ROI. Higher QSM Z-scores within frontal white matter (WM) independently predicted PPCS based on parent ratings of cognitive symptoms (p=0.001). The combination of frontal WM QSM Z-score and 5P score was better at predicting PPCS than 5P score alone (p=0.004). The area under the curve was 0.72 (95% CI 0.63 to 0.81) for frontal WM susceptibility, 0.69 (95% CI 0.59 to 0.79) for the 5P score and 0.74 (95% CI 0.65 to 0.83) for both. CONCLUSION: The findings suggest that QSM is a potential MRI biomarker that can help predict PPCS in children with concussion, over and above the current clinical benchmark, and thereby aid in clinical management. They also suggest a frontal lobe substrate for PPCS, highlighting the potential for QSM to clarify the neurophysiology of paediatric concussion.

Motor cortex functional connectivity is associated with underlying neurochemistry in ALS.

OBJECTIVE: To identify structural and neurochemical properties that underlie functional connectivity impairments of the primary motor cortex (PMC) and how these relate to clinical findings in amyotrophic lateral sclerosis (ALS). METHODS: 52 patients with ALS and 52 healthy controls, matched for age and sex, were enrolled from 5 centres across Canada for the Canadian ALS Neuroimaging Consortium study. Resting-state functional MRI, diffusion tensor imaging and magnetic resonance spectroscopy data were acquired. Functional connectivity maps, diffusion metrics and neurometabolite ratios were obtained from the analyses of the acquired multimodal data. A clinical assessment of foot tapping (frequency) was performed to examine upper motor neuron function in all participants. RESULTS: Compared with healthy controls, the primary motor cortex in ALS showed reduced functional connectivity with sensory (T=5.21), frontal (T=3.70), temporal (T=3.80), putaminal (T=4.03) and adjacent motor (T=4.60) regions. In the primary motor cortex, N-acetyl aspartate (NAA, a neuronal marker) ratios and diffusion metrics (mean, axial and radial diffusivity, fractional anisotropy (FA)) were altered. Within the ALS cohort, foot tapping frequency correlated with NAA (r=0.347) and white matter FA (r=0.537). NAA levels showed associations with disturbed functional connectivity of the motor cortex. CONCLUSION: In vivo neurochemistry may represent an effective imaging marker of impaired motor cortex functional connectivity in ALS.

Vascular burden and cognition: Mediating roles of neurodegeneration and amyloid PET.

It remains unclear to what extent cerebrovascular burden relates to amyloid beta (Aß) deposition, neurodegeneration, and cognitive dysfunction in mixed disease populations with small vessel disease and Alzheimer's disease (AD) pathology. In 120 subjects, we investigated the association of vascular burden (white matter hyperintensity [WMH] volumes) with cognition. Using mediation analyses, we tested the indirect effects of WMH on cognition via Aß deposition (18 F-AV45 positron emission tomography [PET]) and neurodegeneration (cortical thickness or 18 F fluorodeoxyglucose PET) in AD signature regions. We observed that increased total WMH volume was associated with poorer performance in all tested cognitive domains, with the strongest effects observed for semantic fluency. These relationships were mediated mainly via cortical thinning, particularly of the temporal lobe, and to a lesser extent serially mediated via Aß and cortical thinning of AD signature regions. WMH volumes differentially impacted cognition depending on lobar location and Aß status. In summary, our study suggests mainly an amyloid-independent pathway in which vascular burden affects cognitive function via localized neurodegeneration. HIGHLIGHTS: Alzheimer's disease often co-exists with vascular pathology. We studied a unique cohort enriched for high white matter hyperintensities (WMH). High WMH related to cognitive impairment of semantic fluency and executive function. This relationship was mediated via temporo-parietal atrophy rather than metabolism. This relationship was, to lesser extent, serially mediated via amyloid beta and atrophy.

Vascular Brain Lesions, Cognitive Reserve, and Their Association with Cognitive Profile in Persons with Early-Stage Cognitive Decline.

Background: Cognitive reserve may protect against the effects of brain pathology, but few studies have looked at whether cognitive reserve modifies the adverse effects of vascular brain pathology. Objective: We determined if cognitive reserve attenuates the associations of vascular brain lesions with worse cognition in persons with subjective concerns or mild impairment. Methods: We analyzed 200 participants aged 50-90 years from the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study. Cognition was measured using the Montreal Cognitive Assessment and a neuropsychological test battery. High vascular lesion burden was defined as two or more supratentorial infarcts or beginning confluent or confluent white matter hyperintensity. Cognitive reserve proxies included education, occupational attainment, marital status, social activities, physical activity, household income, and multilingualism. Results: Mean age was 72.8 years and 48% were female; 73.5% had mild cognitive impairment and 26.5% had subjective concerns. Professional/managerial occupations, annual household income≥$60,000 per year, not being married/common law, and high physical activity were independently associated with higher cognition. Higher vascular lesion burden was associated with lower executive function, but the association was not modified by cognitive reserve. Conclusion: Markers of cognitive reserve are associated with higher cognition. Vascular lesion burden is associated with lower executive function. However, cognitive reserve does not mitigate the effects of vascular lesion burden on executive function. Public health efforts should focus on preventing vascular brain injury as well as promoting lifestyle factors related to cognitive reserve, as cognitive reserve alone may not mitigate the effects of vascular brain injury.

Multi-Coil MRI Reconstruction Challenge-Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations.

Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process. Nevertheless, the scientific community lacks appropriate benchmarks to assess the MRI reconstruction quality of high-resolution brain images, and evaluate how these proposed algorithms will behave in the presence of small, but expected data distribution shifts. The multi-coil MRI (MC-MRI) reconstruction challenge provides a benchmark that aims at addressing these issues, using a large dataset of high-resolution, three-dimensional, T1-weighted MRI scans. The challenge has two primary goals: (1) to compare different MRI reconstruction models on this dataset and (2) to assess the generalizability of these models to data acquired with a different number of receiver coils. In this paper, we describe the challenge experimental design and summarize the results of a set of baseline and state-of-the-art brain MRI reconstruction models. We provide relevant comparative information on the current MRI reconstruction state-of-the-art and highlight the challenges of obtaining generalizable models that are required prior to broader clinical adoption. The MC-MRI benchmark data, evaluation code, and current challenge leaderboard are publicly available. They provide an objective performance assessment for future developments in the field of brain MRI reconstruction.

Short-term repeatability and long-term reproducibility of quantitative MR imaging biomarkers in a single centre longitudinal study.

Quantitative imaging biomarkers (QIBs) can be defined as objective measures that are sensitive and specific to changes in tissue physiology. Provided the acquired QIBs are not affected by scanner changes, they could play an important role in disease diagnosis, prognosis, management, and treatment monitoring. The precision of selected QIBs was assessed from data collected on a 3-T scanner in four healthy participants over a 5-year period. Inevitable scanner changes and acquisition protocol revisions occurred during this time. Standard and custom processing pipelines were used to calculate regional brain volume, cortical thickness, T2, T2*, quantitative susceptibility, cerebral blood flow, axial, radial and mean diffusivity, peak width of skeletonized mean diffusivity, and fractional anisotropy from the acquired images. Coefficient of variation (CoV) and intra-class correlation (ICC) indices were determined in the short-term (i.e., repeatable over three acquisitions within 4 weeks) and in the long-term (i.e., reproducible over four acquisition sessions in 5 years). Precision indices varied based on acquisition technique, processing pipeline, and anatomical region. Good repeatability (average CoV=2.40% and ICC=0.78) and reproducibility (average CoV=8.86 % and ICC=0.72) were found over all QIBs. The best performance indices were obtained for diffusion derived biomarkers (CoV∼0.96% and ICCs=0.87); conversely, the poorest indices were found for the cerebral blood flow biomarker (CoV>10% and ICC<0.5). These results demonstrate that changes in protocol, along with hardware and software upgrades, did not affect the estimates of the selected biomarkers and their precision. Further characterization of the QIB is necessary to understand meaningful changes in the biomarkers in longitudinal studies of normal brain aging and translation to clinical research.

Functional alterations in large-scale resting-state networks of amyotrophic lateral sclerosis: A multi-site study across Canada and the United States.

Amyotrophic lateral sclerosis (ALS) is a multisystem neurodegenerative disorder characterized by progressive degeneration of upper motor neurons and lower motor neurons, and frontotemporal regions resulting in impaired bulbar, limb, and cognitive function. Magnetic resonance imaging studies have reported cortical and subcortical brain involvement in the pathophysiology of ALS. The present study investigates the functional integrity of resting-state networks (RSNs) and their importance in ALS. Intra- and inter-network resting-state functional connectivity (Rs-FC) was examined using an independent component analysis approach in a large multi-center cohort. A total of 235 subjects (120 ALS patients; 115 healthy controls (HC) were recruited across North America through the Canadian ALS Neuroimaging Consortium (CALSNIC). Intra-network and inter-network Rs-FC was evaluated by the FSL-MELODIC and FSLNets software packages. As compared to HC, ALS patients displayed higher intra-network Rs-FC in the sensorimotor, default mode, right and left fronto-parietal, and orbitofrontal RSNs, and in previously undescribed networks including auditory, dorsal attention, basal ganglia, medial temporal, ventral streams, and cerebellum which negatively correlated with disease severity. Furthermore, ALS patients displayed higher inter-network Rs-FC between the orbitofrontal and basal ganglia RSNs which negatively correlated with cognitive impairment. In summary, in ALS there is an increase in intra- and inter-network functional connectivity of RSNs underpinning both motor and cognitive impairment. Moreover, the large multi-center CALSNIC dataset permitted the exploration of RSNs in unprecedented detail, revealing previously undescribed network involvement in ALS.

Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads.

Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2 *) mapping from multiecho T2 *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R2 * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R2 * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R2 * were highly correlated (R2 ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R2 *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s-1 for R2 *. For within-site measurements of QSM and R2 *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s-1 , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.

Lifespan Volume Trajectories From Non-harmonized T1-Weighted MRI Do Not Differ After Site Correction Based on Traveling Human Phantoms.

Multi-site imaging consortiums strive to increase participant numbers by pooling data across sites, but scanner related differences can bias results. This study combines data from three research MRI centers, including three different scanner models from two vendors, to examine non-harmonized T1-weighted brain imaging protocols in two cohorts. First, 23 human traveling phantoms were scanned twice each at all three sites (six scans per person; 138 scans total) to quantify within-participant variability of brain volumes (total brain, white matter, gray matter, lateral ventricles, thalamus, caudate, putamen and globus pallidus), and to calculate site-specific correction factors for each structure. Sample size calculations were used to determine the number of traveling phantoms needed to achieve effect sizes for observed differences to help guide future studies. Next, cross-sectional lifespan volume trajectories were examined in 856 healthy participants (5-91 years of age) scanned at these sites. Cross-sectional trajectories of volume versus age for each structure were then compared before and after application of traveling phantom based site-specific correction factors, as well as correction using the open-source method ComBat. Although small systematic differences between sites were observed in the traveling phantom analysis, correction for site using either method had little impact on the lifespan trajectories. Only white matter had small but significant differences in the intercept parameter after ComBat correction (but not traveling phantom based correction), while no other fits differed. This suggests that age-related changes over the lifespan outweigh systematic differences between scanners for volumetric analysis. This work will help guide pooling of multisite datasets as well as meta-analyses of data from non-harmonized protocols.

Cerebrovascular Reactivity Across the Entire Brain in Cerebral Amyloid Angiopathy.

BACKGROUND AND OBJECTIVES: Reduced cerebrovascular reactivity is proposed to be a feature of cerebral amyloid angiopathy (CAA) but has not been measured directly. Employing a global vasodilatory stimulus (hypercapnia), this study assessed the relationships between cerebrovascular reactivity and MRI markers of CAA and cognitive function. METHODS: In a cross-sectional study, individuals with probable CAA, mild cognitive impairment, or dementia due to Alzheimer disease and healthy controls underwent neuropsychological testing and an MRI that included a 5% carbon dioxide challenge. Cerebrovascular reactivity was compared across groups controlling for age, sex, and the presence of hypertension, and its associations with MRI markers of CAA in participants with CAA and with cognition across all participants were determined using multivariable linear regression adjusting for group, age, sex, education, and the presence of hypertension. RESULTS: Cerebrovascular reactivity data (mean ± SD) were available for 26 participants with CAA (9 female; 74.4 ± 7.7 years), 19 participants with mild cognitive impairment (5 female; 72.1 ± 8.5 years), 12 participants with dementia due to Alzheimer disease (4 female; 69.4 ± 6.6 years), and 39 healthy controls (30 female; 68.8 ± 5.4 years). Gray and whiter matter reactivity averaged across the entire brain was lower in participants with CAA and Alzheimer disease dementia compared to healthy controls, with a predominantly posterior distribution of lower reactivity in both groups. Higher white matter hyperintensity volume was associated with lower white matter reactivity (standardized coefficient [ß], 95% CI -0.48, -0.90 to -0.01). Higher gray matter reactivity was associated with better global cognitive function (ß 0.19, 0.03-0.36), memory (ß 0.21, 0.07-0.36), executive function (ß 0.20, 0.02-0.39), and processing speed (ß 0.27, 0.10-0.45) and higher white matter reactivity was associated with higher memory (ß 0.22, 0.08-0.36) and processing speed (ß 0.23, 0.06-0.40). CONCLUSIONS: Reduced cerebrovascular reactivity is a core feature of CAA and its assessment may provide an additional biomarker for disease severity and cognitive impairment.