An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data

Changes in cerebrovascular reactivity within functional networks in older adults with long-COVID

Introduction

Cognitive symptoms are reported in the vast majority of individuals with long-COVID and there is growing support to suggest neurovascular mechanisms may play a role. Older adults are at increased risk for developing complications associated with COVID-19, including heightened risk for cognitive decline. Cerebrovascular Reactivity (CVR), a marker of neurovascular health, has been linked to age related cognitive decline and may play a role in long-COVID, however, this has not yet been explored.

Methods

The present study examined group differences in CVR in 31 older adults with long-COVID compared to 31 cognitively unimpaired older adults without long-COVID symptoms. Follow up analyses were conducted to examine how CVR was associated with both subjective cognitive symptoms and neuropsychological (NP) test performance. A subject-specific approach, Distribution-Corrected Z-scores (DisCo-Z), was used.

Results

Analyses revealed the long-COVID group demonstrated significantly greater incidence of extreme CVR clusters within the brain (>100 voxels) and within functional networks thought to drive attention and executive function. Extreme positive CVR clusters were positively associated with greater number of subjective cognitive symptoms and negatively correlated with NP performance.

Discussion

These findings are among the first to provide a link between cognitive functioning in long-COVID and neurovascular changes relevant for aging and mechanistic studies of long-COVID.

Rate of abnormalities in quantitative MR neuroimaging of persons with chronic traumatic brain injury

BACKGROUND

Mild traumatic brain injury (mTBI) can result in lasting brain damage that is often too subtle to detect by qualitative visual inspection on conventional MR imaging. Although a number of FDA-cleared MR neuroimaging tools have demonstrated changes associated with mTBI, they are still under-utilized in clinical practice.

METHODS

We investigated a group of 65 individuals with predominantly mTBI (60 mTBI, 48 due to motor-vehicle collision, mean age 47 ± 13 years, 27 men and 38 women) with MR neuroimaging performed in a median of 37 months post-injury. We evaluated abnormalities in brain volumetry including analysis of left-right asymmetry by quantitative volumetric analysis, cerebral perfusion by pseudo-continuous arterial spin labeling (PCASL), white matter microstructure by diffusion tensor imaging (DTI), and neurometabolites via magnetic resonance spectroscopy (MRS).

RESULTS

All participants demonstrated atrophy in at least one lobar structure or increased lateral ventricular volume. The globus pallidi and cerebellar grey matter were most likely to demonstrate atrophy and asymmetry. Perfusion imaging revealed significant reductions of cerebral blood flow in both occipital and right frontoparietal regions. Diffusion abnormalities were relatively less common though a subset analysis of participants with higher resolution DTI demonstrated additional abnormalities. All participants showed abnormal levels on at least one brain metabolite, most commonly in choline and N-acetylaspartate.

CONCLUSION

We demonstrate the presence of coup-contrecoup perfusion injury patterns, widespread atrophy, regional brain volume asymmetry, and metabolic aberrations as sensitive markers of chronic mTBI sequelae. Our findings expand the historic focus on quantitative imaging of mTBI with DTI by highlighting the complementary importance of volumetry, arterial spin labeling perfusion and magnetic resonance spectroscopy neurometabolite analyses in the evaluation of chronic mTBI.

Longitudinal Brain Perfusion and Symptom Presentation Following Pediatric Concussion: A Pediatric Concussion Assessment of Rest and Exertion+MRI (PedCARE+MRI) Substudy

Emerging evidence suggests that advanced neuroimaging modalities such as arterial spin labelling (ASL) might have prognostic utility for pediatric concussion. This study aimed to: 1) examine group differences in global and regional brain perfusion in youth with concussion or orthopedic injury (OI) at 72 h and 4 weeks post-injury; 2) examine patterns of abnormal brain perfusion within both groups and their recovery; 3) investigate the association between perfusion and symptom burden within concussed and OI youths at both time-points; and 4) explore perfusion between symptomatic and asymptomatic concussed and OI youths. Youths ages 10.00-17.99 years presenting to the emergency department with an acute concussion or OI were enrolled. ASL-magnetic resonance imaging scans were conducted at 72 h and 4 weeks post-injury to measure brain perfusion, along with completion of the Health Behavior Inventory (HBI) to measure symptoms. Abnormal perfusion clusters were identified using voxel-based z-score analysis at each visit. First, mixed analyses of covariance (ANCOVAs) investigated the Group*Time interaction on global and regional perfusion. Post hoc region of interest (ROI) analyses were performed on significant regions. Second, within-group generalized estimating equations investigated the recovery of abnormal perfusion at an individual level. Third, multiple regressions at each time-point examined the association between HBI and regional perfusion, and between HBI and abnormal perfusion volumes within the concussion group. Fourth, whole-brain one-way ANCOVAs explored differences in regional and abnormal perfusion based on symptomatic status (symptomatic vs. asymptomatic) and OIs at each time-point. A total of 70 youths with a concussion [median age (interquartile range; IQR) = 12.70 (11.67-14.35), 47.1% female] and 29 with an OI [median age (IQR) = 12.05 (11.18-13.89), 41.4% female] were included. Although no Group effect was found in global perfusion, the concussion group showed greater adjusted perfusion within the anterior cingulate cortex/middle frontal gyrus (MFG) and right MFG compared with the OI group across time-points (ps ≤ 0.004). The concussion group showed lower perfusion within the right superior temporal gyrus at both time-points and bilateral occipital gyrus at 4 weeks, (ps ≤ 0.006). The number of hypoperfused clusters was increased at 72 h compared with 4 weeks in the concussion youths (p < 0.001), but not in the OIs. Moreover, Group moderated the HBI-perfusion association within the left precuneus and superior frontal gyrus at both time-points, (ps ≤ 0.001). No association was found between HBI and abnormal perfusion volume within the concussion group at any visits. At 4 weeks, the symptomatic sub-group (n = 10) showed lower adjusted perfusion within the right cerebellum and lingual gyrus, while the asymptomatic sub-group (n = 59) showed lower adjusted perfusion within the left calcarine, but greater perfusion within the left medial orbitofrontal cortex, right middle frontal gyrus, and bilateral caudate compared with OIs. Yet, no group differences were observed in the number of abnormal perfusion clusters or volumes at any visit. The present study suggests that symptoms may be associated with changes in regional perfusion, but not abnormal perfusion levels.

Comparison of automated and manual quantification methods for neuromelanin-sensitive MRI in Parkinson's disease

Neuromelanin-sensitive magnetic resonance imaging quantitative analysis methods have provided promising biomarkers that can noninvasively quantify degeneration of the substantia nigra in patients with Parkinson's disease. However, there is a need to systematically evaluate the performance of manual and automated quantification approaches. We evaluate whether spatial, signal-intensity, or subject specific abnormality measures using either atlas based or manually traced identification of the substantia nigra better differentiate patients with Parkinson's disease from healthy controls using logistic regression models and receiver operating characteristics. Inference was performed using bootstrap analyses to calculate 95% confidence interval bounds. Pairwise comparisons were performed by generating 10,000 permutations, refitting the models, and calculating a paired difference between metrics. Thirty-one patients with Parkinson's disease and 22 healthy controls were included in the analyses. Signal intensity measures significantly outperformed spatial and subject specific abnormality measures, with the top performers exhibiting excellent ability to differentiate patients with Parkinson's disease and healthy controls (balanced accuracy = 0.89; area under the curve = 0.81; sensitivity =0.86; and specificity = 0.83). Atlas identified substantia nigra metrics performed significantly better than manual tracing metrics. These results provide clear support for the use of automated signal intensity metrics and additional recommendations. Future work is necessary to evaluate whether the same metrics can best differentiate atypical parkinsonism, perform similarly in de novo and mid-stage cohorts, and serve as longitudinal monitoring biomarkers.

Registration quality filtering improves robustness of voxel-wise analyses to the choice of brain template

Motivation:

Many clinical and scientific conclusions that rely on voxel-wise analyses of neuroimaging depend on the accurate comparison of corresponding anatomical regions. Such comparisons are made possible by registration of the images of subjects of interest onto a common brain template, such as the Johns Hopkins University (JHU) template. However, current image registration algorithms are prone to errors that are distributed in a template-dependent manner. Therefore, the results of voxel-wise analyses can be sensitive to template choice. Despite this problem, the issue of appropriate template choice for voxel-wise analyses is not generally addressed in contemporary neuroimaging studies, which may lead to the reporting of spurious results.

Results:

We present a novel approach to determine the suitability of a brain template for voxel-wise analysis. The approach is based on computing a “distance” between automatically-generated atlases of the subjects of interest and templates that is indicative of the extent of subject-to-template registration errors. This allows for the filtering of subjects and candidate templates based on a quantitative measure of registration quality. We benchmark our approach by evaluating alternative templates for a voxel-wise analysis that reproduces the well-known decline in fractional anisotropy (FA) with age. Our results show that filtering registrations minimizes errors and decreases the sensitivity of voxel-wise analysis to template choice. In addition to carrying important implications for future neuroimaging studies, the developed framework of template induction can be used to evaluate robustness of data analysis methods to template choice.

Joint analysis of frontal theta synchrony and white matter following mild traumatic brain injury

Some of the most disabling aspects of mild traumatic brain injury (mTBI) include lingering deficits in executive functioning. It is known that mTBI can damage white matter tracts, but it remains unknown how this structural brain damage translates into cognitive deficits. This experiment utilized theta band phase synchrony to identify the dysfunctional neural operations that contribute to cognitive problems following mTBI. Sub-acute stage (< 2 weeks) mTBI patients (N = 52) and healthy matched controls (N = 32) completed a control-demanding task with concurrent EEG. Structural MRI was also collected. While there were no performance-specific behavioral differences between groups in the dot probe expectancy task, the degree of theta band phase synchrony immediately following injury predicted the degree of symptom recovery two months later. Although there were no differences in fractional anisotropy (FA) between groups, joint independent components analysis revealed that a smaller network of lower FA-valued voxels contributed to a diminished frontal theta phase synchrony network in the mTBI group. This finding suggests that frontal theta band markers of cognitive control are sensitive to sub-threshold structural aberrations following mTBI.

Resting-State fMRI Metrics in Acute Sport-Related Concussion and Their Association with Clinical Recovery: A Study from the NCAA-DOD CARE Consortium

There has been a recent call for longitudinal cohort studies to track the physiological recovery of sport-related concussion (SRC) and its relationship with clinical recovery. Resting-state functional magnetic resonance imaging (rs-fMRI) has shown potential for detecting subtle changes in brain function after SRC. We investigated the effects of SRC on rs-fMRI metrics assessing local connectivity (regional homogeneity; REHO), global connectivity (average nodal strength), and the relative amplitude of slow oscillations of rs-fMRI (fractional amplitude of low-frequency fluctuations; fALFF). Athletes diagnosed with SRC (n = 92) completed visits with neuroimaging at 24-48 h post-injury (24 h), after clearance to begin the return-to-play (RTP) progression (asymptomatic), and 7 days following unrestricted RTP (post-RTP). Non-injured athletes (n = 82) completed visits yoked to the schedule of matched injured athletes and served as controls. Concussed athletes had elevated symptoms, worse neurocognitive performance, greater balance deficits, and elevated psychological symptoms at the 24-h visit relative to controls. These deficits were largely recovered by the asymptomatic visit. Concussed athletes still reported elevated psychological symptoms at the asymptomatic visit relative to controls. Concussed athletes also had elevated REHO in the right middle and superior frontal gyri at the 24-h visit that returned to normal levels by the asymptomatic visit. Additionally, REHO in these regions at 24 h predicted psychological symptoms at the asymptomatic visit in concussed athletes. Current results suggest that SRC is associated with an acute alteration in local connectivity that follows a similar time course as clinical recovery. Our results do not indicate strong evidence that concussion-related alterations in rs-fMRI persist beyond clinical recovery.

Spatial distribution bias in subject-specific abnormalities analyses

The neuroimaging community has seen a renewed interest in algorithms that provide a location-independent summary of subject-specific abnormalities (SSA) to assess individual lesion load. More recently, these methods have been extended to assess whether multiple individuals within the same cohort exhibit extrema in the same spatial location (e.g., voxel or region of interest). However, the statistical validity of this approach has not been rigorously established. The current study evaluated the potential for a spatial bias in the distribution of SSA using several common z-transformation algorithms (leave-one-out [LOO]; independent sample [IDS]; Enhanced Z-Score Microstructural Assessment of Pathology [EZ-MAP]; distribution-corrected z-scores [DisCo-Z]) using both simulated data and DTI data from 50 healthy controls. Results indicated that methods which z-transformed data based on statistical moments from a reference group (LOO, DisCo-Z) led to bias in the spatial location of extrema for the comparison group. In contrast, methods that z-transformed data using an independent third group (EZ-MAP, IDS) resulted in no spatial bias. Importantly, none of the methods exhibited bias when results were summed across all individual elements. The spatial bias is primarily driven by sampling error, in which differences in the mean and standard deviation of the untransformed data have a higher probability of producing extrema in the same spatial location for the comparison but not reference group. In conclusion, evaluating SSA overlap within cohorts should be either be avoided in deference to established group-wise comparisons or performed only when data is available from an independent third group.