Gray Matter Regions Of Interest Research Articles

Kinetic modeling of 18 F-PI-2620 binding in the brain using an image-derived input function with total-body PET.

Accurate quantification of tau binding from 18 F-PI-2620 PET requires kinetic modeling and an input function. Here, we implemented a non-invasive Image-derived input function (IDIF) derived using the state-of-the-art total-body uEXPLORER PET/CT scanner to quantify tau binding and tracer delivery rate from 18 F-PI-2620 in the brain. Additionally, we explored the impact of scan duration on the quantification of kinetic parameters. Total-body PET dynamic data from 15 elderly participants were acquired. Time-activity curves from the grey matter regions of interest (ROIs) were fitted to the two-tissue compartmental model (2TCM) using a subject-specific IDIF derived from the descending aorta. ROI-specific kinetic parameters were estimated for different scan durations ranging from 10 to 90 minutes. Logan graphical analysis was also used to estimate the total distribution volume (V T ). Differences in kinetic parameters were observed between ROIs, including significant reduction in tracer delivery rate (K 1 ) in the medial temporal lobe. All kinetic parameters remained relatively stable after the 60-minute scan window across all ROIs, with K 1 showing high stability after 30 minutes of scan duration. Excellent correlation was observed between V T estimated using 2TCM and Logan plot analysis. This study demonstrated the utility of IDIF with total-body PET in investigating 18 F-PI-2620 kinetics in the brain.

Neural Correlates of Obesity and Inflammation in Children and Adolescents with Congenital Adrenal Hyperplasia

Introduction: Patients with classical congenital adrenal hyperplasia (CAH) exhibit an increased prevalence of obesity from childhood including central adiposity and inflammation. There is also an emerging affected brain phenotype in CAH, with decreased cortico-limbic gray matter volumes and white matter abnormalities. We aimed to study the relationship between brain structure, obesity, and inflammation in children and adolescents with CAH compared to controls. Methods: 27 CAH (12.6 ± 3.4 y, 16 females) and 35 control (13.0 ± 2.8 y, 20 females) participants had MRI of gray matter regions of interest (prefrontal cortex [PFC], amygdala, hippocampus) and white matter microstructure (fornix, stria terminalis [ST]). Anthropometric measures and lab analytes were obtained. Relaimpo analyses (relative importance for linear regression; percent variance) identified which brain structures were most different between groups. Subsequent regressions further quantified the magnitude and direction of these relationships. Correlations analyzed relationships between brain structure, obesity, and inflammation in the context of CAH status. Results: PFC (13.3% variance) and its superior frontal (SF) subregion (14%) were most different between CAH and controls for gray matter; ST (16%) for white matter. Patients with CAH had lower caudal middle frontal (β = −0.56 [−0.96, −0.15]) and superior frontal (β = −0.58 [−0.92, −0.25]) subregion volumes, increased orientation dispersion index in the fornix (β = 0.56 [0.01, 1.10]) and ST (β = 0.85 [0.34, 1.36]), and decreased fractional anisotropy in the fornix (β = −0.91 [−1.42, −0.42]) and ST (β = −0.83 [−1.34, −0.33]) (all p’s r = −0.41), visceral adipose tissue (r = −0.25), and waist-to-height ratio (r = −0.27, all p’s r = 0.31) and TNF-α (r = 0.29, all p’s Conclusions: Relationships among key brain structures, body composition, and inflammatory markers in pediatric patients with CAH could be largely driven by having CAH, with implications for obesity and neuroinflammation in this high-risk population.

Tau‐neurodegeneration mismatch from inter‐modality image translation using deep learning

AbstractBackgroundThe relationship between tau neurofibrillary tangles (T) and neurodegeneration (N) may offer clues to potential presence of comorbidities, as well as relative resilience and vulnerability to Alzheimer’s disease (AD) pathology. We have previously developed measures of tau PET (T) and cortical thickness (N) mismatch based on linear model residuals. However, the underlying relationships between T and N are likely complex and non‐linear. Moreover, predicting cortical thickness based on local tau level may miss non‐local contributions of tauopathy. Here we investigate T‐N mismatch using a deep‐learning 3D image translation neural network to estimate synthetic maps of cortical thickness based on tau PET images. Deviation between the synthetic and actual cortical thickness serves as a metric of T‐N mismatch.MethodWe derived 3D cortical thickness from T1‐MRI and SUVR from 18F‐flortaucipir tracer uptake to represent N and T maps respectively. We predicted cortical thickness maps from tau SUVR by training a 3D U‐Net (Ronneberger et al. 2015) to learn the relationship between paired cortical tau SUVR and thickness maps from 70 symptomatic patients from ADNI. Approximately 70% of the training set was A+. We used regional standardized mean absolute error between predicted and actual thickness across 104 bilateral gray matter regions of interest as T‐N mismatch for clustering in a separate independent sample of 194 A+ symptomatic patients.ResultThe voxel‐wise mean absolute error of thickness translation on 194 tested patients was 0.54 mm. We obtained six T‐N data‐driven clusters (Figure 2). The group with lowest reconstruction error was defined as canonical – meaning that the degree of neurodegeneration was accurately predicted by tau PET. There were three groups with lower thickness than predicted, which were denoted as temporal‐limbic (TL) vulnerable, posterior vulnerable and diffuse vulnerable based on their spatial patterns. Additionally, two groups with greater thickness than predicted were defined as anterior resilient and diffuse resilient. These groups differed in subsequent longitudinal cognitive decline measured by CDR‐SB (Figure 3). The vulnerable groups displayed greater cognitive decline than the canonical group, which may be attributable to associations with comorbidities.ConclusionOur findings support a deep‐learning T‐N mismatch approach for disentangling AD heterogeneity.

Tau‐neurodegeneration mismatch from inter‐modality image translation using deep learning

AbstractBackgroundThe relationship between tau neurofibrillary tangles (T) and neurodegeneration (N) may offer clues to potential presence of comorbidities, as well as relative resilience and vulnerability to Alzheimer’s disease (AD) pathology. We have previously developed measures of tau PET (T) and cortical thickness (N) mismatch based on linear model residuals. However, the underlying relationships between T and N are likely complex and non‐linear. Moreover, predicting cortical thickness based on local tau level may miss non‐local contributions of tauopathy. Here we investigate T‐N mismatch using a deep‐learning 3D image translation neural network to estimate synthetic maps of cortical thickness based on tau PET images. Deviation between the synthetic and actual cortical thickness serves as a metric of T‐N mismatch.MethodWe derived 3D cortical thickness from T1‐MRI and SUVR from 18F‐flortaucipir tracer uptake to represent N and T maps respectively. We predicted cortical thickness maps from tau SUVR by training a 3D U‐Net (Ronneberger et al. 2015) to learn the relationship between paired cortical tau SUVR and thickness maps from 70 symptomatic patients from ADNI. Approximately 70% of the training set was A+. We used regional standardized mean absolute error between predicted and actual thickness across 104 bilateral gray matter regions of interest as T‐N mismatch for clustering in a separate independent sample of 194 A+ symptomatic patients.ResultThe voxel‐wise mean absolute error of thickness translation on 194 tested patients was 0.54 mm. We obtained six T‐N data‐driven clusters (Figure 2). The group with lowest reconstruction error was defined as canonical – meaning that the degree of neurodegeneration was accurately predicted by tau PET. There were three groups with lower thickness than predicted, which were denoted as temporal‐limbic (TL) vulnerable, posterior vulnerable and diffuse vulnerable based on their spatial patterns. Additionally, two groups with greater thickness than predicted were defined as anterior resilient and diffuse resilient. These groups differed in subsequent longitudinal cognitive decline measured by CDR‐SB (Figure 3). The vulnerable groups displayed greater cognitive decline than the canonical group, which may be attributable to associations with comorbidities.ConclusionOur findings support a deep‐learning T‐N mismatch approach for disentangling AD heterogeneity.

Cognitive status modifies the association between elevated cerebrospinal fluid phosphorylated tau and longitudinal cerebral blood flow changes over a 7‐year follow‐up period

AbstractBackgroundAlzheimer’s disease (AD) is associated with widespread reductions in cerebral blood flow (CBF), but the precise link between AD pathology and CBF is unclear. Hypoperfusion is a late‐stage event associated with tau, but not amyloid, pathology. We assessed whether baseline levels of cerebrospinal fluid (CSF)‐measured core AD pathology [β‐amyloid42 (Aβ42), phosphorylated tau (p‐tau)] related to CBF changes over a 7‐year period and if associations differed by baseline cognitive status.MethodsVanderbilt Memory and Aging Project participants free of clinical dementia or stroke at enrollment [n = 153, 72±6 years, 37% mild cognitive impairment (MCI), 33% female] underwent lumbar puncture to obtain CSF at study entry and serial multimodal 3T brain magnetic resonance imaging over a 7‐year follow‐up period (mean = 5.4 years). Enzyme‐linked immunosorbent assays quantified CSF Aβ42 and p‐tau181. Pseudo‐continuous arterial spin‐labeling captured CBF in total and lobar grey matter regions of interest (ROI). Linear mixed‐effects models related biomarker x time to longitudinal CBF variables adjusting for baseline age and cognitive status, sex, race/ethnicity, education, Framingham Stroke Risk Profile (minus age), ROI volume, APOE‐ε4 status, and time. Models were repeated testing a cognitive status x biomarker x time interaction term.ResultsIn main effect models, neither CSF Aβ42 (p‐values>0.31) nor p‐tau (p‐values>0.28) related to CBF outcomes. Aβ42 did not interact with cognitive status on CBF outcomes (p‐values>0.37), but p‐tau interacted with baseline cognitive status on longitudinal frontal, temporal, parietal, occipital, and total grey matter CBF trajectories (p‐values<0.005). Among cognitively unimpaired participants, higher p‐tau was associated with slower reductions in frontal (β = 0.01, p = 0.03), parietal (β = 0.01, p = 0.04), occipital (β = 0.01, p = 0.02), and total grey matter CBF (β = 0.01, p = 0.04). Among individuals with MCI, higher p‐tau was associated with faster reductions in frontal (β = ‐0.03, p = 0.008), temporal (β = ‐0.02, p = 0.01), parietal (β = ‐0.04, p = 0.002), occipital (β = ‐0.03, p = 0.0004), and total grey matter CBF (β = ‐0.03, p = 0.005).ConclusionsResults linking CSF p‐tau to CBF decline in MCI support the theory that grey matter hypoperfusion is a later‐stage event tied to neurofibrillary tangle pathology. Associations between higher p‐tau and slower rates of CBF decline among cognitively unimpaired individuals warrants further investigation. Funding: R01‐AG034962, K24‐AG046373, F31‐AG079640, T32‐AG058524, P20‐AG068082

Associations between white matter integrity of the cingulum bundle, surrounding gray matter regions, and cognition across the dementia continuum.

Previous Alzheimer's disease and related dementias (AD/ADRD) research studies have illustrated the significance of studying alterations in white matter (WM). Fewer studies have examined how WM integrity, measured with diffusion tensor imaging (DTI), is associated with volume of gray matter (GM) regions and measures of cognitive function in aged participants spanning the dementia continuum. Magnetic resonance imaging and cognitive data were collected from 241 Boston University Alzheimer's Disease Research Center participants who spanned from cognitively normal controls to amnestic mild cognitive impairment to having dementia. Primary DTI tracts of interest were the cingulum ventral (CV) and cingulum dorsal (CD) pathways. GM regions of interest (ROIs) were in the medial temporal lobe (MTL), prefrontal cortex, and retrosplenial cortex. Analyses of covariance models were used to assess differences in WM integrity across groups (control, amnestic mild cognitive impairment, and dementia). Multiple linear regression models were used to assess associations between WM integrity and GM volume, and with measures of memory and executive function. Differences in WM integrity were shown in both cingulum pathways in participants across the dementia continuum. Associations between WM integrity of both cingulum pathways and volume of selected GM ROIs were widespread. Functionally significant associations were found between WM of the CV pathway and memory, independent of MTL GM volume. Differences in WM integrity of the cingulum bundle and surrounding GM ROI are likely related to the progression of AD/ADRD. Such differences should continue to be studied, particularly in association with memory performance.

Magnetic resonance texture analysis reveals stagewise nonlinear alterations of the frontal gray matter in patients with early psychosis.

Although gray matter (GM) abnormalities are present from the early stages of psychosis, subtle/miniscule changes may not be detected by conventional volumetry. Texture analysis (TA), which permits quantification of the complex interrelationship between contrasts at the individual voxel level, may capture subtle GM changes with more sensitivity than does volume or cortical thickness (CTh). We performed three-dimensional TA in nine GM regions of interest (ROIs) using T1 magnetic resonance images from 101 patients with first-episode psychosis (FEP), 85 patients at clinical high risk (CHR) for psychosis, and 147 controls. Via principal component analysis, three features of gray-level cooccurrence matrix - informational measure of correlation 1 (IMC1), autocorrelation (AC), and inverse difference (ID) - were selected to analyze cortical texture in the ROIs that showed a significant change in volume or CTh in the study groups. Significant reductions in GM volume and CTh of various frontotemporal regions were found in the FEP compared with the controls. Increased frontal AC was found in the FEP group compared to the controls after adjusting for volume and CTh changes. While volume and CTh were preserved in the CHR group, a stagewise nonlinear increase in frontal IMC1 was found, which exceeded both the controls and FEP group. Increased frontal IMC1 was also associated with a lesser severity of attenuated positive symptoms in the CHR group, while neither volume nor CTh was. The results of the current study suggest that frontal IMC1 may reflect subtle, dynamic GM changes and the symptomatology of the CHR stage with greater sensitivity, even in the absence of gross GM abnormalities. Some structural mechanisms that may contribute to texture changes (e.g., macrostructural cortical lamina, neuropil/myelination, cortical reorganization) and their possible implications are explored and discussed. Texture may be a useful tool to investigate subtle and dynamic GM abnormalities, especially during the CHR period.

Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers

Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. ClinicalTrials.gov Identifier: NCT01206062.

Impact of material homogeneity assumption on cortical stiffness estimates by MR elastography.

Inversion algorithms used to convert acquired MR elastography wave data into material property estimates often assume that the underlying materials are locally homogeneous. Here we evaluate the impact of that assumption on stiffness estimates in gray-matter regions of interest in brain MR elastography. We describe an updated neural network inversion framework using finite-difference model-derived data to train convolutional neural network inversion algorithms. Neural network inversions trained on homogeneous simulations (homogeneous learned inversions [HLIs]) or inhomogeneous simulations (inhomogeneous learned inversions [ILIs]) are generated with a variety of kernel sizes. These inversions are evaluated in a brain MR elastography simulation experiment and in vivo in a test-retest repeatability experiment including 10 healthy volunteers. In simulation and in vivo, HLI and ILI with small kernels produce similar results. As kernel size increases, the assumption of homogeneity has a larger effect, and HLI and ILI stiffness estimates show larger differences. At each inversion's optimal kernel size in simulation (7 × 7 × 7 for HLI, 11 × 11 × 11 for ILI), ILI is more sensitive to true changes in stiffness in gray-matter regions of interest in simulation. In vivo, there is no difference in the region-level repeatability of stiffness estimates between the inversions, although ILI appears to better maintain the stiffness map structure as kernel size increases, while decreasing the spatial variance in stiffness estimates. This study suggests that inhomogeneous inversions provide small but significant benefits even when large stiffness gradients are absent.

Whole brain atlas-based diffusion kurtosis imaging parameters for evaluation of minimal hepatic encephalopathy.

Minimal hepatic encephalopathy (MHE) has no recognizable clinical symptoms, but patients have cognitive and psychomotor deficits. Hyperammonemia along with neuroinflammation lead to microstructural changes in cerebral parenchyma. Changes at conventional imaging are detected usually at the overt clinical stage, but microstructural alterations by advanced magnetic resonance imaging techniques can be detected at an early stage. Whole brain diffusion kurtosis imaging (DKI) data acquired at 3T was analyzed to investigate microstructural parenchymal changes in 15 patients with MHE and compared with 15 age- and sex-matched controls. DKI parametric maps, namely kurtosis fractional anisotropy (kFA), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK), were evaluated at 64 white matter (WM) and gray matter (GM) regions of interest (ROIs) in the whole brain and correlated with the psychometric hepatic encephalopathy score (PHES). The MHE group showed a decrease in kFA and AK across the whole brain, whereas MK and RK decreased in WM ROIs but increased in several cortical and deep GM ROIs. These alterations were consistent with brain regions involved in cognitive function. Significant moderate to strong correlations (-0.52 to -0.66; 0.56) between RK, MK and kFA kurtosis metrics and PHES were observed. DKI parameters show extensive microstructural brain abnormalities in MHE with minor correlation between the severity of tissue damage and psychometric scores.

Gray matter volume correlates of adolescent posttraumatic stress disorder: A comparison of manual intervention and automated segmentation in FreeSurfer

Exposure to early life trauma is common and confers risk for psychological disorders in adolescence, including posttraumatic stress disorder (PTSD). Trauma exposure and PTSD are also consistently linked to alterations in gray matter volume (GMV). Despite the quantity of structural neuroimaging research in trauma-exposed populations, little consensus exists amongst research groups on best practices for image processing method and manual editing procedures. The purpose of this report is to evaluate the utility of manual editing of magnetic resonance (MR) images for detecting PTSD-related group differences in GMV. Here, T1-weighted MR images from adolescent girls aged 11–17 were obtained and analyzed. Two datasets were created from the FreeSurfer reconall pipeline, one of which was manually edited by trained research assistants. Gray matter regions of interest were selected and total volume estimates were entered into linear mixed effects models with method (manual edits or automated) as a within-subjects factor and group dummy-coded with PTSD as the reference group. Consistent with prior literature, individuals with PTSD demonstrated reduced GMV of the amygdala compared to trauma-exposed and non-trauma exposed controls, independent of editing method. Our results demonstrate that amygdala GMV reductions in PTSD are robust to certain methodological choices and do not suggest a benefit to the time-intensive manual editing pipeline in FreeSurfer for quantifying PTSD-related GMV.

Association of hypometabolic extension of 18F-FDG PET with diffusion tensor imaging indices in mesial temporal lobe epilepsy with hippocampal sclerosis

Purpose: To assess the association between hypometabolic extension of 18F-fluorodeoxyglucose positron emission tomography and diffusion tensor imaging indices, including mean diffusivity (MD) and fractional anisotropy (FA), in hippocampal sclerosis (HS). Methods: Thirty-six unilateral HS were retrospectively selected and stratified into two groups: broad and localized hypometabolic groups (hypometabolism beyond [n = 26] and within the temporal lobe [n = 10]). Forty-one pairs of gray matter (GM) regions of interest (ROIs) were segmented using FreeSurfer software. The GM ROIs were applied to MD maps, and median MD values within each ROI were compared between hemispheres ipsilateral and contralateral to HS using a mixed effect model. Tract-Based Spatial Statistics (TBSS) was used to evaluate FA of white matter (WM) tracts between hemispheres ipsilateral and contralateral to HS. Disease laterality was controlled for. Results: The MD values in the thalamus, caudate, hippocampus, amygdala, superior frontal gyrus, middle and inferior temporal gyrus, temporal pole, and isthmus cingulate gyrus were significantly higher in the HS side than the contralateral side for the broad hypometabolic group. Those in the amygdala and superior temporal sulcus were significantly higher in the HS side than the contralateral side for the localized group. The TBSS analyses showed significantly decreased FA in the WM tracts of the temporal and frontal lobes for the broad hypometabolic group, while no tracts showed significant differences for the localized group. Conclusion: The hypometabolic extension for HS was associated with the abnormalities of MD and FA in GM and WM, respectively, with more widespread microstructural alterations for broad hypometabolic HS.

The macaque brain ONPRC18 template with combined gray and white matter labelmap for multimodal neuroimaging studies of Nonhuman Primates

Macaques are the most common nonhuman primate (NHP) species used in neuroscience research. With the advancement of many neuroimaging techniques, new studies are beginning to apply multiple types of in vivo magnetic resonance imaging (MRI), such as structural imaging (sMRI) with T1 and T2 weighted contrasts alongside diffusion weighed (DW) imaging. In studies involving rhesus macaques, this approach can be used to better understand micro-structural changes that occur during development, in various disease states or with normative aging. However, many of the available rhesus brain atlases have been designed for only one imaging modality, making it difficult to consistently define the same brain regions across multiple imaging modalities in the same subject. To address this, we created a brain atlas from 18 adult rhesus macaques that includes co-registered templates constructed from images frequently used to characterize macroscopic brain structure (T2/SPACE and T1/MP-RAGE), and a diffusion tensor imaging (DTI) template. The DTI template was up-sampled from 1 mm isotropic resolution to resolution match to the T1 and T2-weighted images (0.5 mm isotropic), and the parameter maps were derived for FA, AD, RD and MD.The labelmap volumes delineate 57 gray matter regions of interest (ROIs; 36 cortical regions and 21 subcortical structures), as well as 74 white matter tracts. Importantly, the labelmap overlays both the structural and diffusion templates, enabling the same regions to be consistently identified across imaging modalities. A specialized condensed version of the labelmap ROIs are also included to further extend the usefulness of this tool for imaging data with lower spatial resolution, such as functional MRI (fMRI) or positron emission tomography (PET).

Evaluating High Spatial Resolution Diffusion Kurtosis Imaging at 3T: Reproducibility and Quality of Fit.

Diffusion kurtosis imaging (DKI) quantifies the non-Gaussian diffusion of water within tissue microstructure. However, it has increased fitting parameters and requires higher b-values. Evaluation of DKI reproducibility is important for clinical purposes. To assess the reproducibility in whole-brain high-resolution DKI at varying b-values. Retrospective. In all, 44 individuals from the test-retest Human Connectome Project (HCP) database and 12 3D-printed phantoms. Diffusion-weighted multiband echo-planar imaging sequence at 3T and 9.4T. magnetization-prepared rapid acquisition gradient echo at 3T for in vivo structural data only. From HCP data with b-values = 1000, 2000, 3000 s/mm2 (dataset A), two additional datasets with b-values = 1000, 3000 s/mm2 (dataset B) and b-values = 1000, 2000 s/mm2 (dataset C) were extracted. Estimated DKI metrics from each dataset were used for evaluating reproducibility and fitting quality in white matter (WM) and gray matter (GM) based on whole-brain and regions of interest (ROIs). DKI reproducibility was assessed using the within-subject coefficient of variation (CoV), fitting residuals to evaluate DKI fitting accuracy and Pearson's correlation to investigate the presence of systematic biases. Repeated measures analysis of variance was used for statistical comparison. Datasets A and B exhibited lower DKI CoVs (<20%) compared to C (<50%) in both WM and GM ROIs (all P < 0.05). This effect varies between DKI and DTI parameters (P < 0.005). Whole-brain fitting residuals were consistent across datasets (P > 0.05), but lower residuals in dataset B were detected for the WM ROIs (P < 0.001). A similar trend was observed for the phantom data CoVs (<7.5%) at varying fiber orientations for datasets A and B. Finally, dataset C was characterized by higher residuals across the different fiber crossings (P < 0.05). The study demonstrates that high reproducibility can still be achieved within a reasonable scan time, specifically dataset B, supporting the potential of DKI for aiding clinical tools in detecting microstructural changes.

Pilot multi-site and reproducibility study of hypothalamic gliosis in children.

Quantitative magnetic resonance imaging (MRI) evidence of mediobasal hypothalamic (MBH) gliosis positively correlates with body mass index (BMI) in adults. This has neither been well explored in children nor have other brain regions involved in appetitive processing been tested for evidence of gliosis. Multi-site cross-sectional study in children to test for differences in quantitative T2 signal (measure of gliosis) by region and to assess relationships with age and BMI. Participants underwent brain MRI using the same equipment and protocol to quantify T2 relaxation time in six bilateral regions of interest (ROIs): putamen, caudate, ventral striatum, amygdala, hippocampus and MBH, and three control regions: white matter, motor cortex and dorsal hypothalamus. Thirty-one participants (61% female) were included in a combined sample from the University of Washington (N = 9) and John Hopkins University (N = 22). Mean age was 14 ± 3 years, and BMI z-score was 0.7 ± 1.1 (26% with obesity). No study site-related differences were seen in T2 relaxation time across all nine regions (chi2 (8): 9.46, P = .30). Regional differences in T2 relaxation time were present (P < .001). MBH presented longer T2 relaxation time, suggestive of gliosis, when compared to all regions (P < .001), including an intra-hypothalamic control. Physiological age-related declines in T2 relaxation times were found in grey matter ROIs, but not in the MBH (r = -0.14, P = .46). MBH was the only region with a positive correlation between T2 relaxation time and BMI z-score (r = 0.38, P = .03). In a multi-site study, pilot data suggest that quantitative MRI detected normal maturation-related brain variation as well as evidence that MBH gliosis is associated with increased adiposity in children.

Greater Social Engagement and Greater Gray Matter Microstructural Integrity in Brain Regions Relevant to Dementia.

Social engagement (SE) may protect against cognitive decline in older adults. We estimate associations of SE with gray matter (GM) microstructure in regions of interest (ROI) relevant to social cognition, among community-dwelling older adults. Cross-sectional analysis of 293 Health ABC study participants who underwent 3 Tesla magnetic resonance imaging with diffusion tensor and free from cognitive impairment was conducted. Linear regression models tested associations between SE index (marital status, not living alone, social activities, work, and volunteering) and mean diffusivity (MD) of GM ROIs, adjusted for age, race, gender, and education. Hearing and activities of daily living (ADL) difficulties were tested as confounders. Effect modification by gender was tested with interaction terms and stratification by gender. Higher SE was significantly related to lower MD (greater GM microstructural integrity) (shown as standardized estimate [p-value]) in left middle frontal gyrus-orbital part: -.168 (.005), left caudate nucleus: -.141 (.02), left temporal pole-middle temporal gyrus: -.136 (.03), right middle frontal gyrus: -.160 (.006), right superior frontal gyrus-orbital part: -.187 (.002), and right middle frontal gyrus-orbital part: -.124 (.04), when adjusted for demographic attributes. Associations were robust to adjustments for hearing or ADL difficulty. There was significant effect modification by gender for some ROIs, with associations only for females. SE is related to greater microstructural integrity of specific GM regions relevant to social cognition, that have described roles in dementia. SE may therefore be a useful preventive mechanism against loss of GM integrity in older adults.

Intrasession Reliability of Arterial Spin-Labeled MRI-Measured Noncontrast Perfusion in Glioblastoma at 3 T.

Arterial spin-labeled magnetic resonance imaging can provide quantitative perfusion measurements in the brain and can be potentially used to evaluate therapy response assessment in glioblastoma (GBM). The reliability and reproducibility of this method to measure noncontrast perfusion in GBM, however, are lacking. We evaluated the intrasession reliability of brain and tumor perfusion in both healthy volunteers and patients with GBM at 3 T using pseudocontinuous labeling (pCASL) and 3D turbo spin echo (TSE) using Cartesian acquisition with spiral profile reordering (CASPR). Two healthy volunteers at a single time point and 6 newly diagnosed patients with GBM at multiple time points (before, during, and after chemoradiation) underwent scanning (total, 14 sessions). Compared with 3D GraSE, 3D TSE-CASPR generated cerebral blood flow maps with better tumor-to-normal background tissue contrast and reduced image distortions. The intraclass correlation coefficient between the 2 runs of 3D pCASL with TSE-CASPR was consistently high (≥0.90) across all normal-appearing gray matter (NAGM) regions of interest (ROIs), and was particularly high in tumors (0.98 with 95% confidence interval [CI]: 0.97–0.99). The within-subject coefficients of variation were relatively low in all normal-appearing gray matter regions of interest (3.40%–7.12%), and in tumors (4.91%). Noncontrast perfusion measured using 3D pCASL with TSE-CASPR provided robust cerebral blood flow maps in both healthy volunteers and patients with GBM with high intrasession repeatability at 3 T. This approach can be an appropriate noncontrast and noninvasive quantitative perfusion imaging method for longitudinal assessment of therapy response and management of patients with GBM.

Reduced Microstructural Lateralization in Males with Chronic Schizophrenia: A Diffusional Kurtosis Imaging Study.

Decreased brain lateralization is considered a trait marker of schizophrenia. Whereas reductions in both functional and macrostructural gray matter laterality in schizophrenia are well established, the investigation of gray matter microstructural lateralization has so far been limited to a small number of ex vivo studies, which limits the understanding of neurobiological substrates involved and development of adequate treatments. The aim of the current study was to assess in vivo gray matter microstructure lateralization patterns in schizophrenia by employing the diffusion kurtosis imaging (DKI)-derived mean kurtosis (MK) metric. MK was calculated for 18 right-handed males with chronic schizophrenia and 19 age-matched healthy control participants in 46 bilateral gray matter regions of interest (ROI). Microstructural laterality indexes (μLIs) were calculated for each subject and ROI, and group comparisons were conducted across regions. The relationship between μLI values and performance on the Wisconsin Card Sorting Test (WCST) was also evaluated. We found that compared with healthy controls, males with chronic schizophrenia had significantly decreased μLI across cortical and subcortical gray matter regions, which was correlated with poorer performance on the WCST. Our results suggest the ability of DKI-derived MK to capture gray matter microstructural lateralization pathology in vivo.

Brain Changes Induced by Electroconvulsive Therapy Are Broadly Distributed

BackgroundElectroconvulsive therapy (ECT) is associated with volumetric enlargements of corticolimbic brain regions. However, the pattern of whole-brain structural alterations following ECT remains unresolved. Here, we examined the longitudinal effects of ECT on global and local variations in gray matter, white matter, and ventricle volumes in patients with major depressive disorder as well as predictors of ECT-related clinical response. MethodsLongitudinal magnetic resonance imaging and clinical data from the Global ECT-MRI Research Collaboration (GEMRIC) were used to investigate changes in white matter, gray matter, and ventricle volumes before and after ECT in 328 patients experiencing a major depressive episode. In addition, 95 nondepressed control subjects were scanned twice. We performed a mega-analysis of single subject data from 14 independent GEMRIC sites. ResultsVolumetric increases occurred in 79 of 84 gray matter regions of interest. In total, the cortical volume increased by mean ± SD of 1.04 ± 1.03% (Cohen’s d = 1.01, p < .001) and the subcortical gray matter volume increased by 1.47 ± 1.05% (d = 1.40, p < .001) in patients. The subcortical gray matter increase was negatively associated with total ventricle volume (Spearman’s rank correlation ρ = −.44, p < .001), while total white matter volume remained unchanged (d = −0.05, p = .41). The changes were modulated by number of ECTs and mode of electrode placements. However, the gray matter volumetric enlargements were not associated with clinical outcome. ConclusionsThe findings suggest that ECT induces gray matter volumetric increases that are broadly distributed. However, gross volumetric increases of specific anatomically defined regions may not serve as feasible biomarkers of clinical response.

Natalizumab treatment reduces microglial activation in the white matter of the MS brain.

ObjectiveTo evaluate whether natalizumab treatment reduces microglial activation in MS.MethodsWe measured microglial activation using the 18-kDa translocator protein (TSPO)-binding radioligand [11C]PK11195 and PET imaging in 10 patients with MS before and after 1 year treatment with natalizumab. Microglial activation was evaluated as the distribution volume ratio (DVR) of the specifically bound radioligand in brain white and gray matter regions of interest. MRI and disability measurements were performed for comparison. Evaluation was performed identically with 11 age- and sex-matched patients with MS who had no MS therapy.ResultsNatalizumab treatment reduced microglial activation in the normal-appearing white matter (NAWM; baseline DVR vs DVR after 1 year of treatment 1.25 vs 1.22, p = 0.014, Wilcoxon) and at the rim of chronic lesions (baseline DVR vs DVR after 1 year of treatment 1.24 vs 1.18, p = 0.014). In patients with MS with no treatment, there was an increase in microglial activation at the rim of chronic lesions (1.23 vs 1.27, p = 0.045). No alteration was observed in microglial activation in gray matter areas. In the untreated patient group, higher microglial activation at baseline was associated with more rapid disability progression during an average of 4 years of follow-up.ConclusionsTSPO-PET imaging can be used as a tool to assess longitudinal changes in microglial activation in the NAWM and in the perilesional areas in the MS brain in vivo. Natalizumab treatment reduces the diffuse compartmentalized CNS inflammation related to brain resident innate immune cells.