Clusters Of Voxels Research Articles

Perspectives on obesity imaging: [18F]2FNQ1P a specific 5-HT6 brain PET radiotracer.

Estimates suggest that approximatively 25% of the world population will be overweight in 2025. Better understanding of the pathophysiology of obesity will help to develop future therapeutics. Serotonin subtype 6 receptors (5-HT6) have been shown to be critically involved in appetite reduction and weight loss. However, it is not known if the pathological cascade triggered by obesity modifies the density of 5-HT6 receptors in the brain. Influence of diet-induced obesity (DIO) in Wistar rats was explored using MRI (whole-body fat) and PET ([18F]2FNQ1P as a specific 5-HT6 radiotracer). The primary goal was to monitor the 5-HT6 receptor density before and after a 10-week diet (DIO group). The secondary goal was to compare 5-HT6 receptor densities between DIO group, Wistar control diet group, Zucker rats (with genetic obesity) and Zucker lean strain rats. Wistar rats fed with high-fat diet showed higher body fat gain than Wistar control diet rats on MRI. [18F]2FNQ1P PET analysis highlighted significant clusters of voxels (located in hippocampus, striatum, cingulate, temporal cortex and brainstem) with increased binding after high-fat diet (p < 0.05, FWE corrected). This study sheds a new light on the influence of high-fat diet on 5-HT6 receptors. This study also positions [18F]2FNQ1P PET as an innovative tool to explore neuronal consequences of obesity or eating disorder pathophysiology.

Habitat Imaging With Tumoral and Peritumoral Radiomics for Prediction of Lung Adenocarcinoma Invasiveness on Preoperative Chest CT: A Multicenter Study.

Background: Tumors' growth processes result in spatial heterogeneity, with the development of tumor subregions (i.e., habitats) having unique biologic characteristics. Objective: To develop and validate a habitat model combining tumor and peritumoral radiomics features on chest CT for predicting invasiveness of lung adenocarcinoma. Methods: This retrospective study included 1156 patients (mean age, 57.5 years; 464 male, 692 female) from three centers and a public dataset, who underwent chest CT before lung adenocarcinoma resection (variable date ranges across datasets). Patients from one center formed training (n=500) and validation (n=215) sets; patients from the other sources formed three external test sets (n=249, 113, 79). For each patient, a single nodule was manually segmented on chest CT. The nodule segmentation was combined with an automatically generated 4-mm peritumoral region into a whole-volume volume-of-interest (VOI). A Gaussian mixture model (GMM) identified voxel clusters with similar first-order energy across patients. GMM results were used to divide each patient's whole-volume VOI into multiple habitats, defined consistently across patients. Radiomic features were extracted from each habitat. After feature selection, a habitat model was developed for predicting invasiveness, using pathologic assessment as a reference. An integrated model was constructed, combining features extracted from habitats and whole-volume VOIs. Model performance was evaluated, including in subgroups based on nodule density (pure ground-glass, part-solid, solid). Results: Invasive cancer was diagnosed in 625/1156 patients. GMM identified four as the optimal number of voxel clusters and thus of per-patient tumor habitats. The habitat model had AUC of 0.932 in the validation set, and 0.881, 0.880, and 0.764 in the three external test sets. The integrated model had AUC of 0.947 in the validation set and 0.936, 0.908, and 0.800 in the three external test sets. In the three external test sets combined, across nodule densities, AUCs for the habitat model were 0.836-0.969 and for the integrated model were 0.846-0.917. Conclusions: Habitat imaging combining tumoral and peritumoral radiomic features could help predict lung adenocarcinoma invasiveness. Prediction is improved when combining information on tumor subregions and the tumor overall. Clinical Impact: The findings may aid personalized preoperative assessments to guide clinical decision-making in lung adenocarcinoma.

A neural compass in the human brain during naturalistic virtual navigation.

A central component of wayfinding is the ability to maintain a consistent representation of one's facing direction when moving about the world. In rodents, head direction cells are believed to support this "neural compass", but identifying a similar mechanism in humans during dynamic naturalistic navigation has been challenging. To address this issue, we acquired fMRI data while participants freely navigated through a virtual reality city. Encoding model analyses revealed voxel clusters in retrosplenial complex and superior parietal lobule that exhibited reliable tuning as a function of facing direction. Crucially, these directional tunings were consistent across perceptually different versions of the city, spatially separated locations within the city, and motivationally distinct phases of the behavioral task. Analysis of the model weights indicated that these regions may represent facing direction relative to the principal axis of the environment. These findings reveal specific mechanisms in the human brain that allow us to maintain a sense of direction during naturalistic, dynamic navigation.

Hippocampus and olfactory impairment in Parkinson disease: a comparative exploratory combined volumetric/functional MRI study.

Patients with Parkinson's Disease (PD) commonly experience Olfactory Dysfunction (OD). Our exploratory study examined hippocampal volumetric and resting-state functional magnetic resonance imaging (rs-fMRI) variations in a Healthy Control (HC) group versus a cognitively normal PD group, further categorized into PD with No/Mild Hyposmia (PD-N/MH) and PD with Severe Hyposmia (PD-SH). We calculated participants' relative Total Hippocampal Volume (rTHV) and performed Spearman's partial correlations, controlled for age and gender, to examine the correlation between rTHV and olfactory performance assessed by the Odor Stick Identification Test for the Japanese (OSIT-J) score. Mann-Whitney U tests assessed rTHV differences across groups and subgroups, rejecting the null hypothesis for p < 0.05. Furthermore, a seed-based rs-fMRI analysis compared hippocampal connectivity differences using a one-way ANCOVA covariate model with controls for age and gender. Spearman's partial correlations indicated a moderate positive correlation between rTHV and OSIT-J in the whole study population (ρ = 0.406; p = 0.007), PD group (ρ = 0.493; p = 0.008), and PD-N/MH subgroup (ρ = 0.617; p = 0.025). Mann-Whitney U tests demonstrated lower rTHV in PD-SH subgroup compared to both HC group (p = 0.013) and PD-N/MH subgroup (p = 0.029). Seed-to-voxel rsfMRI analysis revealed reduced hippocampal connectivity in PD-SH subjects compared to HC subjects with a single cluster of voxels. Although the design of the study do not allow to make firm conclusions, it is reasonable to speculate that the progressive involvement of the hippocampus in PD patients is associated with the progression of OD.

A multivariate to multivariate approach for voxel-wise genome-wide association analysis.

The joint analysis of imaging-genetics data facilitates the systematic investigation of genetic effects on brain structures and functions with spatial specificity. We focus on voxel-wise genome-wide association analysis, which may involve trillions of single nucleotide polymorphism (SNP)-voxel pairs. We attempt to identify underlying organized association patterns of SNP-voxel pairs and understand the polygenic and pleiotropic networks on brain imaging traits. We propose a bi-clique graph structure (ie, a set of SNPs highly correlated with a cluster of voxels) for the systematic association pattern. Next, we develop computational strategies to detect latent SNP-voxel bi-cliques and an inference model for statistical testing. We further provide theoretical results to guarantee the accuracy of our computational algorithms and statistical inference. We validate our method by extensive simulation studies, and then apply it to the whole genome genetic and voxel-level white matter integrity data collected from 1052 participants of the human connectome project. The results demonstrate multiple genetic loci influencing white matter integrity measures on splenium and genu of the corpus callosum.

Signal Intensity Trajectories Clustering for Liver Vasculature Segmentation and Labeling (LiVaS) on Contrast-Enhanced MR Images: A Feasibility Pilot Study.

This study aims to develop a semiautomated pipeline and user interface (LiVaS) for rapid segmentation and labeling of MRI liver vasculature and evaluate its time efficiency and accuracy against manual reference standard. Retrospective feasibility pilot study. Liver MR images from different scanners from 36 patients were included, and 4/36 patients were randomly selected for manual segmentation as referenced standard. The liver was segmented in each contrast phase and masks registered to the pre-contrast segmentation. Voxel-wise signal trajectories were clustered using the k-means algorithm. Voxel clusters that best segment the liver vessels were selected and labeled by three independent radiologists and a research scientist using LiVaS. Segmentation times were compared using a paired-sample t-test on log-transformed data. The agreement was analyzed qualitatively and quantitatively using DSC for hepatic and portal vein segmentations. The mean segmentation time among four readers was significantly shorter than manual (3.6 ± 1.4 vs. 70.0 ± 29.2min; p < 0.001), even when using a higher number of clusters to enhance accuracy. The DSC for portal and hepatic veins reached up to 0.69 and 0.70, respectively. LiVaS segmentations were overall of good quality, with variations in performance related to the presence/severity of liver disease, acquisition timing, and image quality. Our semi-automated pipeline was robust to different MRI vendors in producing segmentation and labeling of liver vasculature in agreement with expert manual annotations, with significantly higher time efficiency. LiVaS could facilitate the creation of large, annotated datasets for training and validation of neural networks for automated MRI liver vascularity segmentation. HIGHLIGHTS: Key Finding: In this pilot feasibility study, our semiautomated pipeline for segmentation of liver vascularity (LiVaS) on MR images produced segmentations with simultaneous labeling of portal and hepatic veins in good agreement with the manual reference standard but at significantly shorter times (mean LiVaS 3.6 ± 1.4 vs. mean manual 70.0 ± 29.2min; p < 0.001). Importance: LiVaS was robust in producing liver MRI vascular segmentations across images from different scanners in agreement with expert manual annotations, with significant ly higher time efficiency, and therefore potential scalability.

Immediate neural effects of acupuncture manipulation time for stroke with motor dysfunction: a fMRI pilot study.

Acupuncture is widely utilized as a beneficial intervention for the treatment of motor dysfunction after stroke, and its effectiveness depends on the stimulation dose. Manipulation time is an important factor affecting the dose. This trial aimed use fMRI to explore the immediate neural effects in stroke patients with motor dysfunction by different acupuncture manipulation times, to reveal the neural mechanism of acupuncture manipulation. Thirty participants were divided into three groups according to different acupuncture times. Each group received the same acupoint prescription, although the continuous manipulation time of each acupoint in three groups was 1-min, 2-min, and 3-min, respectively. The NIHSS, FMA and fMRI-BOLD in each participant we obtained before and after acupuncture manipulation. Then, we used the regional homogeneity (ReHo) algorithm to analyze the changes of brain function and to compare the neural effects at different acupuncture manipulation times. There were no significant differences in NIHSS and FMA scores between and within groups. Longitudinal analysis of ReHo values indicated that the right inferior frontal gyrus was activated in the 1-min group, the right insula in the 2-min group, and the right inferior temporal gyrus in the 3-min group. Compared with the 1-min group, the 2-min group showed the ReHo values of the right precentral gyrus was decreased, and the 3-min group showed the left cerebellum posterior lobe was increased, the right posterior cingulate gyrus and the right anterior cingulate gyrus were decreased. Compared with the 2-min group, the 3-min group showed the ReHo values of the right cerebellum anterior lobe was increased. Our findings suggest that acupuncture at different manipulation times caused different changes of the neural effects in stroke patients, and the volume of activated voxel clusters is positively correlated with the manipulation time. Longer acupuncture manipulation could drive SMN and DMN in stroke patients, which may be the potential neurological mechanism of acupuncture manipulation affecting the recovery of motor dysfunction.

The effects of cannabis abstinence on cognition and resting state network activity in people with multiple sclerosis: A preliminary study

We previously reported that people with multiple sclerosis (pwMS) who have been using cannabis frequently over many years can have significant cognitive improvements accompanied by concomitant task-specific changes in brain activation following 28 days of cannabis abstinence. We now hypothesize that the default Mode Network (DMN), known to modulate cognition, would also show an improved pattern of activation align with cognitive improvement following 28 days of drug abstinence. Thirty three cognitively impaired pwMS who were frequent cannabis users underwent a neuropsychological assessment and fMRI at baseline. Individuals were then assigned to a cannabis continuation (CC, n = 15) or withdrawal (CW, n = 18) group and the cognitive and imaging assessments were repeated after 28 days. Compliance with cannabis withdrawal was checked with regular urine monitoring. Following acquisition of resting state fMRI (rs-fMRI), data were processed using independent component analysis (ICA) to identify the DMN spatial map. Between and within group analyses were carried out using dual regression for voxel-wise comparisons of the DMN. Clusters of voxels were considered statistically significant if they survived threshold-free cluster enhancement (TFCE) correction at p < 0.05. The two groups were well matched demographically and neurologically at baseline. The dual regression analysis revealed no between group differences at baseline in the DMN. By day 28, the CW group in comparison to the CC group had increased activation in the left posterior cingulate, and right, angular gyrus (p < 0.05 for both, TFCE). A within group analysis for the CC group revealed no changes in resting state (RS) networks. Within group analysis of the CW group revealed increased activation at day 28 versus baseline in the left posterior cingulate, right angular gyrus, left hippocampus (BA 36), and the right medial prefrontal cortex (p < 0.05). The CW group showed significant improvements in multiple cognitive domains. In summary, our study revealed that abstaining from cannabis for 28 days reverses activation of DMN activity in pwMS in association with improved cognition across several domains.

Abnormal interhemispheric functional cooperation in schizophrenia follows the neurotransmitter profiles.

Interhemispheric cooperation is one of the most prominent functional architectures of the human brain. In patients with schizophrenia, interhemispheric cooperation deficits have been reported using increasingly powerful neurobehavioural and neuroimaging measures. However, these methods rely in part on the assumption of anatomic symmetry between hemispheres. In the present study, we explored interhemispheric cooperation deficits in schizophrenia using a newly developed index, connectivity between functionally homotopic voxels (CFH), which is unbiased by hemispheric asymmetry. Patients with schizophrenia and age- and sexmatched healthy controls underwent multimodal MRI, and whole-brain CFH maps were constructed for comparison between groups. We examined the correlations of differing CFH values between the schizophrenia and control groups using various neurotransmitter receptor and transporter densities. We included 86 patients with schizophrenia and 86 matched controls in our analysis. Patients with schizophrenia showed significantly lower CFH values in the frontal lobes, left postcentral gyrus and right inferior temporal gyrus, and significantly greater CFH values in the right caudate nucleus than healthy controls. Moreover, the differing CFH values in patients with schizophrenia were significantly correlated with positive symptom score and illness duration. Functional connectivity within frontal lobes was significantly reduced at the voxel cluster level compared with healthy controls. Finally, the abnormal CFH map of patients with schizophrenia was spatially associated with the densities of the dopamine D1 and D2 receptors, fluorodopa, dopamine transporter, serotonin transporter and acetylcholine transporter. Regional abnormalities in interhemispheric cooperation may contribute to the clinical symptoms of schizophrenia. These CFH abnormalities may be associated with dysfunction in neurotransmitter systems strongly implicated in schizophrenia.

Aging modulates frontal lobes involvement in emotion regulation processing.

Emotion regulation (ER) is the process by which individuals can modulate the intensity of their emotional experience and it plays a crucial role in daily life. So far, behavioral analyses seem to suggest that ER ability remains stable throughout the lifespan. However, imaging studies evaluating the neural correlates of ER performance during the aging process have shown mixed results. In this study, we used the "Cambridge Centre for Ageing and Neuroscience cohort sample" to investigate: (1) ER behavioral performance and (2) the differential association between brain measures (based on both structural and functional connectivity data) and ER performance, in a group of younger/middle-aged participants (N = 159; age range: 18y < x < 58y) relative to a group of older healthy subjects (N = 136; age range: 58y < =x < 89y). Whereas we found no group-related differences either in ER behavioral data or the association between ER performance and structural data, we did observe that ER performance was differentially correlated in our two study groups to functional connectivity measures in the fronto-insular-temporal network, which has been shown to be involved in emotional processing. Group-related differences were specifically localized in a cluster of voxels within the anterior cingulate areas which revealed a reverse pattern between our study groups: in younger/middle-aged participants better ER performance was associated with increase connectivity, whereas among older participants better ER performance was related to reduced connectivity. Based on our results, we suggest that a de-differentiation mechanism, known to affect the frontal lobes brain activity and connectivity in older subjects, might explain our findings.

Vascular contribution to the relationship between cerebrovascular reactivity and cognition

AbstractBackgroundBrain vascular health is closely related to cognitive performance, and cerebrovascular reactivity (CVR), an indicator of cerebral blood flow (CBF) compensatory capacity in response to vasoactive stimuli, may help elucidate this relationship. Arterial spin labeling (ASL) and blood‐oxygen‐level‐dependent (BOLD) are two representative methods for measuring CVR, although BOLD is a complex combination of CBF, cerebral volume, and cerebral metabolic rate of oxygen. This study aimed to investigate the relationship between cognition and two different CVR methods.MethodSeventy‐nine subjects (age: 68.7±7.2 years) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core underwent MRI, including both dynamic pseudo‐continuous ASL (PCASL) under a hypercapnic respiratory challenge and multi‐TI PCASL for resting CBF and ATT mapping. The dynamic PCASL with a longer TE (20ms) provided simultaneous acquisition of ASL and BOLD. CVR was obtained by calculating CBF or BOLD signal changes during a hypercapnic period. Voxel‐wise multiple linear regression analyses were performed to examine the relationship between CVR and mild cognitive impairment (MCI), adjusting for age, sex, glycemic status, APOE e4 allele, hypertensive status, and years of education. False positive cluster thresholding was applied for each modality. Additional statistical analyses were conducted to investigate differences in baseline CBF and ATT between cognitively healthy and MCI groups within the voxel clusters that showed significantly different CVR values.ResultIn the BOLD‐based CVR analysis, two voxel clusters in the white matter (WM) of superior temporal and parietal lobes showed lower CVR in the MCI group compared to the cognitively healthy group (Figure 1). Additionally, reduced CBF and prolonged ATT were observed within the clusters (Figure 2 and 3).ConclusionSubjects with MCI exhibited lower BOLD‐based CVR in WM, while no association was found between ASL‐based CVR and MCI. BOLD‐based CVR may be a more sensitive measure than ASL‐based CVR in association with cognition, particularly in WM where optimization of ASL acquisition is challenging. The impaired CVR in the MCI group may be due to cerebrovascular impairments, such as reduced CBF and prolonged ATT.

Characterizing the effects of COVID‐19 on the brain using FDG PET imaging before and after COVID‐19 infection

AbstractBackgroundIndividuals diagnosed with COVID‐19 have been found to have changes in brain structure as well as dramatic neuropsychiatric effects such as dementia, Parkinsonism, and greater likelihood of stroke (Taquet, 2021). Infection has also been shown to result in hypometabolic changes on 18F ‐fluorodeoxyglucose positron emission tomography (FDG PET) when compared to normal controls (Guedj, 2021). This study will seek to determine which brain regions are most affected by COVID‐19 with FDG PET. To our knowledge, we are the first study to compare pre‐ and post‐infection FDG PET imaging within patients. These patients were coincidentally infected with COVID‐19 between standard of care longitudinal FDG PET imaging for cancer.MethodPatients with COVID‐19 who had FDG PET imaging that included the brain before and after serologic COVID‐19 diagnosis were identified from an internal COVID‐19 registry. Clinical data was mined from the electronic health record. Images were processed with well‐established SPM12 methods (Friston, 1995). A voxel‐wise ANCOVA was performed on FDG PET images before and after COVID‐19 infection, including covariates of age, sex, ethnicity, and time between chemotherapy and follow‐up imaging using p &lt; 0.001 and voxel extent threshold of 10.Result29 patients met inclusion criteria (Table 1). Compared to baseline, 4 clusters of voxels were significantly decreased after COVID‐19 infection in the temporal lobes, anterior cingulate gyrus, and superior cerebellum (Table 2). In a post‐hoc analysis, spherical regions of interest (radius = 5 mm) surrounding these clusters were tested for post‐infection hypometabolism. The bilateral temporal lobes, anterior lobe of cerebellum, and right caudate head showed significant decrease in glucose metabolism following COVID‐19 infection (p &lt; 0.05).ConclusionCurrently, this is the first study to leverage a pre‐COVID‐19 infection FDG PET for comparison to imaging post‐infection. We discovered regions in the temporal lobe, frontal lobe, and cerebellum that showed hypometabolic changes following infection, important for determining spatial localization of the effects of this viral infection.

Characterizing the effects of COVID‐19 on the brain using FDG PET imaging before and after COVID‐19 infection

AbstractBackgroundIndividuals diagnosed with COVID‐19 have been found to have changes in brain structure as well as dramatic neuropsychiatric effects such as dementia, Parkinsonism, and greater likelihood of stroke (Taquet, 2021). Infection has also been shown to result in hypometabolic changes on 18F ‐fluorodeoxyglucose positron emission tomography (FDG PET) when compared to normal controls (Guedj, 2021). This study will seek to determine which brain regions are most affected by COVID‐19 with FDG PET. To our knowledge, we are the first study to compare pre‐ and post‐infection FDG PET imaging within patients. These patients were coincidentally infected with COVID‐19 between standard of care longitudinal FDG PET imaging for cancer.MethodPatients with COVID‐19 who had FDG PET imaging that included the brain before and after serologic COVID‐19 diagnosis were identified from an internal COVID‐19 registry. Clinical data was mined from the electronic health record. Images were processed with well‐established SPM12 methods (Friston, 1995). A voxel‐wise ANCOVA was performed on FDG PET images before and after COVID‐19 infection, including covariates of age, sex, ethnicity, and time between chemotherapy and follow‐up imaging using p &lt; 0.001 and voxel extent threshold of 10.Result29 patients met inclusion criteria (Table 1). Compared to baseline, 4 clusters of voxels were significantly decreased after COVID‐19 infection in the temporal lobes, anterior cingulate gyrus, and superior cerebellum (Table 2). In a post‐hoc analysis, spherical regions of interest (radius = 5 mm) surrounding these clusters were tested for post‐infection hypometabolism. The bilateral temporal lobes, anterior lobe of cerebellum, and right caudate head showed significant decrease in glucose metabolism following COVID‐19 infection (p &lt; 0.05).ConclusionCurrently, this is the first study to leverage a pre‐COVID‐19 infection FDG PET for comparison to imaging post‐infection. We discovered regions in the temporal lobe, frontal lobe, and cerebellum that showed hypometabolic changes following infection, important for determining spatial localization of the effects of this viral infection.

The Effects of Hypertension on White Matter Microstructural and Vascular Imaging Metrics

AbstractBackgroundHypertension is one of the key vascular risk factors of AD and related dementia. Cerebral blood flow (CBF) and white matter (WM) integrity may play an essential role in understanding the vascular contributions to dementia (VCID). We investigated if hypertension is related to WM microstructural and vascular imaging metrics in WM.MethodFour‐hundred‐seven subjects (age: 69.7±8.1 years) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core underwent MRI, including neurite orientation dispersion and density imaging (NODDI) and eight‐phase pseudo‐continuous ASL (PCASL). The subjects included 158 MCI, 111 APOE e4 allele carriers, 224 with hypertension, and 249 with impaired glycemic status which includes type 2 diabetes and prediabetics. Hypertension status was defined as SBP≥130mmHG and DBP≥80mmHG. The microstructural imaging metrics including intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index (ODI) were obtained from NODDI. The vascular imaging metric included CBF. CBF was obtained from PCASL sequence. Voxel‐wise linear regression analyses were performed to examine if CBF, ICVF, ISOVF, or ODI were related to hypertension adjusting for cognitive status, glycemic status, APOE e4 allele, age, sex, and years of education. All images were normalized into standard space. Tract‐based spatial statistics (TBSS) were used to normalize NODDI images. The false positive cluster thresholding was applied.ResultHypertensive subjects showed impairments in both microstructural and vascular imaging metrics. Based on Figures 1‐(A), 2‐(A) and 3‐(A), there are overlapping brain image voxels between the microstructural and vascular imaging metrics. Additionally, the hypertensive subjects showed significantly lower CBF, higher ISOVF, and higher ODI than normal subjects within the voxel clusters (Figures 1‐(B), 2‐(B), and 3‐(B)). Note that APOE e4 allele, glycemic status, and cognitive status also showed statistical significance in the NODDI parameters, but there was no association in CBF.ConclusionHypertension showed the potential association between the microstructural and vascular impairments in the WM. Each risk factor and cognitive status differently affected WM microstructural and vascular dynamic imaging parameters. These findings warrant further investigations of contributions of hypertension to the microstructural and vascular abnormalities in dementia.

The Effects of Hypertension on White Matter Microstructural and Vascular Imaging Metrics

AbstractBackgroundHypertension is one of the key vascular risk factors of AD and related dementia. Cerebral blood flow (CBF) and white matter (WM) integrity may play an essential role in understanding the vascular contributions to dementia (VCID). We investigated if hypertension is related to WM microstructural and vascular imaging metrics in WM.MethodFour‐hundred‐seven subjects (age: 69.7±8.1 years) enrolled in the Wake Forest Alzheimer’s Disease Research Center (ADRC) Clinical Core underwent MRI, including neurite orientation dispersion and density imaging (NODDI) and eight‐phase pseudo‐continuous ASL (PCASL). The subjects included 158 MCI, 111 APOE e4 allele carriers, 224 with hypertension, and 249 with impaired glycemic status which includes type 2 diabetes and prediabetics. Hypertension status was defined as SBP = 130mmHG and DBP = 80mmHG. The microstructural imaging metrics including intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index (ODI) were obtained from NODDI. The vascular imaging metric included CBF. CBF was obtained from PCASL sequence. Voxel‐wise linear regression analyses were performed to examine if CBF, ICVF, ISOVF, or ODI were related to hypertension adjusting for cognitive status, glycemic status, APOE e4 allele, age, sex, and years of education. All images were normalized into standard space. Tract‐based spatial statistics (TBSS) were used to normalize NODDI images. The false positive cluster thresholding was applied.ResultHypertensive subjects showed impairments in both microstructural and vascular imaging metrics. Based on Figures 1‐(A), 2‐(A) and 3‐(A), there are overlapping brain image voxels between the microstructural and vascular imaging metrics. Additionally, the hypertensive subjects showed significantly lower CBF, higher ISOVF, and higher ODI than normal subjects within the voxel clusters (Figures 1‐(B), 2‐(B), and 3‐(B)). Note that APOE e4 allele, glycemic status, and cognitive status also showed statistical significance in the NODDI parameters, but there was no association in CBF.ConclusionHypertension showed the potential association between the microstructural and vascular impairments in the WM. Each risk factor and cognitive status differently affected WM microstructural and vascular dynamic imaging parameters. These findings warrant further investigations of contributions of hypertension to the microstructural and vascular abnormalities in dementia.

Regional White Matter Hyperintensities are Associated with Diminished Blood Flow and Microstructure in Middle Age

AbstractBackgroundWhite matter hyperintensities (WMH) are areas of increased signal visualized on T2‐weighted FLAIR magnetic resonance imaging (MRI), thought to reflect macrostructural damage due to small vessel cerebrovascular disease. Previous work established an association of WMH severity, particularly in posterior regions, with risk and progression of AD in late onset and genetic forms of AD, suggesting a vascular component to disease pathogenesis and course. Examination of the emergence and correlates of cerebrovascular changes in middle age, a critical time when vascular risk appears to be most penetrant, can give insight into mechanisms linking vascular brain injury and risk for AD. In the current study, we examined the association of cerebral blood flow (CBF) and white matter microstructure with total and regional WMH volume in middle‐aged, community dwelling adults.MethodFour hundred and ninety‐two middle‐aged participants (55+/‐11 age = 28 ‐85 years) from the community‐based Offspring Study of Mechanisms for Racial Disparities in Alzheimer’s Disease received multi‐modal MRI scanning. Regional WMH volumes were derived with in‐house software that labeled clusters of voxels within a hyperintense intensity distribution. Pulsed arterial spin labeling (PASL) sequences were processed to quantify CBF. Fractional anisotropy (FA) maps were obtained from diffusion weighted data. Total and regional WMH volumes were used as predictors for whole brain voxel‐wise correlation analyses in separate models for CBF and FA.ResultThere were negative associations between WMH volume and CBF in frontal, parietal, and occipital regions. Higher white matter hyperintensity volume was associated with lower FA, particularly in the periventricular region.ConclusionWe found associations of increased WMH volume with diminished blood flow and white matter microstructure. Future studies are needed to explain the relationship between these changes and the risk of cognitive impairment in middle aged adults and risk for AD.

Organization of thalamocortical structural covariance and a corresponding 3D atlas of the mouse thalamus

For information from sensory organs to be processed by the brain, it is usually passed to appropriate areas of the cerebral cortex. Almost all of this information passes through the thalamus, a relay structure that reciprocally connects to the vast majority of the cortex. The thalamus facilitates this information transfer through a set of thalamocortical connections that vary in cellular structure, molecular profiles, innervation patterns, and firing rates. Additionally, corticothalamic connections allow for intracortical information transfer through the thalamus. These efferent and afferent connections between the thalamus and cortex have been the focus of many studies, and the importance of cortical connectivity in defining thalamus anatomy is demonstrated by multiple studies that parcellate the thalamus based on cortical connectivity profiles.Here, we examine correlated morphological variation between the thalamus and cortex, or thalamocortical structural covariance. For each voxel in the thalamus as a seed, we construct a cortical structural covariance map that represents correlated cortical volume variation, and examine whether high structural covariance is observed in cortical areas that are functionally relevant to the seed. Then, using these cortical structural covariance maps as features, we subdivide the thalamus into six non-overlapping regions (clusters of voxels), and assess whether cortical structural covariance is associated with cortical connectivity that specifically originates from these regions.We show that cortical structural covariance is high in areas of the cortex that are functionally related to the seed voxel, cortical structural covariance varies along cortical depth, and sharp transitions in cortical structural covariance profiles are observed when varying seed locations in the thalamus. Subdividing the thalamus based on structural covariance, we additionally demonstrate that the six thalamic clusters of voxels stratify cortical structural covariance along the dorsal–ventral, medial–lateral, and anterior–posterior axes. These cluster-associated structural covariance patterns are prominently detected in cortical regions innervated by fibers projecting out of their related thalamic subdivisions.Together, these results advance our understanding of how the thalamus and the cortex couple in their volumes. Our results indicate that these volume correlations reflect functional organization and structural connectivity, and further provides a novel segmentation of the mouse thalamus that can be used to examine thalamic structural variation and thalamocortical structural covariation in disease models.

Stroke-Related Visceral Alterations: A Voxel-Based Neuroanatomic Localization Study.

Functional and morphologic changes in extracranial organs can occur after acute brain injury. The neuroanatomic correlates of such changes are not fully known. Herein, we tested the hypothesis that brain infarcts are associated with cardiac and systemic abnormalities (CSAs) in a regionally specific manner. We generated voxelwise p value maps of brain infarcts for poststroke plasma cardiac troponin T (cTnT) elevation, QTc prolongation, in-hospital infection, and acute stress hyperglycemia (ASH) in 1,208 acute ischemic stroke patients prospectively recruited into the Heart-Brain Interactions Study. We examined the relationship between infarct location and CSAs using a permutation-based approach and identified clusters of contiguous voxels associated with p < 0.05. cTnT elevation not attributable to a known cardiac reason was detected in 5.5%, QTc prolongation in the absence of a known provoker in 21.2%, ASH in 33.9%, and poststroke infection in 13.6%. We identified significant, spatially segregated voxel clusters for each CSA. The clusters for troponin elevation and QTc prolongation mapped to the right hemisphere. There were 3 clusters for ASH, the largest of which was in the left hemisphere. We found 2 clusters for poststroke infection, one associated with pneumonia in the left and one with urinary tract infection in the right hemisphere. The relationship between infarct location and CSAs persisted after adjusting for infarct volume. Our results show that there are discrete regions of brain infarcts associated with CSAs. This information could be used to bootstrap toward new markers for better differentiation between neurogenic and non-neurogenic mechanisms of poststroke CSAs. ANN NEUROL 2023;94:1155-1163.

OS08.7.A DEPRESSIVE SYMPTOMS IN ASSOCIATION WITH TUMOR LOCATIONS AT DIAGNOSIS IN PATIENTS WITH DIFFUSE GLIOMA

Abstract BACKROUND Depressive symptoms are common in glioma patients and occur more frequent than in patients with other cancer types. The presence of tumors in specific brain regions that potentially disturb brain functions could contribute to this difference. These lesions may cause an inadequate emotional response to an incurable and lethal disease with consequences for patient counseling and neurosurgical strategies. In this study, we examine the association between brain tumor location and depressive symptoms at presentation in patients with diffuse glioma using several methods for lesion symptom mapping. MATERIAL AND METHODS The retrospective cohort consisted of patients with diffuse glioma who had a preoperative MR-scan and completed the Center for Epidemiologic Studies Depression scale (CES-D) before treatment. We classified patients based on unexpectedly low ( ≤6), intermediate (7-20) and unexpectedly high (&amp;gt;20) CES-D scores. Tumors were segmented in 3D and corresponding white matter disconnectomes were derived from normative tractography. We first correlated tumor and disconnectome with CES-D using sparse canonical correlation analysis to identify clusters of associated brain voxels. Next, we assessed the association between tumor locations and CES-D category using Bayesian multivariable categorical regression analysis of patient and tumor characteristics, including the overlap of tumors and disconnectomes with specific brain atlas structures, the probability of disconnection of white matter tracts, and functional network changes in local efficiency and eigenvector centrality. RESULTS We included 201 patients with a median age of 45 years (range 18-81), consisting of 62% males and 29% grade 4 gliomas. CES-D was completed a median of three weeks before surgery, was unexpectedly low in 29% and unexpectedly high in 15% of patients. Tumors located in the left (L) pallidum and right (R) thalamus were related to unexpectedly low CES-D, whereas tumors in the L hippocampus, L nucleus accumbens and R putamen were related to unexpectedly high CES-D. Disconnection of the R temporal subsection of the cingulum bundle, L optic radiation, L superior longitudinal fasciculus I and L uncinate fasciculus (UF) were related to unexpectedly low CES-D, whereas disconnection of the R corticospinal tract, R fornix, and L UF were related to unexpectedly high CES-D. Neither voxel clusters nor network measures were associated with CES-D. CONCLUSION Both unexpectedly low and unexpectedly high depressive symptom burden is common in patients with diffuse glioma at presentation. These dysfunctional emotional responses may be associated with the location of the tumor. Awareness of this phenomenon may be important in patient counseling and neurosurgical strategies. * these authors contributed equally

OS06.5.A CLINICAL AND LOCATION-SPECIFIC DETERMINANTS TO DISTINGUISH TUMOR PROGRESSION FROM TREATMENT-INDUCED EFFECTS IN HIGH GRADE GLIOMA

Abstract BACKGROUND Treatment response is an important early prognostic factor in high grade glioma, but distinguishing tumor progression from treatment-induced effects (TIEs) remains a difficult challenge in follow-up. The aim of this study was to explore tumor locations that might be associated with either tumor progression or TIEs. In addition, we investigated the role of clinical characteristics as covariates in classifying new or increasing contrast enhancements (CEs). MATERIAL AND METHODS We retrospectively included patients with histologically confirmed supratentorial WHO grade III or IV gliomas treated between 2011 and 2017. All patients who received first-time radiation therapy (RT), had at least 6 months of follow-up after RT and had new or increasing CE within the radiation field on follow-up MRI were included. Besides histological confirmation, new CEs were either defined, as TIEs when the lesions stabilized/decreased on subsequent imaging follow-up, or as tumor progression when the lesion grew or when anti-tumor treatment was started, in concordance with the RANO guidelines. Gross tumor volume (GTV) was investigated after non-linear registration to MNI stereotaxic space. Voxel-based analysis (VBA) was performed with family-wise error correction for multiple comparisons in order to identify voxels associated with either tumor progression or TIEs. Next, patient, tumor and treatment characteristics were multivariably analyzed as potential etiologic factors and confounders with regard to tumor progression or TIEs with binary logistic regression. Characteristics that showed a significant association were subsequently investigated with VBA. RESULTS The inclusion criteria were met by 407 patients. VBA showed a cluster of GTV voxels that was significantly associated with TIEs in the right temporal lobe, predominantly in the inferior longitudinal fasciculus (ILF). In multivariable analysis, clinical deterioration at time of new CE was associated with tumor progression (OR: 2.601; 95% CI: 1.649-4.102; P&amp;lt;0.001). An RT dose &amp;gt;58Gy EQD2 was significantly associated with TIEs (odds ratio (OR): 2.959; 95% confidence interval (CI): 1.043-8.403; P=0.041). No GTV voxels were significantly associated with clinical deterioration at time of new CE or with an RT dose &amp;gt;58Gy EQD2. CONCLUSION Our study identified a specific location in the right ILF that was associated with TIEs. Additionally, lower RT doses and clinical deterioration at time of new CE were more likely to be associated with tumor progression than TIEs in high grade glioma. However, these characteristics were not associated with any location, suggesting an independent relation between TIEs and the right ILF. These findings may help clinicians in distinguishing between tumor progression and TIEs in follow-up imaging, leading to more accurate diagnoses and appropriate treatment decisions.