bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validating noninvasive techniques for 11C‐ER176 PET quantification in controls and Alzheimer’s disease patients
Authors: Rossano Samantha , Talmasov Daniel , Johnson Aubrey S. , Smith Anna C. , Guzmán Diana S. , Okafor Amarachukwu , Kreisl William Charles , De Jager Philip L , Lao Patrick J. 
Published: December 2023

AbstractBackgroundNoninvasive yet accurate PET quantification methods are crucial for safe yet meaningful PET studies. [11C]ER176 is a PET radioligand that images neuroinflammation via the 18‐kDa translocator protein (TSPO), which is upregulated in activated microglia and has previously been a PET target in Alzheimer’s disease research. Currently, the gold‐standard method for quantifying ER176 PET is kinetic modeling of the dynamic PET data using the arterial input function (AIF), which is invasive and expensive. The current study explores a pseudo‐reference region (RR) technique to noninvasively quantify ER176 scans to facilitate clinical PET studies.MethodDynamic 90‐min [11C]ER176 PET scans were acquired in 11 participants, 5 controls (5M/0F) and 6 patients (3 MCI‐3M/0F; 3 AD‐2M/1F). Arterial blood data were collected throughout the duration of the scan and were used along with the dynamic imaging data to determine regional total volume of distribution (VT) using the two‐tissue compartment model. Standardized Uptake Value Ratio (SUVR) was calculated by normalizing the radioactivity in each region by that of the reference region (cerebellar gray matter). We explored differences across methods (AIF‐derived VT vs. RR‐derived SUVR) and across groups (controls vs. patients).ResultWithin each group, the outcome measures from AIF and RR methods were well correlated (Controls: R2 = 0.986, p < 0.001; Patients: R2 = 0.983, p < 0.001; Figure 1). Both methods showed greater TSPO expression in patients compared to controls, with mean differences in the medial temporal cortex of 14.99% between groups for VT and 10.65% between groups for SUVR, but lower variance for SUVR compared to VT (Figure 2). Both quantification methods showed similar regional patterns of percent differences between groups, corresponding to tau progression along Braak staging (Figure 3).ConclusionResults suggest that using the cerebellum, which does not accumulate amyloid plaques or tau aggregates until end‐stage disease, as a reference region for [11C]ER176 may be a valid method for quantifying differences between AD patients and controls compared to gold‐standard methodology. Regional increases in neuroinflammation are more reliable for SUVR than VT in AD‐related regions. Ongoing work includes a larger sample size to further validate noninvasive PET quantification.
Amyloid and Tau Predominance Subtyping Identifies CI Patients With Different Clinical Phenotypes
Authors: Zalzale Hussein , Povala Guilherme , Ferreira Pamela C.L. , Bellaver Bruna , Ferrari‐Souza João Pedro , Soares Carolina , Lussier Firoza Z , Aguzzoli Cristiano Schaffer , Lemaire Peter Charles , Abbas Sarah , Rohden Francieli , Leffa Douglas Teixeira , Cabrera Arlec , Therriault Joseph , Stevenson Alyssa , Pallen Vanessa , Ashton Nicholas J. , Benedet Andrea Lessa , Blennow Kaj , Zetterberg Henrik , Karikari Thomas K , Rosa‐Neto Pedro , Pascoal Tharick A. 
Published: December 2023

AbstractBackgroundThe ATN classification system assumes a sequential model of disease progression. However, there are groups of individuals in the same ATN category that exhibit a predominance of abnormality (higher burden) of one of the biomarkers, creating heterogeneous ATN groups regarding pathological predominance. Thus, we tested the hypothesis that individuals clustered by ATN biomarker abnormality predominance may offer an alternative to groups defined using biomarkers cut‐offs.MethodWe assessed 103 cognitively impaired individuals(CDR> = 0.5) from the TRIAD cohort with available measures of plasma phosphorylated tau‐181, brain MRI, amyloid PET, and tau PET. We used the K‐means algorithm to stratify participants into three clusters. We compared the clusters on composite measures of memory, executive functioning, language, and visuospatial processing. To examine the utility of the discovered clusters, we compared them to traditional ATN categories in the prediction of neuropsychological measures. We did so by creating three categories: patients positive on all three ATN biomarkers, patients positive on two of the three biomarkers, and patients positive on either one or none. Additionally, we created an inflammation, amyloid and tau deposition probabilistic map anchored on young controls(n = 51, mean age = 23.74).ResultWe uncovered 3 clusters: an amyloid predominant (AP) cluster, a tau/phosphor‐tau predominant cluster (TP), and a cluster showing no predominance with low levels on all biomarkers (CN)(figure 1). Notably, levels of neurodegeneration and inflammation were similar between the AP and TP clusters. The AP cluster significantly differed from the CN cluster in memory only. Participants in the TP cluster had significantly lower scores in memory, executive functioning, language, and visuospatial processing than the other two clusters. In comparison, using threshold‐based ATN groups showed milder differences in memory and executive functioning, and no differences in language and visuospatial processing(figure 2). Furthermore, cluster membership moderated the relationship between various biomarkers, to the point of reversing the direction of correlation(figure 3).ConclusionOur results highlight the biological heterogeneity present within the Alzheimer’s disease continuum and that the pathological predominance of amyloid and tau is associated with different disease phenotypes. Approaching dementia patients with an eye on the predominance of pathology rather than cutoffs for abnormality may provide a better understanding of AD pathological subtypes.
Atrophy of posteromedial sulci in aging and Alzheimer’s disease differs by sulcal type and location
Authors: Maboudian Samira A. , Willbrand Ethan H. , Jagust William J. , Weiner Kevin S. 
Published: December 2023

AbstractBackgroundRecent work has shown that the morphology of tertiary sulci — small, evolutionarily‐newer sulci that emerge last in gestation — is associated with individual differences in cognitive development and symptoms of neuropsychiatric disorders, but these sulci have not been investigated in aging. Here we extend these findings on tertiary sulci to the aging brain.MethodWe manually defined sulci on cortical surface reconstructions of T1 MRI scans in FreeSurfer and extracted the cortical thickness and mean anterior coordinate of each sulcus. We defined sulci in posteromedial cortex (PMC) in 72 younger adults (YA; age 18‐35) from the Human Connectome Project, 72 cognitively normal older adults (OA; age 65‐90) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and 72 age‐matched amyloid positive older adults with AD from ADNI: 4,341 sulci total. We used a mixed‐effects ANOVA to examine the effects of group (YA, OA, AD) as a between‐subject variable, and sulcal type (tertiary or non‐tertiary) and hemisphere (left/right) as within‐subject variables on sulcal cortical thickness. We used LASSO regression with nested cross‐validation for feature selection to determine which sulcal measures are most related to ADNI Memory Composite (MEM) scores, and LOOCV linear regression to predict MEM scores from the best model. Because not all sulci are found in all participants, only the most consistent were included in the LASSO models.ResultIn PMC, tertiary sulci show more age‐ and AD‐related thinning compared to non‐tertiary (group x sulcal type interaction p<.0001; Fig. 1). Additionally, atrophy in PMC shows a more anterior bias in aging that is absent in AD (Fig. 2). The best model for predicting ADNI‐MEM scores relies on a subset of mostly posterior sulci, suggesting a posterior shift in atrophy may be more related to cognitive decline (Fig. 3).ConclusionThis is the first study to investigate tertiary sulci in aging and AD. Results show tertiary sulci in PMC are especially vulnerable to atrophy in aging and that a subset of PMC sulci are particularly associated with memory. The results provide insight into the anatomical specificity of age‐ and AD‐related atrophy in PMC and its association with cognitive decline.
Influence of visible white matter lesions on volumes from automated parcellations
Authors: Sudre Carole H , Carrasco Ferran Prados , James Sarah‐Naomi , Wong Andrew , Malone Ian B , Cash David M , Fox Nick C , Cardoso M Jorge , Schott Jonathan M , Barnes Jo 
Published: December 2023

AbstractBackgroundWhite matter hyperintensities (WMH) are a common occurrence in ageing populations. Their hypointense appearance on T1‐weighted scans is known to affect automated processing and subsequent extraction of volumetric measurements. While lesion infilling with healthy appearing tissue is a common practice in the context of multiple sclerosis, this is not yet the case in studies of neurodegenerative diseases. We investigated the impact of WMH infilling on the volumetric outputs of two automated parcellation pipelines.MethodT1‐weighted and T2‐FLAIR scans were acquired for 462 individuals in the Insight46 neuroimaging substudy of the MRC National Survey for health and Development (NSHD). WMH were automatically segmented and T1‐weighted scans were subsequently infilled over the lesion masks. Two automated parcellation methods Geodesic Information Flows (GIF) and FastSurfer (FS) were run on the two T1‐weighted scans (original and infilled). Cortex, lateral ventricles, basal ganglia (BG), whole brain and total intracranial volumes (TIV) were derived from the four resulting parcellations. Spearman correlation was used to assess the relationship within and across methods according to infilling status. Correlations were also calculated between the observed volumes or percentage difference (original vs infilled volumes) and the WMH burden expressed as percentage of TIV.ResultThe relationship between parcellated volumes and WMH burden varied across methods and tissues/brain areas. While there was little observable relationship for GIF between brain volume or TIV difference and WMH, this relationship was positive for FS. The relationship with cortical volume difference was in opposite directions for GIF (negative relationship) and FS (positive relationship), indicating a tendency to decrease the estimated volume when WMH were visible for GIF and increase it for FS. For lateral ventricles and basal ganglia, volumetric measurements were higher in the presence of visible WMH for GIF and FS (Figure1). Correlations between FS and GIF were slightly stronger after infilling but correlation with WMH burden were attenuated (Table2).ConclusionThe impact of presence of visible WMH on T1‐weighted scan varies according to the chosen technique of analysis and strong correlations were observed between the difference in measured volumes and the WMH burden. Infilling should be considered when T1‐weighted derived volumes are studied.
Parental history of memory impairment predicts β‐amyloid burden and positivity in a preclinical population
Authors: Seto Mabel , Hohman Timothy J. , Mormino Elizabeth C. , Papp Kathryn V. , Amariglio Rebecca E. , Rentz Dorene M. , Johnson Keith A. , Schultz Aaron P. , Sperling Reisa A. , Buckley Rachel F. , Yang Hyun‐Sik 
Published: December 2023

AbstractBackgroundAlzheimer’s disease (AD) is highly heritable, and previous studies suggest that a maternal family history of AD confers a greater risk for AD than paternal history. Whether the maternal and paternal history of AD dementia impacts AD endophenotypes among cognitively unimpaired individuals is not fully described. We examine the effects of parental history of dementia on brain amyloid levels and both subjective and objective measures of cognition.MethodMeasures of objective and subjective cognition (Preclinical Alzheimer’s Cognitive Composite; Cognitive Function Index), APOE‐e4 genotype, ß‐amyloid (Aß) PET, and self‐reported parental history of memory impairment and AD dementia were obtained from 4,429 cognitively unimpaired individuals screening for the Anti‐Amyloid Treatment in Asymptomatic Alzheimer’s (A4) study (mean(SD); age = 71.2(4.7), %male = 40.7, %Non‐Hispanic White = 87.9). Aß was measured with 18F‐florbetapir‐PET using a mean neocortical composite referenced to whole cerebellum (Aß+threshold:1.11 SUVr). Linear regression models assessed the association between maternal or paternal history with cross‐sectional cortical Aß levels and cognition covarying for the participant’s age, sex, and years of education where relevant.ResultAs previously reported, parental history of memory impairment (one or both parents) was significantly associated with elevated neocortical Aß (p<0.001). The association between Aß and history in both parents remained significant when covarying for APOE‐e4 allele count (p = 0.002). In interaction models, parental history in either one or both parents did not modulate the association between APOE‐e4 and Aß. Mean amyloid levels were elevated in individuals with history in both parents (n = 456, p<0.001) and in those with only maternal family history (n = 1776, p<0.001), compared to those with only paternal history (n = 634) or no family history (n = 1563, Figure 1B). Regression models confirmed this finding: ß = 0.03, p<0.001 in individuals with maternal history, ß = 0.01, p = 0.1 in individuals with paternal history. The results remained consistent for participants whose parents received a clinical diagnosis of AD dementia (ßmaternal = 0.02, pmaternal = 0.01; ßpaternal = 0.02, ppaternal = 0.2). No associations with subjective or objective cognition were observed.ConclusionWe confirm that self‐reported family history of dementia is associated with elevated brain amyloid independently of APOE‐e4 status in the A4 Study, with evidence that maternal family history has a stronger impact on Aß burden among asymptomatic older individuals.
Characterizing the effects of chemotherapy on the brain of patients with head and neck cancer using FDG PET
Authors: Bishay Steven , Schwartz Trent , Smith David Samuel , Lee Lok Hin , Rosenthal Eben , Hohman Timothy J. , Jefferson Angela L. , Koran Mary Ellen 
Published: December 2023

AbstractBackgroundChemotherapy has known adverse effects on the brain. From small (N<30) studies primarily in breast cancer, we know that post‐chemotherapy brain changes can be detected with 18F ‐fluorodeoxyglucose positron emission tomography (FDG PET), but this has been relatively unexplored in other cancers, and has not been explored in patients with head and neck cancer (HNCa) (Chen, 2018). Patients with HNCa have 2‐3 times the risk of dementia after therapy compared to controls and may be particularly vulnerable given underlying lower levels of education and heavy tobacco and alcohol use (Zer, 2018). We will determine which areas of the brain are most vulnerable to the chemotherapy in HNCa with FDG PET.MethodPatients with HNCa were identified from Vanderbilt’s Cancer Registry, limited to patients with FDG PET in the last year (2021). 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 chemotherapy, including covariates of age, sex, ethnicity, and time between chemotherapy and follow‐up imaging using conservative family wise error of <0.05 and voxel extent threshold of 10.Result68 patients with HNCa met inclusion criteria and all patients received Carboplatin‐based chemotherapy (Table 1). Compared to baseline, 17 clusters met conservative significance thresholds with decreases in glucose metabolism following treatment (Figure 1). These included large regions (46397 1.5mm3 voxels) in the frontal and temporal lobes (pFWE = <0.001). Specifically, there was significantly decreased glucose metabolism in the dorsolateral prefrontal cortex (BA 9), frontoparietal cortex (BA 10), orbital frontal cortex (BA 11), medial and superior temporal gyri (BA 21, 22), dorsal (BA 24), and the subgenual (BA 25), pregenual (BA 32), and rostral (BA 33) anterior cingulate cortex post‐chemotherapy.ConclusionTo our knowledge, this is the first study to explore the effects of chemotherapy in HNCa, a population particularly vulnerable to these effects. We found that regions in the forebrain and temporal lobes are most vulnerable. Studies like these are important to establish and confirm spatial distributions of these effects which will be crucial for development of diagnostics and monitoring tools for these effects.
Mapping the effects of functional and structural network reorganization on the tau‐cognition relationship in Alzheimer’s disease
Authors: Ottoy Julie , Kang Min Su , de Wael Reinder Vos , Park Bo‐Yong , Bezgin Gleb , Lussier Firoza Z , Rahmouni Nesrine , Stevenson Jenna , Arias Jaime Fernandez , Soucy Jean‐Paul , Gauthier Serge , Bernhardt Boris , Black Sandra E. , Rosa‐Neto Pedro , Goubran Maged 
Published: December 2023

AbstractBackgroundTau pathology can spread through connectivity‐based networks, with certain regions (or epicenters) accumulating more tau than others. Such spatial vulnerabilities may be due to their unique apical position in the cortical hierarchy, which can be elucidated through ‘gradients of connectivity’ (Margulies 2016 PNAS). Prior work showed that the primary gradient of functional connectivity unveils a uni‐to‐transmodal topography of the healthy neocortex which highly correlates with a cognitive gradient of perception‐to‐abstraction. Here, we hypothesized that the gradients of functional/structural connectivity interact with tau to affect cognitive functions in Alzheimer’s disease (AD).MethodWe included 213 participants from TRIAD (103 CN Aß‐, 103 CN Aß+, and 75 CI Aß+) with diffusion‐weighted MRI, resting‐state functional MRI, 18F‐MK6240 tau‐PET, and an extensive cognitive battery. We performed non‐linear dimensionality reduction on the individual functional and structural connectomes, and extracted the first components (‘gradients’) ‐explaining most variance (G1FC and G1SC). First, we compared G1FC_or_SC between diagnostic groups. Second, we investigated the interaction effect of G1FC_or_SC*tauSUVR on cognition (across 9 cognitive domains). Last, we investigated whether the tau‐cognition relationship changed in a topography‐specific manner along the cortical hierarchy, within (equally‐sized) gradient‐derived meta‐ROIs along G1FC_or_SC. Results were compared to Braak‐derived regional associations. Analyses were adjusted for age, sex, APOE, education, and multiple comparisons.ResultWe observed reduced segregation of functional networks in AD compared to controls, with unimodal (lower‐order cognitive) and transmodal (higher‐order cognitive) regions moving closer on G1FC. This may indicate loss of network specialization in AD. Participants who had both higher tau and G1FC alterations had more cognitive impairment (Fig.1A; shown for MMSE/language). This interaction‐effect was less pronounced with G1SC (Fig.1B). Last, tau correlated with cognition in a topography‐specific progressive manner (i.e., along the transmodal‐unimodal G1FC axis and anterior‐posterior G1SC axis) (Fig.1C). Notably, tau correlated with delayed memory progressively along the posterior‐anterior G1SC axis (R2 = 0.93 in all and R2 = 0.95 in A+) and BraakI‐VI axis (R2 = 0.77 in all and R2 = 0.28 in A+).ConclusionOur work supports the contribution of connectome‐driven tau distribution on cognitive impairment in AD. Connectome gradients may provide a spatial framework to study tau spreading along the major axes of brain organization underlying specific cognitive domains.
Characterizing the effects of COVID‐19 on the brain using FDG PET imaging before and after COVID‐19 infection
Authors: Bishay Steven , Schwartz Trent , Smith David Samuel , Lee Lok Hin , Reid Sonya , Hohman Timothy J. , Jefferson Angela L. , Warner Jeremy , Koran Mary Ellen 
Published: December 2023

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 < 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 < 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.