bluuebunny/crossref_metadata_2025 huggingface dataset:
Tau deposition patterns within the medial temporal lobe follow the connectivity of the entorhinal cortex – a combined post‐mortem and 7T fMRI study
Authors: Franzmeier Nicolai , Berron David , Binette Alexa Pichet , Grande Xenia , Hansson Oskar , Ossenkoppele Rik
Published: December 2023

Background

In aging, tau pathology develops in the medial temporal lobe (MTL), but spreads extensively to the cortex in the presence of amyloid‐beta, driving neurodegeneration and Alzheimer’s disease (AD) dementia development. This suggests that earliest age‐related MTL tau is a pre‐requisite for cortical tau spreading and the development of AD. Using tau‐PET in AD, we found previously that functional connectivity routes the cortical expansion of tau, supporting the concept of trans‐neuronal tau spreading. However, it is unclear whether MTL tau accumulation follows within‐MTL connections, in particular those of the entorhinal (EC) and transentorhinal cortex (A35), i.e. the earliest sites of tau accumulation. To address this, we combined post‐mortem histopathological MTL tau assessments with high‐resolution 7T functional MRI to determine MTL subregional connectivity.

Method

We included 3D post‐mortem quantitative histopathological tau assessments of 14 MTL subregions (Fig.1A) in 18 participants with overall low AD neuropathological change to capture earliest tau (Fig.1B), and 7T resting‐state fMRI from young and healthy controls (n = 29) to characterize MTL functional connectivity. Using post‐mortem data, we assessed the covariance of AT8‐stained tau among MTL subregions (Fig.1C) and assessed the correlation with functional connectivity among the same regions (Fig.1D). Further, we determined seed‐based connectivity to determine which MTL subregions connectivity pattern was the best predictor of MTL‐wide tau patterns.

Result

Post‐mortem tau levels were highest in the amygdala, followed by A35 and the EC (Fig.2A). As hypothesized, we found an association between MTL connectivity and covariance in MTL tau (r = 0.42, p<0.001, Fig.2B), where closely connected regions showed correlated tau. When assessing seed‐based connectivity as a predictor of MTL tau patterns, EC connectivity was the best predictor for MTL tau deposition patterns (Fig.2C).

Conclusion

Closely connected MTL subregions show correlated histopathologically‐assessed tau load, suggesting connectivity to route earliest within MTL tau spreading. Despite highest tau in the amygdala, EC connectivity was the best predictor of MTL tau patterns, suggesting that the EC is a key source for within MTL tau spreading. This can be critical to assess EC connectivity as a potential treatment target to prevent cortical tau spreading and thus neurodegeneration and cognitive decline in AD.
Age‐ and Sex‐Related Morphological Changes in Cerebral Blood Vessels: a 7T TOF MRA Study
Authors: Li Jiatai , Stetten George D , Schweitzer Noah , Shi Zonghua , Ibrahim Tamer , Yang Shaolin , Iordanova Bistra , Aizenstein Howard J , Wu Minjie
Published: December 2023

Background

In this study we evaluated age‐ and sex‐associated morphological changes of cerebral blood vessels using 7T Time‐of‐flight (TOF) magnetic resonance angiography (MRA).

Method

Our study consisted of 25 cognitively normal older adults (20 female, mean age 68.2 years). Whole‐Brain TOF MRA images were collected on a 7T Siemens scanner at the University of Pittsburgh (slice number = 354, voxel size = 0.38*0.38*0.38 mm, 12 mins). An iterative vessel segmentation algorithm, VesselMapper, was used to segment blood vessels on TOF MRA images (Li et al., 2023). For each subject, vessels are further divided into large and small vessels by median split based on vessel diameters. Mean tortuosity of large vessels, small vessels and overall vessels was computed. Linear regression analyses were performed to evaluate the main effects of age and sex, and the age*sex interaction on vessel tortuosity and diameter.

Result

As shown in Figure 1, we found age‐related increase in mean vessel tortuosity (greater age is associated with greater tortuosity, p<0.02). This age‐related difference is driven by small vessels (p = 0.002) rather than large vessels (p = 0.7). We also found that age is positively associated with mean voxel tortuosity (p<0.001, black line in Figure 2). Furthermore, women showed greater age‐related increase in mean arterial tortuosity, compared to men (age*sex interaction p = 0.04, Figure 2).

Conclusion

Our findings validated that morphological markers of cerebral blood vessels are sensitive to aging. Small vessels in the brain are particularly vulnerable. Further, compared to men, older women are at a higher risk for cerebral small vessel disease, which may contribute to elevated SVD‐related AD risk in women. Limitation: The study has an unbalanced sample (more women than men) and a relatively modest sample size (N = 25). A cross‐sectional instead of longitudinal design was used in this analysis. Future study with a large balanced sample and a longitudinal design are required to confirm our findings. Reference: Li, Jiatai, et al. “VesselMapper ‐ A Robust Vessel Segmentation Algorithm for 3D Images.” Annual Meeting of the Organization for Human Brain Mapping. 2023
Astrocyte reactivity is associated with synaptic dysfunction across the aging and Alzheimer’s disease spectrum, whereas microglial reactivity is specifically associated with synaptic dysfunction related to cognitive impairment
Authors: Rohden Francieli , Ferreira Pamela C.L. , Bellaver Bruna , Aguzzoli Cristiano Schaffer , Soares Carolina , Povala Guilherme , Ferrari‐Souza João Pedro , Lussier Firoza Z , Zalzale Hussein , Abbas Sarah , Lemaire Peter Charles , Leffa Douglas Teixeira , Cabrera Arlec , Tissot Cécile , Therriault Joseph , Servaes Stijn , Stevenson Jenna , Rahmouni Nesrine , Benedet Andrea Lessa , Cohen Annie , Lopez Oscar L. , Ashton Nicholas J. , Karikari Thomas K , Zetterberg Henrik , Blennow Kaj , Souza Diogo O. , Zimmer Eduardo R , Rosa‐Neto Pedro , Pascoal Tharick A.
Published: December 2023

Background

Healthy synapses are the key to proper brain function, ensuring communication between neurons. Recent studies have associated synaptic dysfunction with Alzheimer’s disease (AD) proteins, however, little is known about the role of glial reactivity, another pathology closely linked to AD, in brain synaptic dysfunction (Figure 1).

Method

We evaluated 123 individuals (67 cognitively unimpaired (CU) and 56 cognitively impaired (CI)) who had available Aß‐ and Tau‐PET as well as cerebrospinal fluid measures of glial fibrillary acidic protein (GFAP), chitinase‐3‐like protein 1 (YKL‐40), soluble triggering receptor expressed on myeloid cells 2 (sTREM2), synaptic markers (growth‐associated protein 43 (GAP‐43), neurogranin (Ng), synaptotagmin 1 (SYT1), and presynaptic protein synaptosomal‐associated protein 25 (SNAP‐25)). ANCOVA adjusted for clinical diagnosis, age, and sex was used to compare levels of CSF biomarkers; whereas linear regressions adjusted for age, sex, clinical diagnosis, and Aß/tau‐PET were used to test the associations between glial reactivity and synaptic markers.

Result

Demographic information is shown in Table 1. Increased levels of GAP‐43, SNAP‐25, and Ng were observed in CI compared to CU individuals. CSF GFAP was highly associated with both presynaptic and postsynaptic biomarkers in CU and CI groups. CSF YKL‐40 was associated only with presynaptic biomarkers in both clinical groups. On the other hand, CSF sTREM2 showed an association with all synaptic markers but only in the CI group (Figure 2).

Conclusion

We found a heterogeneous association between synaptic markers and glial activation. The presence of GFAP+ astrocytes was associated with dysfunction of presynaptic/postsynaptic markers, whereas YKL‐40+ astrocytes specifically reflected presynaptic dysfunction across aging and AD spectrums. On the other hand, microglial activation reflected synaptic dysfunction associated with dementia symptoms. Our results support recent experimental observations suggesting that clarifying the heterogeneity of different glial cell phenotypes is crucial to advancing our understanding of the role of immune cells in cognitive decline.
T1 MRI reveals differential hippocampal atrophy in Lewy Body Disorders with and without Alzheimer’s copathology
Authors: Cohen Jesse S , Phillips Jeffrey S , Das Sandhitsu R. , Rhodes Emma , Cousins Katheryn A Q , Yushkevich Paul A. , Wolk David A. , Weintraub Daniel , Irwin David J. , McMillan Corey T
Published: December 2023

Background

Lewy body disorders (LBD) include Parkinson disease (PD), Parkinson disease dementia (PDD), and dementia with Lewy bodies (DLB). LBD are the second leading cause of neurodegenerative dementia after Alzheimer’s disease (AD). An estimated 50% of LBD patients have coexisting AD pathology (LBD+AD), which correlates with shorter time to dementia and death. Autopsy evidence suggests that verbal memory impairment correlates with the severity of hippocampal tau pathology in LBD. However, it is unknown whether greater hippocampal tau burden in LBD+AD causes neurodegeneration detectable by in vivo structural MRI, and whether hippocampal atrophy explains verbal memory impairment.

Method

Using a case‐control design, we studied 87 patients with clinical diagnoses of LBD (PD, n = 52; PDD, n = 12; DLB, n = 23) with available T1 MRI and AD biomarkers or, and cognitively‐normal controls (n = 131). AD copathology was defined hierarchically by: a) AD “intermediate” or “high” by ABC neuropathologic criteria; 2) positive amyloid PET; and 3) CSF total tau:ß‐amyloid1‐42 ratio > 0.3 (autopsy‐validated cutpoint). The Automated Segmentation of Hippocampal Subfields (ASHS) pipeline was applied to subjects’ T1 MRIs. Hippocampal volume (HV) was compared between controls, LBD‐AD, and LBD+AD, and correlated with verbal memory scores. Linear regression was used to test the association of AD copathology (independent variable) and HV (dependent variable), covarying for age, sex, education, and clinical diagnosis.

Result

Statistically significant differences (ANOVA p = 0.002) in bilateral HV (expressed as percentage of intracranial volume) were seen between groups (mean 0.456for controls, 0.444±0.045 for LBD‐AD, and 0.416±0.063 for LBD+AD). Tukey’s test showed significant differences between LBD+AD vs controls (p = 0.001) and LBD+AD vs. LBD‐AD (p = 0.047). Linear regression showed statistically significant association of LBD+AD with bilateral HV (p = 0.034). Among all LBD patients, hippocampal volume positively correlated with verbal memory (immediate recall: r2 = 0.24, p = 0.033, delayed recall: r2 = 0.22, p = 0.042, recognition discrimination r2 = 0.58, p<0.001).

Conclusion

In patients with LBD, AD copathology is associated with increased hippocampal atrophy as measured by in vivo T1 MRI, which correlates with greater verbal memory deficits. This work supports the that AD copathology impairs cognition in LBD via hippocampal neurodegeneration.
Ante‐mortem magnetic resonance imaging grey‐white matter contrast regional signatures of Alzheimer’s disease neuropathology
Authors: Almeida Francisco , Coelho Ana , Quintas‐Neves Miguel , Teylan Merilee A. , Mock Charles , Kukull Walter A. , Crary John F. , Oliveira Tiago Gil
Published: December 2023

Background

Grey matter (GM), white matter (WM) contrast (GWC) in T1‐weighted MRI has been shown to decrease with age in healthy populations and cognitive impairment in clinical Alzheimer’s Disease (AD). However, the neuropathological determinants of this signal remain unknown. Here, we aimed to study whether GWC is associated with AD neuropathology and longitudinal hippocampal atrophy.

Method

157 patients with neuropathological, clinical data and ante‐mortem MRI were selected from the National Alzheimer’s Coordinating Center database. Cortical volume and GWC (WM/GM intensity) in T1/MRI were obtained with Freesurfer 6.0. Hippocampal volume was divided into anterior, intermediate and posterior regions using a lab‐based algorithm. Correlational analysis was conducted for GWC with age, and GWC residuals after linear regression with age for volume, BRAAK stage (neurofibrillary tangles), CERAD score (neuritic plaque density) and Cognitive Dementia Rating Sum‐of‐Boxes (CDR‐SB). APOE genotypes were compared using one‐way‐ANOVA.

Result

GWC was negatively correlated with age in widespread brain areas (p < 0.05, FDR), but only the entorhinal cortex showed a positive correlation between volume and GWC. There were no significant correlations between GWC and BRAAK stage, CERAD score, CDR‐SB or differences according to APOE genotype. Entorhinal GWC correlated positively only with the posterior hippocampal volume in BRAAK III‐IV.

Conclusion

GWC is highly modulated by age, but not by classical AD neuropathology, APOE genotype or dementia severity in this cohort. Entorhinal GWC correlates with entorhinal and posterior hippocampal volume, suggesting it might reflect an early pathophysiological process distinct from classical AD neuropathology.
tau‐neurodegeneration mismatch from inter‐modality image translation using deep learning
Authors: Lyu Xueying , Khandelwal Pulkit , Duong Michael Tran , Wang Jiancong , Xie Long , Wisse Laura EM , Yushkevich Paul A. , Das Sandhitsu R. , Wolk David A.
Published: December 2023

Background

The 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.

Method

We 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.

Result

The 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.

Conclusion

Our findings support a deep‐learning T‐N mismatch approach for disentangling AD heterogeneity.
Association between brain [18F]FDG‐PET signal and genetic cell markers in the brain tissue
Authors: Machado Luiza Santos , De Bastiani Marco Antônio , da Rocha Andreia Silva , Bellaver Bruna , Soares Carolina , Povala Guilherme , Rahmouni Nesrine , de Souza Débora Guerini , Pascoal Tharick A. , Souza Diogo O. , Rosa‐Neto Pedro , Benedet Andrea Lessa , Blennow Kaj , Zetterberg Henrik , Ashton Nicholas J. , Ferreira Pamela C.L. , Zimmer Eduardo R.
Published: December 2023

Background

Brain glucose hypometabolism, indexed by [18F]FDG‐PET, is considered a biomarker of neurodegeneration in Alzheimer’s disease (AD). However, other brain cells, such as astrocytes and microglia, also consume considerable amounts of glucose and may contribute to the [18F]FDG‐PET signal in the brain. Thus, the cellular source of the [18F]FDG‐PET signal remains controversial. Here, we aimed to evaluate whether canonical markers of different brain cell types (neuron, oligodendrocyte, astrocyte, and microglia) associate with brain [18F]FDG‐PET signal in humans and a rat model of human amyloidosis.

Method

[18F]FDG‐PET images were acquired in ten‐month‐old APP/PS1 (TgF344‐AD, n = 8) and wild‐type (WT, n = 6) rats. Next, we evaluated the gene expression of NeuN, Olig2, GFAP, S100B, and IBA1 in the frontal and temporoparietal cortices and cerebellum. Association maps integrating mRNA with brain [18F]FDG‐PET signal were conducted at the voxel level using RMINC. [18F]FDG‐PET and brain tissue mRNA (GFAP, ACSA2, S100B, GLAST, IBA1, CSF1R, TREM2, Olig2, Cldn11, NeuN) of cognitively unimpaired patients were obtained from ADNI and Allen Brain Atlas database, respectively. In humans, mean regional [18F]FDG‐PET SUVr (reference region: pons) and mRNA expression were used to evaluate their association using a gaussian model. Differences were considered statistically significant at p<0.05 (t>2).

Result

GFAP and S100B mRNA levels in the temporoparietal and frontal cortices positively correlated with brain [18F]FDG‐PET signal (local maxima, GFAPt(13) = 9.4, S100Bt(13) = 6.6; Fig1B‐C). No associations were found with TREM2, Olig2 and NeuN (t(13)<2; Fig1D‐F). We expanded our analysis by comparing gene astrocyte markers and astrocyte gene cell markers in humans. At the regional level, we found that FDG‐PET SUVr and astrocyte mRNA were positively associated: S100B (R‐squared = 0.34), GFAP (R‐squared = 0.33), GLAST (R‐squared = 0.31) and ACSA‐2 (R‐squared = 0.31; Fig1G).

Conclusion

Our findings suggest astrocyte mRNA markers are more closely associated with brain [18F]FDG‐PET signal than neuronal, oligodendrocyte, and microglial mRNA markers.
Deciphering the role of p‐tau, iron and MAOB in neurobiological basis of F18‐flortaucipir signal with voxel‐to‐voxel histology to PET analysis in different tauopathies
Authors: Chen Yuheng , La Joie Renaud , Li Song Hua , Tosun Duygu , Ushizima Daniela , Seeley William W. , Spina Salvatore , Heinsen Helmut , Rabinovici Gil D. , Grinberg Lea T.
Published: December 2023

Background

Flortaucipir F18 was the first FDA approved PET tracer to detect tau pathology. Previous studies show that Flortaucipir is more sensitive to Alzheimer’s disease (AD) tau than four‐repeat tauopathies. Furthermore, the neurobiological basis of low Flortaucipir signal remain unclear, especially in basal ganglia. In this study, we aimed to identify the contributions of p‐tau (Ser 202), iron and MAOB to Flortaucipir signal in different tauopathies by performing voxel‐to‐voxel correlations between histological inclusion density maps and ante‐mortem flortaucipir PET uptake.

Method

Coronal slides of ∼1cm thickness from four tauopathy cases (AD, progressive supranuclear palsy, corticobasal degeneration, and FTLD due to MAPT mutation P305S) and one FTLD‐TDP type‐A case were processed following a computational/histopathology pipeline (Ushizima, Chen, et al. 2021), allowing for whole 3D reconstruction of the histological maps at microscopical level, point‐by‐point aligned to their corresponding MRI T1 images (Figure 1). Serial 120 µm‐thick histological slides underwent immunohistochemistry to p‐tau (Ser 202, CP‐13) and MAOB, and Perl’s iron staining. Density of pathological changes per voxel (1.22×1.22×120um³) was measured using convolution neural network algorithm. Flortaucipir images were thresholded at 1.2 SUVR. Spearman’s bivariate and multiple linear regressions were used to compare Flortaucipir PET uptake to histological CP13/iron/MAOB counterparts. We examined both areas with high Flortaucipir PET uptake and high histological CP13/iron/MAOB burden.

Result

Table 1 show patient features. Figure 2 depicts voxel‐to‐voxel correlations result in scatter plot and bivariate/multiple linear regression analysis.

Conclusion

The correlation of CP13 (p‐Tau) to Flortaucipir was higher in AD than other tauopathies. Iron deposits contributed to Flortaucipir uptake in regions both with or without histopathologically confirmed p‐tau, including basal ganglia, whereas MAOB contribution was almost null in gray matter. The time gap between PET and autopsy and lower PET resolution compared to histology may explain the moderate regression coefficients, but other unexplored contributors cannot be discarded. Voxel‐to‐voxel histology to neuroimaging correlations allow for investigating multiple components of the neurological basis of PET. We are finalizing the regression analysis based on areas of high histological burden.
Effect of Age Range on Power for a Clinical Trial Investigating the Effect of Intensive Systolic Blood Pressure Control on White Matter Hyperintensity Volume Accumulation
Authors: Pruzin Jeremy J. , Chen Yinghua , Chen Kewei , Koijs Daniel , Newby Danielle , Winchester Laura M , Thomas Ronald G. , McGrath Emer R , Su Yi , Reboussin David M. , Pajewski Nicholas M. , Beiser Alexa S. , Seshadri Sudha , Tariot Pierre N.
Published: December 2023

Background

Epidemiological evidence has repeatedly demonstrated elevated systolic blood pressure (SBP) in midlife as a modifiable risk factor for Alzheimer’s Disease and Related Dementia (ADRD) later in life. Despite SBP being readily treatable with safe and inexpensive medications, no clinical intervention implementing a lower SBP goal (<120 mm Hg) in midlife to lower future ADRD risk has ever been attempted. Clinical outcomes are not practical in the age range of interest (45‐65 or 45‐70) during an initial trial period of 5 years however robust evidence demonstrates white matter hyperintensity volume (WMHV) as an MRI finding associated with and predictive of incident ADRD.

Method

We used four data sets (SPRINT, Wisconsin Registry for Alzheimer’s Prevention, Framingham, and UK Biobank) with longitudinal MRI data to examine the effect of age range on power for a clinical trial proposal investigating the effect of intensive SBP control on annualized rates of WMHV accumulation in persons starting in middle age. Analyses were conducted separately in each data set. We calculated mean, standard deviations, and annualized rates of WMHV accumulation (derived from T2 FLAIR MRI), using the linear rate of change for accumulation rate, first stratifying by SBP ( = 132 mm Hg vs <132mm Hg except in SPRINT where groups were stratified by goal SBP group) and then by various age ranges. Next, we examined the effect of age range on necessary sample size with 80% power and two‐tailed alpha of 0.05 for a prospective clinical trial.

Result

As expected, annualized WMHV accumulation rate is lower with younger age in all data sets. However, variability decreased (all four data sets) and the percent reduction achieved at lower SBPs is higher at younger ages (3/4 data sets), thus increasing power when excluding older individuals (e.g., >65 years old, Table 1).

Conclusion

Restricting age to individuals to = 65 years‐old may unexpectedly increase power in a clinical trial designed to investigate the effect of goal SBP<120 mm Hg on annualized WMHV accumulation rate. 45‐65 years‐old is a practical age range for the first ever clinical trial intended to investigate the effects of a lower SBP goal in middle age to reduce future ADRD risk.
Multi‐channel segmentation allows simultaneous estimation of classic tissue compartments, WMH and enlarged perivascular spaces
Authors: Gunter Jeffrey L. , Przybelski Scott A. , Sparrman Kohl Johnson , Cogswell Petrice M , Radford Jonathan Graff , Knopman David S. , Petersen Ronald C. , Vemuri Prashanthi , Jack Clifford R. , Persons Benjamin
Published: December 2023

Background

Large neuroimaging studies like ADNI‐4 now include T1‐weighted, T2‐weighted and FLAIR images at isotropic1mm resolution for investigation of both neurodegenerative and cerebrovascular disease. These three input types allow segmentation of GM, WM, DeepGM, WMH, and CSF compartments. Additionally, this supports automated assessment of enlarged perivascular spaces (PVS). Our objective was to propose a unified framework for segmentation of intracranial classes and PVS while reducing human effort.

Method

FLAIR and T2‐weighted images are aligned to the T1‐weighted image.. Standard SPM12 unified segmentation using all three input images establishes deformations between subject and template space and bias field corrections. Extended tissue priors including deep GM are deformed into subject space. Adding mean intensities from high probability deep GM voxels as seeds and using the extended prior set, segmentation is re‐started, refining model parameters, deformations and bias‐field estimates. The procedure repeats, adding a WMH channel, resulting in a segmentation including GM, WM, CSF, deep GM, WMH and nuisance classes. Frangi filters are applied to the T1‐ and T2‐ weighted images. Filter response images are smoothed, averaged, masked and inserted in place of the CSF prior. Probability maps of vessel‐like shapes with CSF‐like contrast are estimated to identify PVS. Visual grading was also performed for comparison.

Result

The method was applied to 300 participants. Visual quality control found two instances of poor WMH over‐segmentation. Perivascular space maps were all visually reasonable. Standard segmentation classes were visibly superior to single T1‐based segmentation. Figures 1,2 present examples. Pearson correlations of PVS fractional volume with multiple human raters’ PVS counts in CSO/CR was over 0.7 in a subset of 125 participants (Figure 3).

Conclusion

Modern dementia protocols include high‐resolution T1‐weighted, T2‐weighted, and FLAIR images that can be used together as inputs to extend probabilistic segmentation adding deep grey and WMH classes with automated PVS assessment.
An automated pipeline for Centiloid quantification of amyloid‐β using multiple 11C‐PiB‐PET and 18F‐PET tracers
Authors: Gordon Elizabeth , Borrot Mathilde , Gueddou Ayoub , Jubault Thomas , Guizard Nicolas
Published: December 2023

Background

Quantitative measures of amyloid‐ß (Aß) pathology using positron emission tomography (PET) imaging are sensitive to identify pathological changes early in Alzheimer’s disease (AD). The Centiloid scale aims to standardize these in vivo amyloid quantifications to a 100‐point scale, where an average value of zero signifies high certainty of amyloid negativity and 100 identifies average typical AD Aß‐pathology load (Klunk et al., 2015). The current study developed and validated a single and fully automated Centiloid quantification pipeline for multiple amyloid PET compounds.

Method

QyScore’s® fully automated pipeline was validated on 11C‐PiB‐PET and 18F‐PET images from the Centiloid project (https://www.gaain.org/centiloid‐project): 34 young controls [age = 31.5 ± 6.3 years] and 47 AD patients [age = 67.5 ± 10.5 years; CDR = 0.5–1]. 18F tracers included Florbetapir (FBP, N = 46), Forbetaben (FBB, N = 35), Flutemetamol (FTM, N = 74) and NAV4694 (NAV, N = 55). PET/MR image pairs were both co‐registered and normalized in the MNI template space. The fully automated segmentation from QyScore®, a CE‐marked and FDA‐cleared neuroimaging medical device, parcellated the masks of the grey matter tissue (target) and of the cerebellum (reference) region (Figure 1). The standardized uptake value ratio (SUVr) was computed as the ratio of the mean signal in both regions. Correlations of 11C‐PiB‐PET and 18F‐PET SUVr values with published SUVr data were computed. Further, correlations between 18F‐PET SUVr and paired 11C‐PiB‐PET SUVr were computed. Correlation coefficients (R2) > 0.7 were required to consider the Centiloid calibration valid.

Result

QyScore’s® fully automated quantitative pipeline produced SUVr values well within the bounds defined by the Centiloid method (SUVr_AD‐100 = 2.08 +/‐ 0.2; SUVr_YC‐0 = 1.01+/‐ 0.05; R2 = 0.99; slope = 1.00; intercept = ‐0.44). 11C‐PiB SUVr correlation coefficients with published values were above 0.99 (Figure 2). Correlation coefficients of 18F‐PET SUVr with 11C‐PiB‐PET SUVr were respectively 0.91, 0.95, 0.96, 0.99 (Figure 3). Equations for converting to Centiloid were respectively: • Centiloid = 177.79 FBP_SUVr ‐ 183.56 • Centiloid = 153.08 FBB_SUVr – 152.93 • Centiloid = 122.39 FTM_SUVr – 120.97 • Centiloid = 90.20 NAV_SUVr – 91.61

Conclusion

We demonstrate the feasibility and reliability of a fully automated amyloid PET pipeline for multiple amyloid‐PET compounds (11C‐PiB and 18F) suitable for implementation in clinical trials.
Cohort heterogeneity and AD biomarkers in older adults without significant cognitive impairment: A comparison of U.S. POINTER and ADNI
Authors: Landau Susan M. , Harrison Theresa M. , Ward Tyler J. , Baker Suzanne L. , Koeppe Robert A. , Vemuri Prashanthi , Lockhart Samuel N. , Jung Youngkyoo , Harvey Danielle J. , Lovato Laura , Toga Arthur W. , Masdeu Joseph C. , Oh Hwamee , Gitelman Darren R. , Aggarwal Neelum T. , Farias Sarah Tomaszewski , Papp Kathryn V. , Snyder Heather M , Baker Laura D , Decarli Charles , Jagust William J.
Published: December 2023

Background

A key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.

Method

To examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aß and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aß‐negative individuals <70yrs and with global CDR = 0).

Result

U.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aß+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.

Conclusion

Heterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.
Associations of NREM Slow Wave Activity and Regional in‐vivo tau PET deposition in black and white community‐dwelling cognitively normal older‐adults with normal sleep
Authors: Bubu Omonigho Michael M , Umasabor‐Bubu Ogie Queen , Kovbasyuk Zanetta , Valkanova Elena M , Mbah Alfred , Cejudo Jaime Ramos , Turner Arlener , Hu Lu , Williams Natasha , Jean‐Louis Girardin A , de Leon Mony J. , Masurkar Arjun V. , Wisniewski Thomas , Varga Andrew , Osorio Ricardo S
Published: December 2023

Background

In this proof‐of‐concept study, we examined whether NREM slow wave activity (SWA) is associated with regional in‐vivo tau deposition; and whether race‐specific differences exist in this association, in clinically normal older adults with normal sleep, in the context of Aß.

Method

This was a cross‐sectional analysis of baseline data from 21 community‐dwelling cognitively normal older‐adults with normal sleep. Participants were matched on age, sex, BMI, and APOE4 carrier status in a 1:3 ratio, blacks: whites. Normal sleep was defined as 6‐9 h of total sleep time and absence of AHI4%>15 and AHI4%>5 with sleepiness. SWA was defined as power between 0.5‐4.0 Hz during NREM with NREM cycles characterized as stages NREM 2‐3 of = 15 min. terminated by rapid eye movement (REM) or wakefulness of = 5 min. Tau burden was assessed using 18F‐PI2620. Linear mixed‐effects models with random intercept and slope were used to assess associations between NREM SWA, and regional in‐vivo tau PET deposition, respectively, controlling for Aß, age, BMI, sex, APOE4‐status, education and other sleep variables.

Result

Of the 21 participants, 7 (33.3%) were black, 12 (57.1%) were women and 5 (24%) were APOE4 carriers. The mean (SD) age, and education were 69.1 (5.5), and 17.2 (3.8) years respectively. NREM SWA was associated with tau deposition in the entorhinal cortex, inferior and middle temporal ROIs, including gray matter neocortical ROIs i.e., anterior ventral striatum, orbitofrontal, precuneus, superior frontal, lateral temporal and posterior cingulate gyrus cortices (p <.01 for all). Racial differences existed in the entorhinal cortex, and inferior and middle temporal ROIs, including the lateral temporal, parietal, precuneus and posterior cingulate gyrus cortices (p <.02 for all), with black participants having lower tau levels relative to white participants. Divergent NREM SWA and tau associations were observed in the entorhinal cortex, precuneus, and inferior and middle temporal ROIs with NREM SWA negatively correlated with tau‐PET levels in whites and positively correlated in blacks.

Conclusion

Racial differences in physiological sleep features, uniquely associated with tau levels in the brain, may reflect one mechanism of how sociocultural factors, often through behavioral processes, become physiologically expressed as increased AD‐risk in blacks.
A multivariate MRI model of Alzheimer’s disease risk is associated with clinical diagnosis, PET imaging, and plasma biomarkers in a mixed dementia sample
Authors: Phillips Jeffrey S , Govindarajan Sindhuja Tirumalai , Hwang Gyujoon , Erus Guray , Cousins Katheryn A Q , Das Sandhitsu R. , Wolk David A. , Irwin David J. , Grossman Murray , Nasrallah Ilya M. , Davatzikos Christos
Published: December 2023

Background

We sought to validate two structural MRI‐based brain health models: Spatial Pattern of Atrophy for REcognition of Alzheimer’s disease (SPARE‐AD) and SPARE‐Brain Age Gap (SPARE‐BAG), which estimates the discrepancy between biological brain age and chronological age. These models' generalization to non‐amnestic AD (naAD) syndromes and associations with positron emission tomography (PET) and plasma biomarkers remain underinvestigated. We hypothesized that SPARE‐AD scores in naAD would be lower (less abnormal) than in amnestic AD (aAD) but elevated (more abnormal) relative to controls; and that SPARE‐AD but not SPARE‐BAG scores would be associated with PET and plasma biomarkers of AD.

Method

SPARE‐AD and SPARE‐BAG scores were estimated for each of 1607 MRI scans from 277 cognitively normal adults (62.8% female; mean age = 69.5 years) and 902 clinical participants (54.2% female; mean age = 73.1 years), including 585 with amnestic mild cognitive impairment (aMCI) or aAD; 56 with naAD syndromes; 28 with vascular disease; 28 with Lewy body disorders (LBD); 18 with suspected frontotemporal lobar degeneration (FTLD); 56 with non‐amnestic MCI of uncertain etiology; and 131 with other clinical diagnoses. We used mixed effects models adjusting for age, sex, and global cognition to test group differences in SPARE‐AD and SPARE‐BAG. Additionally, we assessed associations with tau (n = 122) and amyloid‐beta (n = 199) PET imaging and plasma‐based phosphorylated tau‐181 (p‐tau181) and glial fibrillary acidic protein (GFAP) (n = 358).

Result

SPARE‐AD scores were elevated vs. controls in aMCI/aAD, naAD, vascular disease, FTLD, and naMCI (all p<0.003) but not in LBD or other diagnoses (p>0.1). NaAD patients had lower SPARE‐AD (p<0.02) but higher SPARE‐BAG scores (p<0.02) than aMCI/aAD patients. SPARE‐AD scores were positively associated with mean cortical tau PET uptake, amyloid PET positivity, and plasma p‐tau181 and GFAP (all p<0.001). In contrast, SPARE‐BAG scores were not associated with PET or plasma biomarkers (all p>0.05).

Conclusion

SPARE‐AD values for naAD syndromes were intermediate between those of controls and aMCI/AD patients, likely reflecting divergent, partially overlapping cortical atrophy relative to aAD. PET and plasma biomarkers of AD neuropathologic change were associated with SPARE‐AD but not with SPARE‐BAG scores, suggesting SPARE‐BAG reflects age‐related atrophy that is largely independent of AD.
Correlations between [18F]flutemetamol PET and region‐matched postmortem integrated density measures of cyano‐flutemetamol signal in Aβ plaques
Authors: Abrahamson Eric E , Buckley Christopher , Pemberton Hugh , Farrar Gill , Smith Adrian , Ikonomovic Milos D
Published: December 2023

Background

The binding substrates of [18F]flutemetamol and [11C]PiB PET consist of fibrillar amyloid‐ß (Aß) aggregates in morphologically and structurally distinct diffuse plaques (DP) and cored plaques (CP) which are present at different proportions across brain regions in Alzheimer’s disease (AD). To account for this heterogeneity, an unbiased quantitative measure integrating plaque size and density of amyloid‐ß (Aß) fibrils in plaques could help avoid false positive results, improve imaging‐to‐autopsy correlations, and further advance our understanding of pathological substrates for binding of amyloid PET tracers.

Method

Sixteen subjects underwent [18F]flutemetamol PET imaging in the pivotal Phase III end‐of‐life study (Study GE067‐007 and GE067‐026) and later came to autopsy (mean imaging‐to‐autopsy interval was 111 ± 87.6 days). [18F]flutemetamol SUVRpons values in four neocortical regions were correlated with region‐matched postmortem measures of cyano‐flutemetamol labeling of all plaques, as well as CP and DP separately, using percent area coverage, mean grayscale intensity of fluorescence, or a combination of the two measures referred to as integrated density.

Result

In the analysis of all cyano‐flutemetamol‐labeled plaques, [18F]flutemetamol SUVRpons values were more closely associated with integrated density measures than percent area coverage and mean grayscale values. Similarly, when CP and DP were analyzed separately, the integrated density values showed the closest association with neocortical region‐matched [18F]flutemetamol SUVRpons values. When area coverage of CP and DP were each expressed as a fraction of total plaque area coverage with or without integrating fluorescence intensity values, [18F]flutemetamol SUVRpons values within each region of interest were associated with the DP, but not the CP, area coverage measure.

Conclusion

The association of antemortem [18F]flutemetamol PET and region‐matched postmortem integrated density measurements of cyano‐flutemetamol labeled plaques further supports the hypothesis that amyloid PET signal is influenced both by plaque size and Aß fibril density within DP and CP. Further elucidating the relative contributions of each plaque type to the retention of amyloid PET radioligands could influence how a positive amyloid PET signal is interpreted in relation to postmortem pathology data.
Quantifying associations of four major proteinopathies with grey matter atrophy: an imaging‐pathology study
Authors: Phillips Jeffrey S , Robinson John L. , Cousins Katheryn A Q , Das Sandhitsu R. , Yushkevich Paul A. , Wolk David A. , Lee Eddie B , McMillan Corey T , Trojanowski John Q , Grossman Murray , Irwin David J.
Published: December 2023

Background

Gross atrophy observed on MRI provides a clinically useful marker of possible neurodegenerative disease. However, autopsy studies of polypathology suggest atrophy is likely driven not by a single proteinopathy but also co‐pathologies. We hypothesized that in a clinically heterogeneous autopsy sample, amyloid‐ß, tau, a‐synuclein, and TDP‐43, would co‐occur within regions, and that co‐pathologies would have independent associations with grey matter atrophy.

Method

T1‐weighted antemortem MRI was available in 121 patients with postmortem ordinal pathology ratings (0 = none; 1 = mild; 2 = intermediate; 3 = severe). Primary neuropathologic diagnoses included Alzheimer’s disease (AD; n = 52), amyotrophic lateral sclerosis (n = 2), frontotemporal lobar degeneration due to tau (n = 29) and TDP‐43 (n = 22), and Lewy body disease (16). Regional volumes were expressed as W‐scores adjusting for age, sex, and intracranial volume for 10 regions spanning the limbic system, neocortex, and subcortex. We used mixed effects models with a random intercept per patient to regress W‐scores on ordinal pathology ratings.

Result

Amyloid‐ß and tau co‐occurred in all regions, reflecting the prevalence of AD neuropathologic change (Fig. 2, top). Alpha‐synuclein and TDP‐43 pathology were highest in amygdala, anterior cingulate, entorhinal cortex, and hippocampus, where they frequently co‐occurred with amyloid‐ß and tau. Neocortical regions including middle frontal, angular, and superior/middle temporal cortex had intermediate rates of co‐pathology, while thalamus, striatum, and globus pallidus had the lowest polypathologic burden (Fig. 2, bottom). Ordinal measures of tau [F(3,1073) = 24.1, p<0.001], TDP‐43 [F(3,1073) = 13.7, p<0.001], and ‐synuclein [F(3,1073) = 4.3, p<0.005] burden were inversely associated with regional volumes, but amyloid‐ [F(3,1073) = 1.8, p>0.15] was not. An increase in ordinal tau scoring by one unit was associated with a mean reduction of ‐0.29 in regional W‐score; for TDP‐43, a decrease of ‐0.51; and for a‐synuclein, a decrease of ‐0.16.

Conclusion

Mixed proteinopathies were common at the regional level in limbic and neocortical structures. Using blinded ordinal pathology scoring, TDP‐43 was associated with greater atrophy than tau; a‐synuclein had a smaller but significant association. Amyloid‐ß was not associated with atrophy when adjusting for tau. Results suggest co‐pathologies have a measurable effect on observed brain atrophy.
A multi‐site study of Alzheimer’s disease neuroimaging and cognitive biomarkers in 2819 cognitively normal individuals
Authors: Xie Long , Das Sandhitsu R. , Wisse Laura EM , Lyu Xueying , McGrew Emily , de Flores Robin , Gibson Eli , Yushkevich Paul A. , Wolk David A.
Published: December 2023

Background

Developing effective Alzheimer’s disease (AD) biomarkers in cognitively normal (CN) individuals is crucial. Prior studies have identified neuroimaging and cognitive measures that are sensitive to preclinical AD. However, the generalizability of these biomarkers in large, multi‐site cohorts and their power to predict disease progression remain unclear. Structural MRI, tau PET and standardized cognitive tests of 2819 CN adults were pooled from three studies to investigate the power of these measures in discriminating ß‐amyloid positivity (A+/‐) and predicting disease progression.

Method

T1‐weighted MRI and cognitive data of 2819 CN (A‐/A+: 1180/1540, Table 2) individuals from ADNI, HABS and A4 were included. Baseline medial temporal lobe structural measures were extracted from MRI (complete list in Table 1). For participants with prospective longitudinal MRI or cognitive measures (4.5 years), annualized change rate of each measurement was estimated. ANCOVA and receiver operating characteristic analyses were used to test biomarker differences between A+/A‐. In 563 CN with cross‐sectional tau PET available, stepwise linear mixed effect modeling was performed to identify the subset of baseline cross‐sectional biomarkers (tau, MRI and cognition) that yields the optimal model (smallest Akaike information criterion) in predicting longitudinal atrophy and cognitive decline. The area under the curve (AUC) of each model in discriminating the first (fast) and last (slow progressors) tertiles of each longitudinal measurement was reported.

Result

Significant differences between A+/A‐ (Table 2) were observed in cross‐sectional tau (most significant), cross‐sectional and longitudinal cognitive, as well as longitudinal structural MRI measures. When predicting disease progression with baseline measures (Figure 1‐a), tau (selected in all the models) and cognitive biomarkers were included in the most predictive models while MRI biomarkers did not provide additional information. The selected biomarkers can identify fast versus slow progressors with AUCs ranging from 0.63‐0.78 (Figure 1‐b).

Conclusion

The results demonstrated that both cross‐sectional (tau PET and cognition) and longitudinal biomarkers (MRI and cognition) are sensitive to amyloid status in CN. In addition, baseline tau PET and cognitive measures provide complementary information in predicting disease progression regardless of amyloid status. This indicates that these biomarkers may have important utility in preclinical AD clinical trials and normal aging studies.