bluuebunny/crossref_metadata_2025 huggingface dataset:
Associations Between Choroid Plexus Integrity and Cognitive Decline in Aging: Insights from Advanced MRI Analysis
Authors: Gong Zhaoyuan , Bilgel Murat , Faulkner Mary E , Bae Jonghyun , Laporte John P , Guo Alex , Resnick Susan M. , Egan Josephine M. , Bouhrara Mustapha
Published: January 2025

Background

The choroid plexus (CP), a vital component in the brain’s ventricles, is crucial for cerebrospinal fluid (CSF) production and maintenance of the brain’s physiological environment. It plays a key role in regulating neuroinflammatory responses, clearing harmful substances, producing neurotrophic factors and signaling molecules, and forming blood‐CSF barrier. Consequently, changes to the CP’s structural integrity could disrupt brain homeostasis and lead to cognitive impairment. Indeed, recent research has highlighted CP alterations in aging as well as in various cognitive disorders including Alzheimer’s and Parkinson’s diseases. This study investigates the correlation between the macrostructural and microstructural integrity of the CP and longitudinal cognitive changes in cognitively unimpaired individuals.

Method

116 cognitively unimpaired participants from the BLSA and GESTALT underwent advanced MRI, including relaxometry (T1 and T2) and diffusion tensor imaging (DTI), enabling the quantification of CP volume, fractional anisotropy (FA), and mean diffusivity (MD). Participants received cognitive assessments at visits preceding and concurrent with MRI scans (320 visits total) to measure memory, attention, executive function, verbal fluency, and processing speed (Table 1). Linear mixed‐effects models were used to analyze the association between MRI metrics and longitudinal cognitive changes, adjusting for age, sex, education, and race.

Result

Our study found that larger CP volume, elevated T1 and T2 values, and higher MD values, all indicative of compromised macrostructural or microstructural integrity, were associated with faster declines in various cognitive domains (Table 2). Particularly, the association was found in memory, verbal fluency, and processing speed for CP volume; in attention, executive function, and processing speed for T1 and T2 (Figure 1); and in attention, executive function, and processing speed for MD. Conversely, lower FA values, representing deteriorated microstructural integrity, correlated with accelerated decline in memory, attention, verbal fluency, and processing speed.

Conclusion

This study highlights a significant association between CP characteristics and cognitive decline in cognitively unimpaired individuals. These findings underscore the importance of the CP in cognitive health and emphasize the need for further research into the role of the CP in healthy aging, potentially opening new pathways for early detection and intervention in cognitive decline.
Non‐invasive quantification of [18F]‐PI‐2620 binding to tau deposits in the brain using an image‐derived input function
Authors: Bhattarai Anjan , Holy Emily Nicole , Wang Yiran , Spencer Benjamin A. , Wang Guobao , DeCarli Charles S. , Fan Audrey P.
Published: January 2025

Background

This study quantified tau binding in the brain with 18F‐PI2620 PET using a non‐invasive Image‐Derived Input function(IDIF), derived using a new total‐body EXPLORER PET/CT scanner (Spencer et al.,2021). Additionally, we explored how PET scan duration influences the quantification of kinetic parameters across brain regions of interest(ROIs) that are vulnerable in Alzheimer’s Disease.

Method

The study cohort included 15 individuals(10 cognitively unimpaired, 3 mild cognitive impairment, and 2 AD; ages = 68‐92 years; all tau negative) from the UC Davis ADRC. Dynamic total‐body 18F‐PI‐2620 PET images were acquired over 90 minutes using the uEXPLORER (resolution = 2.344 mm isotropic voxels, framing protocol:30×2s,12×10s,7×60s,16×300s). Brain cropped PET images were motion corrected (Jenkinson et al.,2002), and linearly registered to individual T1‐weighted(T1W) MRIs (Jenkinson & Smith, 2001). Grey matter ROIs, including the medial temporal(MT), posterior cingulate(PC), and lateral parietal(LP) cortices, were obtained parcellating T1W images(Desikan et al.,2006). Dynamic time activity curves for each brain ROI were fitted to a reversible two‐tissue compartmental model(2TCM), accounting for delay, using a subject‐specific IDIF(plasma and metabolite‐corrected) derived from the descending aorta of the same images (Figure 1). ROI‐specific micro and macro kinetic parameters were estimated. Logan graphical analysis (Logan,2000) was also used to estimate total distribution volume(VT).

Result

2TCM with IDIF demonstrated high‐quality fits of 18F‐PI2620 binding across grey matter ROIs(Figure1). Perfusion (K1) was observed to be reduced in MT compared to PC and LP(Figure2A). All kinetic parameters remained relatively stable after the 60‐minute scan window across all ROIs. Notably, K1 showed stability after 30 minutes of scan duration across all ROIs(Figure2 and 3). A strong correlation was observed between VT estimated using 2TCM and Logan plot analysis, across all ROIs LP(r = 1.00,p<0.001), MT(r = 0.96,p<0.001), PC(r = 1.00,p<0.001). Additionally, significant negative correlation was observed between binding potential and perfusion across all ROIs (r = ‐0.40,p = 0.007).

Conclusion

This study highlights the utility of a non‐invasive descending aorta IDIF derived using a total‐body EXPLORER PET/CT scanner to quantify 18F‐PI‐2620 grey matter kinetics. Preliminary findings suggest that a 60‐minute scan window may be sufficient for reliable quantification of kinetic parameters, while a 30‐minute scan time may suffice for perfusion alone. These findings warrant validation in a cohort involving tau positive individuals.
Multimodal neuroimaging and plasma biomarker evidence of white matter macrostructure loss in Parkinson's dementia
Authors: Zarkali Angeliki , Hannaway Naomi , McColgan Peter , Heslegrave Amanda J , Veleva Elena , Laban Rhiannon , Zetterberg Henrik , Lees Andrew , Fox Nick C , Weil Rimona S
Published: January 2025

Background

Parkinson’s (PD) is common and debilitating with over half of patients progressing to postural instability, dementia or death within 10 years. However, onset and rate of progression is highly variable, reflecting heterogeneity in underlying pathology, and biomarker studies to‐date have been limited to a single modality or assessed patients with established cognitive impairment.

Method

We assessed multimodal neuroimaging and plasma biomarkers in 98 PD patients (mean disease duration at baseline 4.33 years) and 28 age‐matched controls followed‐up over 3 years. Of PD patients, 31 (31.6%) had a poor outcome (PD poor outcomes), defined as mild cognitive impairment, dementia, frailty, or death during follow‐up. We compared biomarkers of gray matter (cortical thickness), white matter macrostructure (fibre cross‐section) and microstructure (fibre density) at whole‐brain and tract level, structural and functional connectivity, and plasma levels of neurofilament light chain (NFL) and phosphorylated tau 181 (p‐tau) between PD who progress to poor outcomes versus those with good outcomes.

Result

We found extensive white matter macrostructural changes in PD who progress to poor outcomes already at baseline: with 19% reduction in fibre cross‐section and a subnetwork of reduced structural connectivity (105 nodes, 215 edges, p=0.017), particularly involving interhemispheric connections. Gray matter and functional connectivity were preserved. NFL but not p‐tau was increased in PD poor outcomes and correlated with white matter loss.

Conclusion

PD patients who progress to poor outcomes, show white matter macrostructural loss already at baseline, evident both from imaging and fluid biomarkers. Our findings highlight white matter imaging and plasma NFL as potential biomarkers of poor outcomes in Parkinson’s, informing the design of future clinical trials.
Quantitative Analysis of Choroid Plexus Enlargement in Alzheimer’s Dementia: A Study of Automated Volumetric Technique
Authors: Kim Dong‐Hee , Suh Chong Hyun , Jung Wooseok , Lee Seung Hyun , Kim Jinyoung , Cho Hyeonwoo , Lee Yeha , Kim Sang Joon , Moon Won‐Jin
Published: January 2025

Background

Choroid plexus enlargement is implicated in the exacerbation of cognitive impairments characteristic of Alzheimer’s dementia (AD). Manual volumetric assessment by radiologists, while accurate, is impractical for large‐scale application due to its resource‐intensive nature. We examine the use of automated brain volumetry software as an efficient and cost‐effective alternative for quantifying choroid plexus volume.

Method

We collected 3D T1 brain MRI images from 293 patients aged between 44 and 91, with a median age of 73, at Konkuk University Hospital (n = 95), Asan Medical Center (n = 99), and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (n = 99). The study comprised 76 normal control (NC), 89 mild cognitive impairment (MCI), and 128 AD cases, with a female majority of 58.4%. Using VUNO‐Med DeepBrain software, we obtained choroid plexus segmentation masks and volumes from both radiologists and neural networks trained with deep learning. All choroid plexus volumes were normalized by intracranial volume (ICV) multiplied by 1000. Additionally, to assess DeepBrain’s accuracy, we calculated the Intraclass Correlation Coefficient (ICC(2, k)) between the manually labeled volumes and those labeled by DeepBrain.

Result

The median choroid plexus volumes measured by radiologists were 1.328 for NC, 1.354 for MCI, and 1.495 for AD. In contrast, measurements by DeepBrain were 1.163 (NC), 1.284 (MCI), and 1.428 (AD). A one‐way ANOVA analysis (NC vs. MCI vs. AD) revealed that DeepBrain‐based measurements (p < 0.001) may be more significant than manual measurements (p = 0.17) in elucidating the relationship between choroid plexus enlargement and cognitive impairments in AD. Additionally, the Intraclass Correlation Coefficient (ICC(2, k)) between manual and DeepBrain volumes indicated a moderate correlation with a score of 0.69 (p < 0.001).

Conclusion

Our results suggest that automated brain volumetry is a reliable method for assessing choroid plexus volume, correlating with the cognitive impairment continuum in AD. Its implementation could significantly streamline the diagnostic process, offering a scalable and objective approach for clinicians and researchers.
Longitudinal interplay between cerebral glucose metabolism, subclinical atherosclerosis and cardiovascular risk factors in midlife: the PESA study
Authors: Tristão‐Pereira Catarina , Fuster Valentin , Garcia‐Lunar Ines , Schöll Michael , Suarez‐Calvet Marc , Moro Maria Angeles , Garcia‐Alvarez Ana , Sanchez‐Gonzalez Javier , Zetterberg Henrik , Blennow Kaj , Ibañez Borja , Gispert Juan Domingo , Cortes‐Canteli Marta
Published: January 2025

Background

Cardiovascular disease and dementia often co‐exist at advanced stages. Yet, midlife longitudinal studies examining the interplay between atherosclerosis and its risk factors on brain health are scarce. We aimed to determine the longitudinal associations between cerebral glucose metabolism, subclinical atherosclerosis and cardiovascular risk factors in middle‐aged asymptomatic individuals.

Method

The Progression of Early Subclinical Atherosclerosis (PESA) is a longitudinal observational cohort study of 4184 asymptomatic individuals aged 40‐54. Participants with subclinical atherosclerosis underwent longitudinal cerebral [18F]fluorodeoxyglucose (FDG)‐PET (outcomes). Cardiovascular risk was quantified with SCORE2 and subclinical atherosclerosis with 3D vascular ultrasound (exposures). Multivariate regression and linear mixed effects models were used to assess outcome‐exposure associations through region‐of‐interest and voxelwise approaches. Additionally, blood‐based biomarkers of neuropathology were quantified and mediation analyses performed.

Result

This longitudinal study included 370 participants (median age: 49·8 [IQR=46·1‐52·2] years; 84% men; follow‐up: 4·7 [4·2‐5·2] years). Persistent high‐risk of cardiovascular disease was associated with an accelerated decline of cortical FDG uptake compared to low‐risk (ß=‐0·008 [95% CI ‐0·013 to ‐0·002]; pFDR=0·040), with plasma neurofilament light chain, a marker of neurodegeneration, mediating this association by 20% (ß=0·198 [0·008 to 0·740]; pFDR=0·050) (Figure 1). Moreover, progression of subclinical carotid atherosclerosis was associated with an additional decline in FDG uptake in Alzheimer’s disease brain regions, not explained by cardiovascular risk (ß=‐0·269 [95% CI ‐0·509 to ‐0·027]; p=0·029) (Figure 2).

Conclusion

Middle‐aged asymptomatic individuals with sustained cardiovascular risk and subclinical carotid atherosclerosis already present brain metabolic decline, suggesting that maintaining cardiovascular health during midlife may be key to reducing neurodegenerative disease burden later in life.
Subject‐level Detection of Focal Neurodegeneration Using Spatiotemporal Connectomics: Towards Atrophy Characterization in Preclinical Alzheimer's Disease
Authors: Sánchez Cristina , Diez Ibai , Bueichekú Elisenda , Kim Chan‐Mi , Grothe Michel J. , Sanchez‐Juan Pascual , Sepulcre Jorge
Published: January 2025

Background

Brain atrophy is a normal part of healthy aging, but it is aggravated by several neurodegenerative diseases. Previous studies have described a large heterogeneity in individual neurodegeneration patterns, but the underlying brain mechanisms are currently not fully understood. From a graph theory‐based framework, the estimation of subject‐specific focal or multifocal brain atrophy in healthy aging and in the preclinical stage of different neurodegenerative diseases, such as Alzheimer's disease (AD), will help to better understand individual atrophy networks and likely improve prediction of phenotypic heterogeneity in disease trajectories. This study aimed to develop a novel spatiotemporal connectomic method based on graph theory applied to serial MRI measurements to identify neurodegeneration focality (i.e., unifocal or multifocal atrophy patterns) in healthy aging at the single‐subject level.

Method

The study included a unique sample of 79 older cognitively normal participants from the the Vallecas project who underwent longitudinal T1 MRI scanning with 8 follow‐up timepoints over 9,46±1,97 years. Voxel‐based morphometry was used to define the brain atrophy topology of each subject, and uni‐ or multifocal atrophy patterns were identified using a graph theory approach based on structural similarity between each voxel and the rest of the brain across serial gray matter measurements (Figure 1).

Result

We identified individualized atrophy phenotypes characterized by different graph morphologies (Figure 2), which could be classified into three main groups based on their connectivity behavior. One group of subjects was characterized by atrophic voxels with a coordinated behavior, another with a predominance towards divergent or discoordinated behavior, and a third group that laid between these two extremes.

Conclusion

We present a novel analytical tool for characterizing individualized atrophy phenotypes in healthy subjects based on graph theory and structural similarity analyses of longitudinal MRI data. This method may help to describe the first structural events in preclinical AD and other neurodegenerative diseases and, therefore, could be crucial for predicting differences in disease phenotype and progression in single subjects.
Cerebrovascular reactivity (CVR) MRI as a biomarker for cerebral small vessel disease (SVD) related cognitive decline: Multi‐site validation in the MarkVCID Consortium
Authors: Liu Peiying , Lin Zixuan , Hazel Kaisha , Pottanat George , Xu Cuimei , Jiang Dengrong , Pillai Jay J , Lucke Emma , Bauer Christopher E. , Gold Brian T , Greenberg Steven M. , Helmer Karl G , Jann Kay , Jicha Gregory A , Kramer Joel H. , Maillard Pauline , Mulavelil Rachel M. , Satizabal Claudia L , Schwab Kristin , Seshadri Sudha , Singh Herpreet , Velarde Angel G , Wang Danny JJ , Kalyani Rita , Moghekar Abhay , Rosenberg Paul B. , Yasar Sevil , Albert Marilyn S. , Lu Hanzhang
Published: January 2025

Background

Cerebral small vessel disease (SVD) related vascular contributions represent a major factor contributing to cognitive decline and dementia (VCID) in older adults. However, there has not been a validated biomarker for the diagnosis and treatment monitoring of this condition. Recently, the US National Institute on Neurological Disorders and Stroke (NINDS) funded the MarkVCID Consortium to identify and validate clinical‐trial‐ready biomarkers for VCID. Cerebrovascular reactivity (CVR) MRI is one of the selected biomarkers that underwent multi‐site testing in the Consortium. The present study aimed to report the relationship between CVR and cognitive function at independent sites, based on a pre‐specified hypothesis.

Method

CVR, the ability of cerebral small vessels to dilate upon stimulus, is thought to directly reflect physiological function of the brain microvasculature. Based on previous single‐site findings, the pre‐defined hypothesis was that CVR will be associated with the global cognitive function measured by Montreal Cognitive Assessment (MoCA) after adjusting for age, sex, and education, and this association will be observed in data collected and analyzed at each individual site. A total of 264 older participants from three sites were included (Table 1). Each site performed an identical CVR MRI procedure using 5% CO2 inhalation, and a standardized clinical and cognitive evaluation. Multi‐linear regression analysis was conducted on a site‐by‐site basis to examine the pre‐defined hypothesis.

Result

Gray‐matter CVR showed a positive association with MoCA score after adjustment for age, sex, and education, in which participants with higher CVR had higher MoCA scores. This relationship was reproduced at each site (Fig.1, p<0.05 for each), confirming our pre‐specified hypothesis. In the secondary analysis of all data together, higher gray‐matter CVR was found to be significantly associated with better executive function measure of item response theory (IRT) score (ß = 2.87, p = 0.003).

Conclusion

The present study evaluated the relationship between CVR and cognition in a multi‐center setting. CVR was found to be positively associated with global cognitive function measured by the MoCA, which was shown to be reproducible across different sites with diverse cohorts. These findings support the utility of CVR as a biomarker in future clinical trials of SVD and VCID.
Differences in amyloid positivity rates among racial groups with cognitive impairment in a suburban‐rural Southeast community
Authors: Chacon Eduardo Garcia , Woodring Annalise C , Crane Monica K
Published: January 2025

Background

Underrepresented racial and ethnic groups have higher rates of clinical dementia symptoms and are given clinical diagnoses of Alzheimer’s disease without confirmatory AD biomarkers.

Method

We compared amyloid PET positivity in cohort of all rural and suburban Southeastern participants from a single clinical practice who met appropriate‐use criteria for amyloid PET imaging between January 2020‐December 2024. We used a paired nominal date test McNemar test to compare amyloid PET positivity proportions between matched racial and ethnic groups and multivariable logistic regression to assess the odds of having a positive amyloid PET scan.

Result

Data from 94 individuals (6 Asian/Pacific Islander(Other), 42 Black, 7 Hispanic, and 39 White) with MCI or dementia and amyloid PET were analyzed between April 2020 and December 2023. The median (range) age of participants was 75 (68‐82) years; 51 participants (54.3%) were female and 43 (45.7%) were male. For patient amyloid status, 49 participants (52.1%) had a validated negative amyloid result, and 45 participants (47.9%) had a validated positive amyloid result. In the optimal 1:1 matching analysis (n = 81, White participants had a greater proportion of positive amyloid PET scans analyzed but did not achieve statistical significance when compared with Black participants (24 of 39; 61.5%; 95% CI, 0.38‐0.72 vs 14 of 42; 33.3%; 95% CI, 0.19‐0.51, respectively) p>0.05. In the adjusted model, the odds of having a positive amyloid PET scan were lower for Black participants (OR, 0.313; 95% CI, 0.126‐0.776; P = 0.012), and Hispanic participants (OR, 0.33; 95% CI, 0.163‐4.253; P>0.05) compared with White participants.

Conclusion

The proportion of amyloid positive PET scan was greater among White as compared with Black and Hispanic participants when controlling for social and demographic factors. These findings may reflect differences in underlying pathology and raises concern that other factors may be contributing to higher levels of cognitive impairment in underrepresented groups.
Impact of AI‐based segmentation on PET analyses
Authors: Bracoud Luc , Cajgfinger Thomas , Rousset Olivier , Ingalhalikar Madhura , Conklin Chris , Lehmann Manja , Schaerer Joel , Scott David , Suhy Joyce
Published: January 2025

Background

Brain MRI segmentation is required for quantitative PET analysis, in order to derive regional uptake and calculate uptake ratio relative to reference regions. FreeSurfer has been a popular method but is being supplanted by faster and more robust AI‐driven methods. The objective of this work is to confirm that the use of Clario’s novel AI segmentation method, whose impact was assessed towards various MRI endpoints, is also valid in the context of PET quantification.

Method

507 subjects from ADNI were selected, including normal controls, subjective memory complainers, early/late MCI and AD subjects. Besides, 210 were selected with available test/re‐test data. For each, a pair of good quality 3DT1 MRI and Amyloid PET scans were available. 3DT1 data were segmented with both FreeSurfer v6 (FS) and Clario’s AI method (AI), and registered to PET space for calculation of Standard Uptake Value (SUV) in a set of cortical regions (frontal, posterior cingulate, lateral parietal and lateral temporal) and reference regions (cerebellar grey and whole cerebellum). SUVR (ratio to reference region) was calculated for both. Results were also converted to Centiloid (CL) units. SUV and SUVR values were compared across segmentation methods via Bland‐Altmann plots and correlated with Pearson’s coefficient. The ability to distinguish between disease severity stages was assessed by ROC analysis using global AUC. Finally, classification as amyloid (Aβ) positive or negative was assessed by setting a cut‐off of 20.1 CL and looking at Cohen’s Kappa.

Results

SUV and SUVR values were highly and significantly correlated between FS and AI methods (r>0.99, p<0.001) and for test/re‐test, for all regions investigated, with a difference that did not exceed 0.41% on average (SD<1.38%). Global AUC was comparable for both methods and for test/retest (average gAUC = 0.62). Aβ classification was near‐perfect across methods (κ = 0.98) and between test/retest data (κFS = 0.97, κAI = 0.99).

Conclusion

Comparing FreeSurfer and Clario’s AI‐based MRI segmentation method, no impact was found on subsequent PET analyses and test/retest performance was equivalent. These results support the use of either method for PET quantification. For future trials, the AI method could either be used as the primary method, or as a back‐up when traditional FS segmentation fails.
White matter hyperintensity onset, trajectories, and associations with cognitive decline in the presence of amyloid and tau
Authors: Du Lianlian , Langhough Rebecca E. , Hermann Bruce P , Betthauser Tobey J. , Planalp Elizabeth M. , Jonaitis Erin M. , Reyes Ramiro Eduardo Rea , Rivera‐Rivera Leonardo A. , Cody Karly Alex , Chin Nathaniel A. , Cadman Robert V. , Johnson Kevin M. , Field Aaron S , Rowley Howard A. , Pompa Christian C. , Hudson Sarah C. , Ryther Brenda , Sparks Lia J. , Miess Beryl , Norris Nia , Ramsey Celena M , Mueller Kimberly D , Asthana Sanjay , Eisenmenger Laura B. , Christian Bradley T. , Johnson Sterling C.
Published: January 2025

Background

Cognitive decline is often influenced by Alzheimer’s disease (AD) pathology (e.g., beta‐amyloid burden) and other pathology (e.g., vascular abnormalities). Amyloid onset and chronicity estimation using Sampled Iterative Local Approximation (SILA), enhanced our understanding of AD progression and its preclinical phase. This study has three aims: 1) estimate White Matter Hyperintensities (WMH) onset and chronicity; 2) assess whether baseline WMH chronicity/burden moderates the association between Aß chronicity/burden and Clinical Dementia Rating‐sum of boxes (CDR‐SB) trajectories; 3) explore whether tau burden mediates WMH and amyloid associations with CDR‐SB.

Method

Participants were from the University of Wisconsin WRAP and ADRC cohorts and had completed at least one T1‐weighted and T2‐weighted FLAIR scans (Aim 1: n = 877, age 43‐93y). WMH values were aligned to a duration scale using SILA and WMH positivity threshold of ∼2.06 mL for WMH+ chronicity = 0. We compared mixed effects models with up to cubic time (age vs WMH chronicity) terms for characterizing WMH trajectories. We also examined baseline WMH burden*amyloid burden at each CDR‐SB assessment (PiB A+ DVR threshold ∼17CL; linear and quadratic amyloid burden) relative to longitudinal CDR‐SB (Aim 2; n = 426), and tau PET SUVR’s mediating effects on WMH*amyloid associations with last CDR‐SB (Aim 3; n = 385; meta‐temporal (MTC) SUVR; florquinitau tracer).

Result

Mean(SD) age at baseline and last MRI were 65.36(8.49) and 67.26(8.14) years, respectively (sample details in Table 1). Comparisons of simple slopes (95%CI) show overlapping annualized WMH‐ slope estimates using age (0.028(0.022,0.034)) or chronicity (0.037(0.033,0.040)); in contrast, the WMH+ slopes are 2.26 times larger when aligned to WMH chronicity vs age (WMH+: 0.042(0.036,0.047), WMH‐: (0.095(0.091,0.10); Figure 1A&B). Whether biomarker “burden” was modeled as ±, estimated DVR, or chronicity (Figure 1C&D), significant interactions showed a synergistic effect of WMH and amyloid on accelerated CDR‐SB trajectory. Moderated mediation models revealed MTC‐tau accumulation partially mediated (∼65%) the synergistic effect of WMH and amyloid on last CDR‐SB (Figure 2).

Conclusion

WMH accumulation follows a predictable trajectory post‐onset and appears to exacerbate cognitive decline in those with amyloid pathology. Future analyses will further elucidate the complex relationships between vascular risk, amyloid, tau accumulation and cognitive decline.
Comparison of MRI T2 FLAIR White Matter Hyperintensity Segmentation Algorithms in Clinical Trials
Authors: Scheel Norman , Hubert Josh , Baker Joshua H. , Fernandez Zachary , Yanev Pavel G. , Stowe Ann M , Vongpatanasin Wanpen , Zhang Rong , Zhu David C
Published: January 2025

Background

White Matter Hyperintensities (WMH) appear on T2‐weighted Fluid‐Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Imaging (MRI) and are an important biomarker of cerebral small vessel disease (CSVD), cognitive decline, and stroke. However, manual delineation is laborious and bias‐prone, while automated segmentation has proven challenging. With the recent conclusion of the MICCAI‐Society WMH segmentation challenge, and our large clinical trials, “Risk Reduction for Alzheimer’s Disease” (rrAD) and “Hypertension, Intracranial Pulsatility and Brain Amyloid‐beta Clearance in older adults” (HIPAC), we investigated the differences in the total WMH volume segmented by various algorithms to ensure the extraction of accurate and meaningful image‐derived phenotypes.

Methods

The rrAD trial provides 512 2D axial T2 FLAIR scans, fat saturation off (ages 60‐85). The HIPAC study provides 84 3D T2 FLAIR scans, fat saturation on (ages 55‐79). The MICCAI WMH challenge provides a test set of 110 scans of 2D axial T2 FLAIR images, 30 without, and 80 with fat saturation. Our clinical trials and the MICCAI datasets comprise data from over 700 subjects, across 10 scanners and diverse sequences. Three of the best‐performing MICCAI algorithms were selected: PGS, Sysu‐Media‐2, FMRIB‐TrUE‐Net2, as well as the LPA algorithm from SPM. Segmentation results were randomized, and fully blinded expert raters scored a subset of 120 scans.

Results

Figure 1 depicts the average normalized images for each T2 FLAIR contrast. The MICCAI test set shows a median WMH burden of 10‐17 ml, while rrAD subjects presented with relative medians of ˜3‐4 ml, and HIPAC subjects with ˜2‐3 ml. Figure 2 shows the WMH volume for each segmentation algorithm and dataset. For HIPAC Sysu‐Media‐2 had high false pickup within grey matter regions, while LPA produced high false pickup at the posterior septum pellucidum. PGS scored best in manual ratings.

Conclusions

MRI sequences that use fat saturation change the T2 FLAIR image contrast substantially and impact segmentation performance, we observed better performance with fat saturation off. The MICCAI challenge algorithms outperformed classical methods (PGS leading), detecting small lesions, away from the ventricles. As WMH distribution, shape, and longitudinal tracking are likely more sensitive biomarkers than volume alone, further analysis is warranted.
Immunoassay and Immunohistochemistry of TDP‐43 and the association with annual rate of hippocampal atrophy in Alzheimer's disease
Authors: Youssef Hossam , Gatto Rodolfo G. , Pham Nha Trang Thu , Petersen Ronald C. , Dickson Dennis W. , Petrucelli Leonard , Whitwell Jennifer L. , Prudencio Mercedes , Josephs Keith A.
Published: January 2025

Background

Transactive response DNA‐binding protein of 43 kDa (TDP‐43) is implicated in numerous neurodegenerative diseases, including Alzheimer’s disease (AD). Immunohistochemically stained TDP‐43 is linked to faster rates of hippocampal atrophy (HA) in AD. However, it is unclear whether phosphorylated TDP‐43 (pTDP‐43) measured using an immunoassay is also associated with HA. We explored associations between pTDP‐43 levels, TDP‐43 immunohistochemistry, and annual rate of HA in AD. We hypothesized that higher pTDP‐43 levels would be associated with positive TDP‐43 immunohistochemistry, and faster rates of HA.

Method

Thirty‐seven cognitively impaired participants from the Mayo Clinic Alzheimer’s Disease Research Center underwent serial brain MRIs and brain autopsy. Hippocampal TDP‐43 was detected histochemically, and pTDP‐43 was quantified using biochemical assay. Hippocampal volumes were measured using the longitudinal pipeline in FreeSurfer‐7 and annualized HA rates were calculated. Linear regression analyzed the relationship between HA and pTDP‐43 biochemical assay levels. pTDP‐43 was categorized as positive (=400) or negative (<400), and logistic regression tested the association of these levels with HA rates. The correlation between TDP‐43 immunohistochemistry status and biochemical assay levels was evaluated using descriptive statistics. All analyses were adjusted for potential confounders.

Results

The mean age at death was 83.5 (±9.9) years with 49% females. Median scan interval was 3‐years. A negative relationship was observed between age at death and annual HA rate (ß=‐3.1; 95% CI [‐5.3,‐0.9]; p=0.007), and a positive relationship was observed between pTDP‐43 level and annual HA rate (ß=0.02; 95% CI [0.003,0.03]; p=0.015). A one‐unit increase in HA rate was associated with a 3% increase in the odds of being pTDP‐43 positive (=400) (odds ratio=1.03; CI [1.007,1.05]; p=0.014). Cases that tested positive for Immunohistochemistry TDP‐43 had significantly higher mean pTDP‐43 immunoassay levels (1508 ± 2072 vs. 202 ± 131; p=0.008). More cases with positive IHC TDP‐43 surpassed the pTDP‐43 immunoassay cut‐off level of 400 vs the negative participants (p=0.003).

Conclusion

Higher pTDP‐43 levels in the hippocampus are linked to faster HA in AD and correlated with immunohistochemistry TDP‐43 positivity. These findings underscore the role of TDP‐43 in AD neurodegeneration. The biological and clinical implications of these observations necessitate further exploration in subsequent studies.
PET imaging utility of a novel Aβ‐tracking PET radiotracer, [18F]FC119S in aged vervet monkeys
Authors: Bhoopal Bhuvanachandra , Frye Brett M. , Bansode Avinash , Miller Mack , Damuka Naresh , Gollepalli Krishna Kumar , Barcus Richard A. , Lockhart Samuel N. , Sutphen Courtney L. , Jorgensen Matthew J. , Craft Suzanne , Register Thomas C. , Whitlow Christopher T , Shively Carol A. , Sai Kiran K. Solingapuram
Published: January 2025

Background

Older vervet monkeys are an excellent model for studying age‐associated Aß deposition; however, they have high proportions of low‐affinity Aß sites compared to human brains. Commonly used Aß PET radiotracers are most useful in detecting high affinity Aß fibrils. Measuring real‐time levels of low affinity Aß fibrils through PET provides critical information of early AD progression. The radiotracer [18F]FC119S has high binding strength for Aß1‐42 protein aggregates (0.16 nM) and AD brain homogenates (13‐15 nM). A pilot clinical trial showed significantly higher hippocampal and cortical uptake in AD patients over cognitively normal participants. Here we report the fully‐automated [18F]FC119S radiochemistry and preliminary imaging and fluid biomarker correlation data in aged vervet monkeys.

Methods

Radiochemistry followed [18F]¯‐assisted nucleophilic substitution of mesityl precursor and deprotection of Boc group. [18F]FC119S(∼0.37GBq)‐based brain PET (0‐120min) and T1‐weighted whole‐brain MRI scans were conducted in aged vervets (19‐27 y, n = 14). CSF and plasma Aß40, Aß42, pTau181, and NfL were measured in samples taken close to the time of PET. Standard Uptake Values with cerebellum as reference (SUVr) and time‐activity‐curves (TACs) were calculated from PET/MR (Fig 1). SUVrs of anterior and posterior cingulate, hippocampus, frontal, parietal, temporal, and occipital lobes were correlated with age, MRI outcomes (grey and white matter volumes), and fluid biomarker data.

Results

[18F]FC119S production was highly reproducible (n>25 runs) in high (>97%) radiochemical purities, and molar activities (∼140 GBq/µmol). TACs showed favorable washout kinetics from all brain regions. SUVrs of hippocampus and cortical parietal lobe positively correlated with age and SUVrs of all the regions analyzed negatively correlated with MRI deep gray and white matter volumes. Among the high SUVr regions, cortical anterior cingulate SUVr was highly positively correlated (Fig 2) with CSF pTau181 (r = 0.78, **p = 0.002).

Conclusion

Preliminary [18F]FC119S PET evaluations agrees with human PET data in vervets with high uptake in regions associated with Aß deposition. Among all fluid biomarkers analyzed, CSF pTau181 was the best correlate of all the brain PET SUVrs. Association of Aß PET imaging data with synaptic density and microtubule data in the same cohort is being evaluated to explore the potential neurodegeneration pathways in aged vervet monkeys.
Perivascular Space Analysis: A Possible Tool for Predicting Cerebral Amyloid Angiopathy in Pathology‐Confirmed Cases
Authors: Fotouhi Maryam , Sheikh‐Bahaei Nasim , Choupan Jeiran
Published: January 2025

Background

Diagnosis of cerebral amyloid angiopathy (CAA) presents a significant challenge in determining whether to propose anti‐amyloid treatment plans. The identification of perivascular spaces (PVS) through MRI serves as a possible strategy to elucidate the physiopathological interconnections between the brain’s clearance mechanisms and the accumulation of amyloid. This study endeavors to the association between PVS morphology and CAA pathology.

Methods

T1‐weighted and T2‐FLAIR MRI data were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Demographic details (sex, age, post‐mortem interval) and ADNI pathologic scores were gathered. Histological images provided scores for cerebral amyloid angiopathy. Leveraging our on the last premortem MRI, we automatically mapped regional PVS in white matter and basal ganglia. analysis was then employed to investigate whether premortem regional PVS volume fractions serve as predictors for postmortem CAA pathology, accounting for age, sex, and post‐mortem interval.

Results

The investigation revealed notable predictive associations between specific occipital regions' PVS volume fractions and the presence of amyloid angiopathy pathology, after multiple comparison correction. Specifically, the study identified the right cuneus PVS volume fraction as a robust predictor for the manifestation of amyloid angiopathy pathology (t = 3.12, p = 0.001). Similarly, the left precuneus PVS volume fraction emerged as a statistically significant predictor (t = 2.78, p = 0.005).

Conclusion

This study presents a noteworthy advancement in amyloid angiopathy diagnosis, employing standard MRI analysis of perivascular spaces. The identified correlation offers a pragmatic means to enhance diagnostic accuracy without complexity. This research underscores the potential applicability of PVS analysis in routine clinical practice for early CAA detection, contributing significantly to the practical improvement of CAA diagnostics. Reference: 1. Sepehrband, F., Barisano, G., Sheikh‐Bahaei, N. et al. Image processing approaches to enhance perivascular space visibility and quantification using MRI. Sci Rep 9, 12351 (2019). https://doi.org/10.1038/s41598‐019‐48910‐x
Developing a novel brain‐based biomarker of mild cognitive impairment using time‐domain functional near‐infrared spectroscopy
Authors: Dubois Julien , Field Ryan M , Jawhar Sami , Koch Erin M , Aghajan Zahra M. , Miller Naomi , Perdue Katherine L , Taylor Moriah
Published: January 2025

Background

Mild cognitive impairment (MCI) is largely under‐diagnosed by primary care physicians. There is an urgent need to develop new objective screening tools to assist with early detection of MCI. Time‐domain functional near‐infrared spectroscopy (TD‐fNIRS) can be used to measure brain function in clinical settings and may fill this need.

Method

MCI patients (n=21) and control older adults (HC; n=24) participated in brain recordings using TD‐fNIRS during rest and cognitive tasks implicated in MCI: 1) Verbal fluency task (VFT) consisting of interleaved blocks reciting words (control: weekdays; semantic: words from a given category; phonological: words starting with a given letter); 2) N‐back task targeting working memory by testing memory for patterns with specific memory loads (0‐, 1‐ and 2‐backs) in a block‐design manner. Raw data, i.e. the distributions of the times of flight (DToFs) of photons at two wavelengths (690 and 905nm), underwent standard preprocessing to obtain moments of DToFs and corresponding changes in the concentrations of oxygenated/deoxygenated hemoglobin. Features related to brain function, systemic physiology, and head optical properties were extracted. For tasks, behavioral metrics were also computed.

Result

First, we looked for features that significantly differentiated between MCI and HC groups during a resting state session (watching a 7‐minute audiovisual segment; Figure 1A). Multiple features, including head optical properties and prefrontal fractional Amplitude of Low Frequency Fluctuations (fALFF) were statistically different between MCI and HC (Figure 1B). Next, we explored the tasks both in terms of behavior and neural features. In VFT, behavior was significantly different between groups (Fig. 2A), which is expected from prior literature. Additionally, whole‐brain hemodynamic activation maps, as computed using Generalized Linear Models (GLM) revealed areas with significant differences between the two groups (Fig. 2B). Similarly, for the N‐back task, multiple behavioral metrics were separated between the groups (Fig. 3A) and group‐level GLM showed brain regions with significantly different activations between groups, specifically medial prefrontal cortex (Fig. 3B).

Conclusion

We demonstrated significant group‐level differences between MCI vs healthy controls using TD‐fNIRS. As such, with ongoing data collection, we seek to validate these findings and employ classification techniques for MCI detection.
Diffusion Basis Spectrum Imaging in Midlife Obesity: Associations with Abdominal Adipose Tissue
Authors: Dolatshahi Mahsa , Commean Paul K. , Rahmani Farzaneh , Nguyen Caitlyn , Lloyd LaKisha , Kasani Sara Hosseinzadeh , Mittendorfer Bettina , Sirlin Claude , Song Sheng‐Kwei , Benzinger Tammie L.S. , Ippolito Joseph E. , Morris John C. , Raji Cyrus A.
Published: January 2025

Background

Obesity and abdominal adiposity in midlife are shown to increase the risk of Alzheimer disease. However, it is not clear whether midlife adiposity is associated with increased neuroinflammation. We aimed to investigate the associations of obesity, BMI of 30 kg/m2 or higher, and abdominal visceral and subcutaneous adipose tissue (VAT and SAT) with brain histology, using diffusion basis spectrum imaging (DBSI) analysis;

Method

In total, 54 cognitively normal middle‐aged subjects (50.46±6.19 years, male: 21 (38.9%), obesity: 32 (59.3%), BMI: 32.18±6.99 kg/m2) underwent brain and abdominal 3T MRI. Abdominal VAT and SAT were semi‐automatically segmented using VOXel Analysis Suite (Voxa). A DBSI scheme with a total of 98 diffusion samplings was acquired followed by movement and eddy current correction and brain tissue extraction in FSL. DBSI maps including fractional anisotropy (FA, overall integrity), axial diffusivity (AD, axonal injury), radial diffusivity (RD, myelin loss), restricted fraction (RF, inflammation cellularity), hindered fraction (HF, extracellular edema), and fiber fraction (FF, axonal density) were generated using in‐house software scripted in MATLAB. DBSI‐derived maps were processed using a tract‐based spatial statistics (TBSS) pipeline for whole‐brain white matter voxel‐wise analyses. Using the Randomize tool from FSL, the difference between obese vs. non‐obese, high‐VAT vs. low‐VAT, and high‐SAT vs. low‐SAT groups were investigated for each DBSI‐derived skeleton, with age and sex as covariates, and a threshold of 0.05 for false‐discovery rate. The sex differences were further investigated;

Result

Lower FF and AD and higher RF in widespread white matter areas were observed in the obese vs. non‐obese group, and in the high‐SAT vs. low‐SAT group. Lower AD and higher RF were observed for the high‐VAT vs. low‐VAT group. All of these differences were only significant in females, not males, but higher RF in obese vs. non‐obese was observed both in males and females;

Conclusion

Our data support lower axonal density and fiber integrity, as well as higher inflammation cellularity in cognitively normal, middle‐aged obese individuals, and those with high VAT and high SAT, especially in females. Overall, our data suggest the differential role of visceral and subcutaneous abdominal fat in promoting neuroinflammation and axonal damage.
Markers of Interstitial Fluid Dynamics from Diffusion MRI Reveal Association with Amyloid Deposition in Cognitively Normal Older Adults
Authors: Chen Chang‐Le , Jin Hecheng , Schweitzer Noah , Minhas Davneet S , Villemagne Victor L , Yang Shaolin , Aizenstein Howard J , Wu Minjie
Published: January 2025

Background

Glymphatic clearance dysfunction within the perivascular space has been implicated in Alzheimer’s Disease (AD) pathology. Diffusion MRI‐based techniques such as DTI‐ALPS can quantify perivascular interstitial fluid (ISF) dynamics, yet their links with other early AD markers in the cognitively normal elderly population remain underexplored. Here, we investigated associations between DTI‐ALPS and cerebral ß‐amyloid (Aß) burden measured with Pittsburgh Compound B (PiB)‐PET. We also evaluated an augmented version of DTI‐ALPS to enhance sensitivity and better reflect the ISF diffusivity potentially associated with glymphatic function.

Methods

Diffusion tensor images (DTI) and PiB‐PET images were collected from 40 cognitively normal older adults (age: 74.8 [5.8] years, sex: 18 males, mini‐mental state examination (MMSE): 28.8 [1.4], APOE‐e4%: 23%). Based on the DTI (acquired on a 3T MRI scanner with 12 diffusion directions, b‐value = 1000, and voxel size in 2 mm cubic), we estimated DTI‐ALPS index that evaluates the perivascular ISF movement along the medullary conduits and also developed an algorithm to generalize the definition of the traditional DTI‐ALPS by automatically localizing the periventricular space as the target area and calculating transverse tensor ratios as the primary measure (Figure 1). PiB‐PET analysis followed our previous validated approach, and the regional standardized uptake value ratios (SUVR) representing PiB retention relative to the cerebellar gray matter were averaged to determine global cerebral Aß burden. Linear regression analysis was applied to investigate the relationship between DTI‐ALPS and global PiB‐PET SUVR.

Results

The baseline model with the predictors of age, sex, MMSE and APOE4 status significantly explained the logarithmic global SUVR of PiB‐PET (Figure 2). When incorporating DTI‐ALPS indices, the baseline models were significantly improved (Likelihood‐ratio test: both p < 0.01); the explained variance increased by 15.3% and 19.3% by adding traditional and proposed augmented DTI‐ALPS indices, respectively. The models indicated that the DTI‐ALPS indices were significantly negatively associated with the global Aß burden after adjusting the covariates (Figure 2).

Conclusion

We observed that higher ISF diffusivity (likely better glymphatic clearance) corresponds to lower PiB‐PET retention (lower Aß burden) in the cognitively normal older adults, suggesting the potential utility of ISF measures as a putative AD biomarker.