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Eirini Messaritaki¹, Thomas M Lancaster^1,2, Katherine E Tansey³, and Derek K Jones^1
1Psychology, Cardiff University, Cardiff, United Kingdom, ²Psychology, University of Bath, Bath, United Kingdom, ³Cardiff University, Cardiff, United Kingdom

Keywords: Alzheimer's Disease, Alzheimer's Disease

This work explores the link between the topological properties of brain structural networks and APOE-epsilon4 in young asymptomatic adults. We investigated the sensorimotor, visual and default-mode networks. We found evidence that there are differences in the mean clustering coefficient of the sensorimotor network of carriers versus non-carriers, with the left caudal middle frontal, left precentral, right postcentral and right precentral gyri driving the differences. Interestingly, the mean clustering coefficient was higher in carriers compared to non-carriers. In contrast, no differences were found for the visual or the default-mode networks.

Sergio Adrian Becerra¹, Kaya Jordan¹, Jon Haroon¹, Kennedy Mahdavi¹, Sheldon Jordan^1,2, Rama Surya¹, and Elisabeth Rindner^1
1Synaptec Network, Santa Monica, CA, United States, ²Neurology, UCLA, Los Angeles, CA, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease

The nucleus basalis (NBM) is the major source of cholinergic innervation to the cerebral cortex, hippocampus and other subcortical structures. Focusing DTI and fMRI on the NBM can shed light on the potential state of subjects with Alzheimer’s disease. We aim to use DTI to provide insight into the white matter projections from the NBM and use fMRI to depict how it is functionally wired.

We found that imaging of the NBM differentiated dementia patients from controls, and captured the level of cognitive decline. While the results are preliminary, this analysis introduces a method of observing the progression of AD.

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Xiaochen Liu¹, David Hike¹, Wenchao Yang¹, Zeping Xie^1,2, Bei Zhang¹, Andy Liu^1,3, Sang Cheon Choi¹, Biyue Zhu¹, Chongzhao Ran¹, Yuanyuan Jiang¹, and Xin Yu^1
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, ²School of Traditional Medicine, Southern Medical University, Guangzhou, China, ³Department of Neuroscience, Boston University, Boston, MA, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, pupil dynamics

This study obtained visually stimulated high-resolution fMRI and real-time pupil dynamic signals in awake normal and AD mice. By analyzing the trial-specific pupillary responses to light (PRL), we identified unique temporal dynamic features in AD mice. By performing the pupil-fMRI event-related analysis, we detected specific subcortical functional nuclei in AD mice, showing strong correlations to the pupil dilation recovery features and the variability across different stimulation events. These results present novel function-behavioral linkage based on the pupillary responses to visual stimulation in AD mice, revealing an intriguing non-invasive and quantitative biomarker of the neurodegenerative progress of AD brains.    

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Alexandra Badea¹, Ali Mahzarnia², Jacques S Stout³, Robert J Anderson², Hae Sol Moon⁴, Zay Yar Han², Kate Beck⁵, Jeffrey N Browndyke⁶, David Dunson⁷, Kim G Johnson⁵, and Richard J O'Brien^8
1Radiology, Neurology, BIAC, Duke Univ Medical Center, Durham, NC, United States, ²Radiology, Duke Univ Medical Center, Durham, NC, United States, ³BIAC, Duke Univ Medical Center, Durham, NC, United States, ⁴BME, Duke Univ Medical Center, Durham, NC, United States, ⁵Neurology, Duke Univ Medical Center, Durham, NC, United States, ⁶Psychiatry and Behavioral Sciences Department, Duke Univ Medical Center, Durham, NC, United States, ⁷Statistical Sciences, Duke University, Durham, NC, United States, ⁸Neurology, Duke University Medical Center, Durham, NC, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, Aging

The brain connectome helds promise to detect subtle changes in individuals at risk for Alzheimer's disease.  We imaged using high resolution diffusion imaging 72 subjects enriched for the APOE4 genotype to reveal vulnerable networks associated with a composite AD risk factor including age, genotype, and sex. Sparse canonical correlation analysis (CCA) revealed a high weight associated with genotype, and subgraphs involving the cuneus, temporal, cingulate cortex, and cerebellum. Our results have identified structural brain networks and the associated weights for several risk factors for AD in preclinical stages.

Zhiwei Guo¹, Qiwen Mu¹, and Xiaoyong Zhang^2
1The Second Clinicall Medical College of North Sichuan Medical College, Nanchong, China, ²Clinical Science, Philips Healthcare, Chengdu, China

Keywords: Alzheimer's Disease, Alzheimer's Disease

Repetitive transcranial magnetic stimulation (rTMS) may lead to a significant improvement in general cognitive function and memory function of Alzheimer's disease (AD). Several related functional connectivity may contribute to the effectiveness of rTMS.  Besides, the baseline functional connectivity between the left hippocampus and left occipitotemporal cortex, left frontoinsular cortex were significantly positively correlated with the improvement of memory recognition function. The baseline functional connectivity between the left hippocampus and left occipitotemporal cortex was significantly positively correlated with the improvement of delayed recall function of memory. 

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Inès Ben Abdallah^1,2, Marion Sourty¹, Mary Mondino¹, Laetitia Degiorgis¹, Julien Lamy¹, Vincent Noblet¹, Marion Rame¹, Cristiana Pistono², Aminé Isik², Marie-Dominique Marinutti², Céline Héraud², Hiroki Sasaguri³, Shoko Hashimoto³, Takashi Saito³, Takaomi Saido³, Chantal Mathis², and Laura Harsan^1,4
1ICube, Université de Strasbourg-CNRS, Strasbourg, France, ²LNCA, Université de Strasbourg-CNRS, Strasbourg, France, ³RIKEN Center for Brain Science, 2-1 Hirosawa, Wako-city, Saitama, Japan, ⁴Department of Biophysics and Nuclear Medicine, University Hospital of Strasbourg, Strasbourg, France

Keywords: Alzheimer's Disease, fMRI (resting state), Preclinical

MRI is a unique tool to study the complexity of functional and structural communication in the brain. To explore the brain architecture of a mouse model of Alzheimer's Disease and highlight sex-dimorphism in the emergence of AD-like signs, we used a recent mouse model, the APP^NL-F/MAPT double knock-in (dKI). In preclinical imaging, we used resting-state graph theory approaches in a longitudinal study associated with behavioral evaluation.  Functional connectivity of perirhinal, dorsal-hippocampus and midbrain nodes were implicated in early memory impairments in dKI female mice. Interestingly, perirhinal-cortex and dorsal-hippocampus are key regions for object-place associative memory and long-term object-recognition.

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Ajay Nemani¹ and Mark Lowe^1
1Cleveland Clinic, Cleveland, OH, United States

Keywords: Alzheimer's Disease, fMRI (resting state), Parcellation, Network Modelling

The search for rsfMRI-based network biomarkers in Alzheimer's disease has yielded inconsistent results.  These models are derived from standard anatomical and functional parcellations that may bias downstream analyses.  We present a network model of Alzheimer's disease based on cohesive parcellation and compare it to traditional measures of network topology.

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Taeyi You^1,2, Taekwan Lee³, Geun Ho Im¹, Seong-gi Kim¹, Sungkwon Chung⁴, and Jung Hee Lee^5
1Center for Neuroscience Imaging Research, Institute of Basic Science, Suwon, Korea, Republic of, ²Biomedical Engineering, Sungkyungkwan University, Suwon, Korea, Republic of, ³Korea Brain Research Institute, Daegu, Korea, Republic of, ⁴Physiology, Sungkyunkwan University, Suwon, Korea, Republic of, ⁵Radiology, Samsung Medical Center, Seoul, Korea, Republic of

Keywords: Alzheimer's Disease, fMRI (task based)

Alzheimer Disease is a neurodegenerative disease that exhibits memory and cognitive deficits. Majority of research has targeted these late-stage biomarkers as treatment targets, yet all have failed in the clinical settings. Detection of early biomarkers is becoming imperative that can be easily and effectively used. fMRI is a quick and non-invasive procedure that can map whole brain activity. Here we use sensory evoked fMRI in a AD mouse model to show longitudinal changes in brain response that can be potential biomarkers for early AD.

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Jasmin A. Keller¹, Sigurdur Sigurdsson ², Bárbara Schmitz Abecassis ¹, Ilse M.J. Kant ^3,4, Mark A. van Buchem¹, Lenore J. Launer⁵, Matthias J.P. van Osch¹, Vilmundur Gudnason^2,6, and Jeroen H.J.M. de Bresser^1
1Department of Radiology, Leiden University Medical Center, Leiden, Netherlands, ²Icelandic Heart Association, Kopavogur, Iceland, ³Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Leiden University Medical Center, Leiden, Netherlands, ⁴Department of Digital Health, University Medical Center Utrecht, Utrecht, Netherlands, ⁵Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, MD, United States, ⁶Faculty of Medicine, University of Iceland, Reykjavik, Iceland

Keywords: Dementia, Aging, Cerebral small vessel disease

Individual brain MRI markers only show at best a modest association with long-term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We implemented a combined hierarchical clustering analysis based on neurodegenerative and neurovascular brain MRI markers and identified 14 distinct subgroups of individuals with different brain MRI phenotypes. These subgroups had a different long-term risk for dementia; especially the multi-burden brain MRI phenotype showed an increased risk (HR: 13.8 (95%-CI:4.28-44.37)). These findings may in the future be useful to determine patient prognosis and may aid in patient selection for future treatment studies.

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Neha Yadav¹, Arkaprava Majumdar¹, and Vivek Tiwari^1
1Department of Biological Sciences, Indian Institute of Science Education and Research Berhampur, Berhampur, India

Keywords: Alzheimer's Disease, Aging

The key to understanding brain-biomarkers depictive of normal cognition and cognitive impairment due to MCI (CI) and/or Alzheimer’s disease (CI-AD) is to identify the series of early, intermediate, and late events that encode brain health. The temporal and spatial order of events of brain health changes observed on MRI, associated with normal aging needs to be precisely delineated from the events associated with cognitive impairment. We have identified early, intermediate and late brain structural and microvascular events distinctive of CN, CI and CI-AD and developed an AI-based platform using an optimal number of MRI features distinctive of cognitive status.

Qixiang Lin¹, Shuai Huang², Aditya Bisht¹, Allan Levey^1,3, James Lah^1,3, and Deqiang Qiu^2,3,4
1Department of Neurology, Emory University, Atlanta, GA, United States, ²Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States, ³Goizueta Alzheimer’s Disease Research Center, Emory University, Atlanta, GA, United States, ⁴Joint Department of BioMedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, United States

Keywords: Alzheimer's Disease, Aging, CSF biomarker; Aβ; Tau; Subcortical; Volume

This study aims to evaluate the association between subcortical volumes and cerebrospinal fluid (CSF) biomarkers of Alzheimer’s Disease (AD) in a large group of healthy aging from a single center. CSF samples were obtained and quantitative levels of amyloid-β and Tau were measured. Subcortical tissue segmentations were performed on T1-weighted MPRAGE scans and the volume of each subcortical structure were calculated. Significant correlations were found between CSF biomarkers of AD and volume of the right and the left caudate. This may indicate that the volume of caudate are associated with CSF AD biomarker in healthy aging participants.  

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Mohammad Rakeen Niaz¹, Yingjuan Wu¹, Abdur Raquib Ridwan², Shengwei Zhang², David A. Bennett², and Konstantinos Arfanakis^1,2
1Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, ²Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States

Keywords: Alzheimer's Disease, Aging, Aging, Atlas, Brain, Gray Matter

The Multichannel Illinois Institute of Technology & Rush university Aging (MIITRA) atlas constructed using high quality MRI data on a large (N=400), diverse, community cohort of non-demented older adults, contains high resolution (0.5mm) structural and diffusion imaging templates. The present work constructed and evaluated a comprehensive set of gyral-based, cytoarchitecture-based, and functional connectivity-based gray matter labels in MIITRA space in order to enhance the functionality of the MIITRA atlas and its interoperability with complementary atlases.

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Xiaowei Zhuang¹, Zhengshi Yang¹, and Dietmar Cordes^1
1Lou Ruvo Center for Brain Health, Cleveland Clinic, Las Vegas, NV, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, Imaging genetics

To better characterize the Alzheimer’s disease pathogenesis and boost the statistical power, we applied a multivariate data-driven approach (independent component analysis (ICA)) to decompose 70000+ single nucleotide variants (SNVs) from 239 AD-associated genes into multiple functionally relevant subsets. We demonstrated that several genetic clusters identified by ICA could be specially associated with AD clinical diagnosis, AD amyloid or tau pathology, and/or MRI-derived neurodegenerative markers. This type of multivariate data-driven approach could be helpful to further delineate diagnoses-associated or neuropathology-associated genetic variants in AD.

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Oluwatobi Folorunsho Adeyemi^1,2, Olivier Mougin¹, George Hutchinson¹, Penny Gowland¹, Richard Bowtell¹, and Akram Hosseini^3
1University of Nottingham, Nottingham, United Kingdom, ²Physics, University of Abuja, Abuja, Nigeria, ³Nottingham University Hospital, Nottingham, United Kingdom

Keywords: Alzheimer's Disease, Alzheimer's Disease, High-Field MRI, Quantitative Susceptibility Mapping, Segematation

Providing a non-invasive biomarker for the diagnosis of AD has been challenging. In this study 25 participants (12 AD and 13 healthy controls) were scanned on a 7T MRI scanner. Cognitive assessments and analysis of the CSF for Amyloidb1-42 performed by trained Clinicians. The volume of the hippocampal subregion shows a linear relationship CSF- Amyloidb1-42 for all the subfield of the hippocampus, but this trend was only significant for the ERC with p=0.023. The association of the volume of ERC and CSF-amyloid-beta(1-42) suggests the potential for using high field-high resolution MRI as a biomarker for an early identification of AD.

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Sean Deoni¹, Phoebe Burton², Jennifer Beauchemin², Rosa Cano-Lorente², Matthew De Both³, Megan Johnson³, Lee Ryan⁴, and Mathew Huentleman^3
1MNCH D&T, Bill & Melinda Gates Foundation, Seattle, WA, United States, ²Advanced Baby Imaging Lab, Providence, RI, United States, ³TGen, Pheonix, AZ, United States, ⁴University of Arizona, Tucson, AZ, United States

Keywords: Dementia, Aging, Remote Neuroimaging

In this study we sought to (1) Determine the feasibility of collecting remote MRI and cognitive data in adults and elderly individuals; and (2) Replicate previously reported population-based associations between regional brain volumes and cognitive performance with an established cognitive assessment, PAL. Overall, this initial report of at-home MRI shows that MRI data collection on a portable low-field MRI system at a participant's home is possible and offers time efficiency, convenience, and accessibility to participants who might otherwise not be able to participate.

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Paola Porcari¹, Saket Patel¹, Elizabeth Coffee¹, Marjan Berishaj ¹, Tanya Jain², Kofi M. Deh¹, Nathaniel T. Kim¹, Yueming Li², and Kayvan Keshari^1
1Radiology, Memoral Sloan Kettering Cancer Center, New York, NY, United States, ²Chemical Biology Program, Memoral Sloan Kettering Cancer Center, New York, NY, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, animal model, 13C HP MRI

Alzheimer’s disease (AD) is  devastating and progressive disease. The non-invasive detection of early onset AD along with the mechanisms that drive its progression are still limited. Recent work has implicated metabolic reprogramming as an earlier AD potential indicator. Therefore, we investigated an AD mouse model at the early stage of development with the goal to evaluate whether co-hyperpolarized [1-¹³C]pyruvate and [1-13C]dehydroascorbate (DHA) along with 3D MRSI might provide insights into the brain metabolism of FAD mice at the onset of the disease. The metabolism of these  translatable biomarkers would then give insight on our understanding of AD diagnosis and treatment. 

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Sandeep Ganji^1,2, Brian Johnson^3,4, Spencer Waddle¹, Johannes Peeters⁵, Laszlo Mechtler⁶, and Nandor Pinter^6,7
1Philips, Rochester, MN, United States, ²Mayo Clinic, Rochester, MN, United States, ³Philips, Gainesville, FL 32608, FL, United States, ⁴University of Texas Southwestern Medical Center, Dallas, TX, United States, ⁵Philips, Eindhoven, Netherlands, ⁶Dent Neurologic Institute, Buffalo, NY, United States, ⁷Department of Neurosurgery, University at Buffalo, Buffalo, NY, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease

Amyloid Related Imaging Abnormality (ARIA) was reported in 40% of patients treated with anti-amyloid beta drugs in phase 3 trials. It is expected to be a significant factor in the clinical application of new Alzheimer’s Disease (AD) modifying therapies and requires standardized and practical imaging. By employing Compressed-SENSE (CS-SENSE) and newer deep learning based SmartSpeed to accelerate acquisition we created a robust MRI protocol that can be completed in under ten minutes without loss of any image quality. This accelerated protocol can provide a clinically feasible strategy for scanning large populations.

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Wenli Li¹, Miao Zhang², Yibo Zhao^3,4, Yudu Li^3,5, Wen Jin^3,4, Jialin Hu¹, Yaoyu Zhang¹, Danni Wang¹, Biao Li², Jun Liu⁶, Binyin Li⁶, Zhi-Pei Liang^3,4, and Yao Li^1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China, ³Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁵National Center for Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁶Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University of Medicine, Shanghai, China

Keywords: Alzheimer's Disease, Alzheimer's Disease

Functional network failure has been implicated in the pathophysiology of Alzheimer’s disease (AD). FDG-PET is a well-established tool to map the glucose hypometabolism during AD progression. MRSI indexes the neuronal loss/astrogliosis noninvasively, but has been limited to single-voxel/slice techniques. Using a high-resolution 3D MRSI technique, we evaluated the neurometabolic changes in brain networks and compared them with glucose hypometabolism. Decreases in NAA and increases in mI were found in all networks. NAA reduction followed similar patterns to the hypometabolism over cognitive decline. Combined 3D MRSI and atrophy biomarkers showed comparable performance to FDG-PET in predicting cognitive decline in AD patients.

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Dean Tran¹, Phillip DiGiacomo¹, Marios Georgiadis¹, Nicholas Edwards², Sharon Bone², Donald Born³, Samuel Webb², and Michael Zeineh^1
1Department of Radiology, Stanford University, Stanford, CA, United States, ²Stanford Synchrotron Radiation Lightsource, SLAC National Accelerator Laboratory, Menlo Park, CA, United States, ³Department of Pathology, Stanford University, Stanford, CA, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, X-ray microscopy

Recent studies suggest that iron and neuroinflammation are key components of AD pathology. Specifically, ferrous Fe²⁺ can cause oxidative stress, a possible a mechanistic link to disease progression. Correlative ex vivo MRI can detect iron-containing microglia in AD hippocampi, but whether this iron is ferrous is unknown. Synchrotron X-ray absorption near edge spectroscopy (XANES) can quantify iron oxidation state in frozen human brain samples. However, tissue thawing during the long scans might affect the oxidation state. Here, we implement the necessary hardware to interrogate that question and present preliminary evidence that, as specimens thaw, less redox-active ferrous iron is measured.

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Christopher William Davies-Jenkins^1,2, Kathleen E Hupfeld^1,2, Helge J Zöllner^1,2, Gwenn S Smith^3,4, and Georg Oeltzschner^1,2
1The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, MD, United States, ²F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States, ³Department of Psychiatry and Behavioral Sciences, Johns Hopkins Medicine, Baltimore, MD, United States, ⁴Division of Nuclear Medicine and Molecular Imaging, The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medicine, Baltimore, MD, United States

Keywords: Alzheimer's Disease, Alzheimer's Disease, MRS, PET, Amyloid, 7T, MCI

Mild cognitive impairment (MCI), a prodromal stage of Alzheimer’s disease, is increasingly studied by multi-modal beta-amyloid (Aβ) PET and MRS. Most studies have targeted the PCC and a limited number of metabolites. In this study, we analyzed Aβ PET and 7T ¹H-MRS data from the ACC and PCC of MCI patients and healthy controls, using a voxel-specific Aβ metric. Metabolite-amyloid correlations were investigated using multiple regression analysis. We report a novel finding of a differential GABA-amyloid relationship for MCI patients compared with controls in the ACC and support previous reports of amyloid relationships with NAA and myo-inositol.