Fatemeh Mohammadian¹, Arash Zare Sadeghi², Hanieh Mobarak Salari³, Mahsa Talebi¹, Hassan Hashemi³, Hamid Reza Saligheh Rad^1,4, and Maryam Noroozian^5
1Department of Medical physics and Biomedical Engineering, Tehran university of medical sciences, TEHRAN, Iran (Islamic Republic of), ²Medical Physics Department, Iran University of Medical Sciences, TEHRAN, Iran (Islamic Republic of), ³Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, TEHRAN, Iran (Islamic Republic of), ⁴Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran (Islamic Republic of), ⁵Department of Psychiatry, Tehran university of medical sciences, TEHRAN, Iran (Islamic Republic of)

Alzheimer's disease (AD) is a network connection dysfunction syndrome. An approximate picture of functional integration and statistical dependence on responses between different regions of the brain can be defined by functional connectivity (FC). Explanation of the statistical dependencies and estimating how the dynamics of neurons affect each other remotely is done by effective connectivity (EC). Studying directional interactions between different regions of the brain plays a key role in our understanding of the functional integration of brain networks.

Emilio Cipriano^1,2, Laura Biagi¹, Paolo Bosco¹, Giovanni Cioni¹, Alessandro Sale³, Nicoletta Berardi³, Michela Matteoli³, Michela Tosetti¹, and the Train the Brain Consortium^4
1FiRMLAB, IRCCS Stella Maris, Pisa, Italy, ²Department of Physics, University of Pisa, Pisa, Italy, ³Institute of Neuroscience of the CNR, Pisa, Italy, ⁴the Train the Brain Consortium, Pisa, Italy

Graph theory approach was used to analyze structural and functional connectivity networks to identify candidate biomarkers of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer’s disease (AD),  for an early diagnosis and intervention. We proposed a method of brain network analysis to combine  structural and functional connectivity networks information. Through graph measures (Segregation, Centrality and Global Efficiency), we evaluated the differences between  MCI and healthy control (HC) subjects  as well the possible effects of physical/cognitive training, in terms of structural and functional connectivity, in MCI population.

Yin Tang¹, Ling Zhang¹, Hongyuan Ding¹, Yi Zhu², Yaxin Gao³, Long Qian⁴, Weiqiang Dou⁴, and Ming Qi^1
1Radiology department, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, ²Rehabilitation Department, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China, ³Rehabilitation Department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China, ⁴MR Research China, GE Healthcare, Beijing, China

The main goal of this study was to investigate the changes of neurovascular coupling (NVC) in patients at early stages of Alzheimer’s disease. Patients with SCD and MCI were enrolled. Significantly changes of neurovascular coupling have been separately found between SCD, MCI patients and HCs in the regions involved the left Rolandic operculum, left anterior orbital gyrus, right insula, right parahippocampal gyrus, left lingual gyrus, median cingulate and paracingulate gyri and left supramarginal gyrus. In addition, these changes of NVC showed strong correlations with multiple clinical scales. Therefore, NVC can be an effective method for early diagnosis of SCD patients.

Elizabeth G. Keeling^1,2, Maurizio Bergamino¹, Nicholas J. Sisco¹, Sudarshan Ragunathan¹, C. Chad Quarles¹, George P. Prigatano¹, and Ashley M. Stokes^1
1Barrow Neurological Institute, Phoenix, AZ, United States, ²Arizona State University, Tempe, AZ, United States

Functional connectivity, measured with BOLD-fMRI, has been previously used to study changes in aging and Alzheimer’s disease. A combined spin- and gradient-echo (SAGE) acquisition may be able to more sensitively distinguish between disease-related changes in functional connectivity. Therefore, this study aims to implement SAGE in resting-state fMRI to assess differences between macro- and microvasculature-sensitive data, between SAGE maps and single-echo methods, and between healthy aging and cognitively impaired cohorts’ functional networks.

Won-Jin Moon¹, Jong Duck Choi¹, Yeonsil Moon², Hee Jin Kim³, Younghee Yim⁴, and Subin Lee^5
1Radiology, Konkuk University Medical Center, Seoul, Korea, Republic of, ²Neurology, Konkuk University Medical Center, Seoul, Korea, Republic of, ³Neurology, Hanyang University Hospital, Seoul, Korea, Republic of, ⁴Radiology, Chung-Ang University Hospital, Seoul, Korea, Republic of, ⁵Electrical and Computer Engineering, Seoul National University, Seoul, Korea, Republic of

In patients with cognitive impairment spectrum, 3T MRI revealed that choroid plexus volume and permeability was associated with cognitive impairment severity. l  In patients with cognitive impairment, choroid plexus (CP) volume followed this order: Alzheimer dementia > late mild cognitive impairment (MCI) > early MCI or subjective cognitive impairment (p<.001)  l  Large CP volume was associated with lower Ktrans (r=-0.403, p=.006) and Vp (r=-0.543, p=.003) l  Increased CP volume was negatively associated with memory function (B=-0.6662, SE=0.2089, p=.002), frontal executive function (B=-0.8973, SE=0.3145, p=.005), and mini-mental status examination score (B=-0.8158, SE=0.3153, p=.01) after adjusting for covariates.

Rashed Sobhan¹, David R. Willis², Rachel Gillings¹, Michael J. Thrippleton³, Joanna M. Wardlaw³, Anne-Marie Minihane¹, Narelle M. Berry¹, and Donnie Cameron^1,4
1Norwich Medical School, University of East Anglia, Norwich, United Kingdom, ²School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom, ³Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom, ⁴C.J. Gorter Centre for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, Netherlands

As part of the CANN trial, we compared blood brain barrier (BBB) integrity in subjective memory impairment (SMI) and mild cognitive impairment (MCI), two early indicators of Alzheimer’s disease. Also, the impact of a combined flavanol and omega-3 fatty acid-based nutritional intervention on BBB leakage was explored for the SMI cohort. Dynamic-contrast-enhanced MRI was performed to obtain fractional plasma volume (v_p) and volume transfer constant (K^Trans) parameters. The results suggest that BBB leakage is similar in the SMI cohort and the nutritional intervention tends to be associated with improved BBB parameters.

Félix Janelle^1,2, Monica Sean^2,3, Félix Dumais², Pascal Tétreault^2,3, Christian Bocti^1,4,5, and Kevin Whittingstall^2
1Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, QC, Canada, ²Médecine nucléaire et radiobiologie, Université de Sherbrooke, Sherbrooke, QC, Canada, ³Anesthésiologie, Université de Sherbrooke, Sherbrooke, QC, Canada, ⁴Service de Neurologie, Département de Médecine, CHUS, Sherbrooke, QC, Canada, ⁵Clinique de la Mémoire et centre de recherche sur le Viellissement, CIUSSS de l'Estrie-CHUS, Sherbrooke, QC, Canada

The Anterior Choroidal Artery (AChA) is a small artery in the cerebral vasculature that perfuses the hippocampus. Its role in brain pathologies and cognitive decline is poorly understood. This could be due to the fact that there is no current standard method to analyse this artery in Time-of-Flight Magnetic Resonance Angiography (TOF-MRA). Here, we propose a fully automated approach for accurately localizing and quantifying the AChA in young healthy subjects. We then used this method to analyse the trajectory of the AChA through the hippocampus and its sub-regions.

Andre Obenaus¹, Amandine Jullienne¹, Brenda Patricia Noarbe¹, Ashley A Keiser², Michelle Vy Trinh¹, Eniko Kramar², Joy Beardwood², Tri Dong², Marcelo Wood², and MODEL AD^3
1Pediatrics, University of California, Irvine, Irvine, CA, United States, ²Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States, ³University of California, Irvine, Irvine, CA, United States

Mouse models of Alzheimer’s disease (AD) currently do not recapitulate accurately the human disease. The MODEL-AD consortium has recently developed new mouse models of AD, including the human amyloid β knockin (hAβKI) mouse. Using high resolution diffusion MRI (dMRI) we examined regional changes in the hAβKI male and female mouse across its lifespan (4-18mo). Sex and regional differences were apparent with age, including reduced diffusion metrics in the hippocampus, that mirrored altered learning and memory. Preclinical MR phenotyping allows for cross-species comparisons for biomarker identification.

Andrada Ianus¹, Renata Cruz¹, Cristina Chavarrias¹, Marco Palombo^2,3,4, and Noam Shemesh^1
1Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal, ²Centre for Medical Image Computing (CMIC), Dept of Computer Science, University College London, London, United Kingdom, ³Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom, ⁴School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

Alzheimer’s disease induces early morphological tissue changes which precede the onset of symptoms and can be important targets for neuroimaging. In this work we employ Soma and Neurite Density Imaging (SANDI), a biophysical modelling approach for diffusion MRI, to investigate tissue microstructure alterations in the 3xTg AD mouse model and compare it with the state-of-the-art Diffusion Kurtosis Imaging (DKI).

Ran Pang¹, Jianli Wang², Prasanna Karunanayaka², Samgan Kanekar², Gela Beselia³, Samika Kanekar³, James R. Connor³, and Qing X. Yang^4
1Departments of Neurosurgery, Pennsylvania State University College of Medicine, PA, United States; Department of Radiology, Dongfang Hospital, Beijing University of Chinese Medicine, Beijing, China, Hershey, PA, United States, ²Departments of Radiology, Pennsylvania State University Colle, Hershey, PA, United States, ³Departments of Neurosurgery, Pennsylvania State University College of Medicine, PA, United States, Hershey, PA, United States, ⁴Departments of 1Neurosurgery and 2Radiology, Pennsylvania State University College of Medicine, PA, United States, Hershey, PA, United States

HFE gene mutation involves iron metabolism, which is shown to directly contribute to myelination process. White matter degeneration in bi-genetic mutation (HFEH63D and ApoE4 allele) carriers was investigated using DTI from the AD Neuroimaging Initiative (ADNI) database. Comparing to the HFEWT/ApoE4+ group, mean diffusivity and radial diffusivity of inferior longitudinal fasciculus in the HFEH63D/ApoE4+ group demonstrated less integrity damage and fewer late-myelination loss with aging reflecting a possible mechanism as HFE polymorphism protective role in partly eliminating ApoE4 being the high-risk factor for AD progressing.

Mathieu David Santin^1,2, Benjamin Galet^1,3, Clément Daube^1,3, and Philippe Ravassard^1,3
1Institut du Cerveau – Paris Brain Institute - ICM, Sorbonne Université, INSERM, CNRS, Paris, France, ²Centre de NeuroImagerie de Recherche – CENIR, Paris, France, ³Molecular Pathophysiology of Parkinson’s Disease Group, Paris, France

This study presents preliminary results obtained on APP muted brain organoids. In vitro images were obtained using ultra-high field MRI and Gd passive staining of samples. MR images were compared to histology and immunohistochemistry slices to confirm the presence of amyloid plaques of mutated APP brain organoid compared to isogenic (control) brain organoid.