ISSN# 1545-4428 | Published date: 19 April, 2024
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At-A-Glance Session Detail
   
Age-Related Changes in the Brain
Oral
Neuro
Monday, 06 May 2024
Nicoll 1
13:45 -  15:45
Moderators: In-Young Choi & Binu Thomas
Session Number: O-37
CME Credit

13:450135.
Connectivity-based parcellation of primary and high-order cortex from infancy to adult
Zuozhen Cao1, Mingyang Li1, Zhiyong Zhao1, Yao Shen1, Yiqi Shen1, and Dan Wu1
1Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, HangZhou, China

Keywords: Aging, Aging, parcellation

Motivation: The human brain undergoes a remarkable development from newborn to adulthood in cortex, white matter, and connectivity in previous studies. We speculated connectivity-based cortical parcellation may also change during this process.

Goal(s): To explore whether and how connectivity-based parcellations of different cortices changed from neonate to adult.

Approach: We utilized diffusion MRI (dMRI) to investigate the structure connectivity-based parcellations of cortical sub-regions and compared the parcellation-related features among infants, toddlers, and adults. 

Results: We observed significantly altered parcellation profiles and changing connectivity patterns during developed. Especially, we found larger alternations in high-order cortex, such as insula, compared to primary sensory and motor cortices.

Impact: Connectivity-based parcellation provided a new insight to assess the development of human brain. Primary cortex has developed sufficiently in early life while high-order cortex developed significantly from newborn to adult. Future studies will fill the gap from toddler to adult.

13:570136.
Structural connectome shapes the maturation of cortical morphology from childhood to adolescence
Xinyuan Liang1, Lianglong Sun1, Xuhong Liao2, Tianyuan Lei1, Mingrui Xia1, Dingna Duan1, Zilong Zeng1, Qiongling Li1, Zhilei Xu1, Weiwei Men3, Yanpei Wang1, Shuping Tan4, Jia-Hong Gao3, Shaozheng Qin1, Sha Tao1, Qi Dong1, Tengda Zhao1, and Yong He1
1State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China, 2School of Systems Science, Beijing Normal University, Beijing, China, 3Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China, 4Beijing Huilongguan Hospital, Beijing, China

Keywords: Structural Connectivity, Brain Connectivity, Adolescents

Motivation: Cortical thinning is an important hallmark of the maturation of brain morphology during childhood and adolescence. However, the connectome-based wiring mechanism that underlies cortical maturation remains unclear.

Goal(s): We aim to model how the maturational pattern of cortical morphology is shaped by white matter connectome architecture.

Approach: We integrated neuroimaging, connectome,  transcriptome analyses and computational modeling.

Results: We found that the maturational patterns of cortical morphology are constrained by the white matter connectome and are particularly represented using a network-based diffusion model. Such constraints are predominantly located in frontoparietal nodes and are linked with the expression of genes associated with microstructural developmental processes.

Impact: Our results highlight the importance of white matter network structure in shaping the coordinated maturation of regional cortical morphology, which demonstrates the feasibility of using a network model to reveal the maturational principle of cortical morphology from childhood to adolescence.

14:090137.
Choroid Plexus Structural and vascular Changes Associated with Aging in the HCP Dataset
Zhe Sun1,2,3, Chenyang Li1,2,3, Thomas Wisniewski4,5, and Yulin Ge1,2
1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Grossman School of Medicine, New York, NY, United States, 2Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Grossman School of Medicine, New York, NY, United States, 3Vilcek Institute of Graduate Biomedical Sciences, NYU Grossman School of Medicine, New York, NY, United States, 4Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, United States, 5Departments of Pathology and Psychiatry, NYU Grossman School of Medicine, New York, NY, United States

Keywords: Aging, Aging, Human Connectome Project, choroid plexus

Motivation: Analyzing ChP changes in normal aging is essential for grasping its role in neurological disorders.
 

Goal(s): To evaluate ChP changes with age using diffusion and perfusion MRI in a lifespan HCP-aging dataset.  
 

Approach: MR images of 641 healthy participants aged from 36 to 90 years old were analyzed to extract diffusion and perfusion measurements of ChP to investigate their age-related changes.
 

Results: With age, the ChP undergoes significant changes, including increased volume, reduced blood flow, elevated MD values, and a more rapid decline in blood flow compared to gray and white matter.

Impact: This study offers a comprehensive evaluation of age-related changes in the ChP, enhancing our comprehension of its potential involvement in age-related cognitive decline. Furthermore, age-related ChP alterations exhibit distinct patterns compared to changes in gray and white matter.   

14:210138.
Age-related differences in macromolecular resonances observed in ultra-short-TE STEAM MR spectra at 7 T
Guglielmo Genovese1, Melissa Terpstra1, Pavel Filip1,2, Silvia Mangia1, J. Riley McCarten3,4, Laura S. Hemmy3,5, and Małgorzata Marjańska1
1Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States, 2Department of Neurology, Charles University, First Faculty of Medicine and General University Hospital, Prague, Czech Republic, 3Geriatric Research, Education and Clinical Center, Veterans Affairs Health Care System, Minneapolis, MN, United States, 4Department of Neurology, University of Minnesota, Minneapolis, MN, United States, 5Department of Psychiatry, University of Minnesota, Minneapolis, MN, United States

Keywords: Spectroscopy, Data Analysis, Macromolecules, LCModel, ultra-high field

Motivation: Macromolecular signals mainly originate from amino-acids within flexible cytosolic proteins, contributing to 1H-MR spectra. Previous studies have yielded inconsistent results regarding age-related differences in macromolecular resonances.

Goal(s): To investigate the macromolecular content across a wide age range in a large cohort of healthy participants.

Approach: Spectroscopy data were acquired at 7 T. The macromolecular content was investigated in 134 datasets from a cohort ranging in age from 19 to 89 years.

Results: Age-related effects were observed for macromolecular peaks. Some macromolecular resonances had significantly higher content at 30-40 years of age while others at 60-70 years of age.

Impact: Our findings strengthen the necessity of using age-matched measured macromolecules during quantification of metabolite concentrations. The ability to detect differences in macromolecular content may be helpful for understanding the neurodegenerative processes associated with aging.

14:330139.
Quantitating Neuroanatomic Volumetry and White Matter Hyperintensity Lesion wrapped in AI Model in Aging Cohorts as a determinant of Brain Age
Neha Yadav1, Niraj Kumar Gupta1, and Vivek Tiwari1
1Department of Biological Sciences, Indian Institute of Science Education and Research Berhampur, Berhampur, India

Keywords: Aging, Aging, Brain Age, Volumetry, White Matter Hyperintensity

Motivation: In an aging population, a subset of individuals at any age group present with low white matter hyperintensity (WMH) volume in the brain, while another subset has intermediate to high WMH load.

Goal(s): To establish a Brain Age Estimation model involving WMH lesion quantification as a clinical indicator of Brain Health.

Approach:  We have investigated the ‘Brain Health’ in terms of Brain Age using neuroanatomic volume, thickness together with WMH load across cognitively normal, impaired and Alzheimer’s Disease subjects.
 

Results: An increased Brain Age gap is observed for the subjects with elevated WMH load compared to the brains with low WMH.

Impact: Brain health is a composite representation of structural, fiber and vascular health. For the first time, a MR based quantitative platform with WMH load and comprehensive neuroanatomic volumetry is established, which estimates ‘Brain Age’ as an indicator of Brain Health.

14:450140.
Normative modeling of brain white matter microstructure using diffusion tensor metrics in 52,719 participants
Julio Ernesto Villalón Reina1, Alyssa H. Zhu1, Talia M. Nir1, Sophia I. Thomopoulus1, Emily Laltoo1, Elnaz Nourollahimoghadam1, Sebastian Benavidez1, Clara A. Moreau1, Yixue Feng1, Tamoghna Chattopadhyay1, Leila Nabulsi1, Katherine E. Lawrence1, Neda Jahanshad1, and Paul M. Thompson1
1USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States

Keywords: White Matter, Diffusion Tensor Imaging

Motivation: It is currently difficult to compute normative models for diffusion MRI metrics of the brain’s white matter across the lifespan due to scanner/protocol effects that are hard to eliminate during harmonization.

Goal(s): We set out to build large-scale multi-site normative models for DTI metrics of the white matter of the human brain. 

Approach: Hierarchical Bayesian Regression was run on ROI metrics derived using the ENIGMA-DTI protocol to determine the age trajectory and centile curves of DTI metrics.

Results: We built DTI reference models based on 52,719 subjects that allowed us to detect deviations from the norm for patients with brain diseases.

Impact: These reference models are valuable for detecting microstructural deviations from the normal range, while modeling scanner, protocol and cohort effects. They will be used in our ENIGMA consortium to map profiles of microstructural anomalies in >20 neurological and psychiatric conditions.

14:570141.
Submillimeter Isotropic in vivo Quantitative Susceptibility Mapping: Application to Women with Suspected Coronary Microvascular Dysfunction
Arzu C Has Silemek1,2, Sreekanth Madhusoodhanan1, Janet Wei 3, Oana Dumitrascu4, Sarah Kremen1, Debiao Li2, Michael D Nelson5, Zaldy S Tan6, Jeffrey Wertheimer7, Yibin Xie2, Noel Bairey Merz3, Wei Gao2, and Pascal Sati1
1Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 2Department of Biomedical Sciences and Imaging, Biomedical Imaging Research Institute (BIRI), Cedars-Sinai Medical Center, Los Angeles, CA, United States, 3Barbra Streisand Women's Heart Center, Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 4Department of Neurology, Mayo Clinic College of Medicine and Science, Scottsdale, AZ, United States, 5Department of Kinesiology, The University of Texas at Arlington, Arlington, TX, United States, 6Departments of Neurology and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States, 7Department of Physical Medicine and Rehabilitation, Cedars-Sinai Medical Center, Los Angeles, CA, United States

Keywords: Aging, Quantitative Susceptibility mapping, Heart, Brain, women, INOCA, Aging, Dementia

Motivation: The study's motivation lies in overcoming the low-resolution limitations of Quantitative susceptibility mapping (QSM) in 3T-MRI, which is critical for investigating brain aging and neurodegeneration.

Goal(s): We aimed to construct high-resolution QSM using submillimeter T2*-3D-EPI sequence to measure iron deposition in the cortical and deep gray matter of women with suspected coronary microvascular dysfunction.

Approach: The approach involved a novel imaging protocol, TGV-based QSM reconstruction, and statistical analysis correlating iron deposition with cardiovascular health markers.

Results: Results indicate a significant association between brain iron accumulation and microvascular heart conditions, pointing to a potential interconnected pathology in women with suspected coronary microvascular dysfunction.

Impact: The study's high-resolution QSM technique could revolutionize neuroimaging, allowing clinicians to detect microvascular changes early and personalize treatments. It opens avenues for exploring the systemic nature of microvascular diseases, potentially altering approaches to managing neurodegenerative and cardiovascular conditions.

15:090142.
Dedifferentiation of functional hierarchical axis captures individual differences in cognition performance and disease progression
Chenye Shen1, Chaoqiang Liu1, Nanguang Chen1, and Anqi Qiu1,2,3
1Biomedical Engineering, National University of Singapore, Singapore, Singapore, 2Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung hom, Hong Kong, 3Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States

Keywords: Functional Connectivity, Aging

Motivation: The healthy aging brain exhibits functional dedifferentiation, yet a consensus on its characterization remains elusive, hindering individual-level assessment of unhealthy aging.

Goal(s): We aim to utilize the functional hierarchical axis to elucidate primary alterations in functional dedifferentiation during healthy aging.

Approach: We developed a measure to quantify the heterogeneity of network dedifferentiation along the functional hierarchical axis, and assessed its relevance to cognition and neurological diseases at an individual level. 

Results: Functional dedifferentiation in attention and control networks captures substantial individual differences in aging, cognition, and diseases. The heterogeneity of functional dedifferentiation along the functional hierarchical axis predicts domain-specific disease risk. 

Impact: Brain aging primarily entails association and control network integrity deterioration on the functional hierarchical axis. The individual differences of functional dedifferentiation on this axis provide risk assessments of unhealthy brain aging.

15:210143.
Brain arteriolosclerosis in community-based older adults is associated with lower gray matter volume
Ana Tomash1, Mahir Tazwar1, Md Tahmid Yasar1, David A Bennett2, Julie A Schneider2, and Konstantinos Arfanakis1,2
1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States, 2Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States

Keywords: Dementia, Blood vessels, Arteriolosclerosis, Brain, Pathology, Ex-vivo applications, Gray matter, Neurodegeneration, Vascular

Motivation: Despite brain arteriolosclerosis being one of the most prevalent small vessel diseases in older adults, its association with regional brain volumes has not been investigated.

Goal(s): To investigate the association of brain arteriolosclerosis with regional gray matter volumes.

Approach: Regional brain volumetry on ex-vivo MRI and detailed neuropathological examination were combined in a large number of community-based older adults that came to autopsy.

Results: More severe brain arteriolosclerosis was associated with lower volume in a number of gray matter regions, including medial orbitofrontal, superior frontal, pericalcarine, cuneus, and lateral occipital areas, independently of the effects of other neuropathologies.

Impact: The finding that brain arteriolosclerosis is associated with lower regional gray matter volumes independently of the effects of other neuropathologies enhances our understanding of the brain anomalies associated with this common small vessel disease pathology.

15:330144.
The Influence of Accelerated Brain Aging on Coactivation Pattern Dynamics in Parkinson's Disease
Su Yan1 and Wenzhen Zhu1
1Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China

Keywords: Parkinson's Disease, Parkinson's Disease

Motivation: Aging has been widely recognized as the primary risk factor for brain degeneration, and Parkinson’s disease (PD) tends to follow accelerated aging trajectories. 

Goal(s): The aim of this study was to investigate the influence of structural brain aging on large-scale functional network temporal dynamics in PD.

Approach: The level of brain aging was assessed by calculating global and local brain age gap estimates from T1-weighted images. Coactivation patterns of the whole brain were identified from fMRI to capture neural network activity.

Results: Accelerated structural brain aging in PD affected brain function, which manifested as aberrant brain network dynamics.

Impact: These findings relate whole-brain coactivation patterns to spatial variation in accelerated brain aging, providing insights into the neuropathological mechanisms in neurodegenerative diseases and implying the possibility of intervention for PD progression by slowing the brain aging process.