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Wang HC, Chen CS, Kuo CC, Huang TY, Kuo KH, Chuang TC, Lin YR, Chung HW. Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis. NMR IN BIOMEDICINE 2024; 37:e5169. [PMID: 38712667 DOI: 10.1002/nbm.5169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 03/21/2024] [Accepted: 04/05/2024] [Indexed: 05/08/2024]
Abstract
In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established techniques, FreeSurfer-Aseg and FSL-FIRST, using three-dimensional T1-weighted MRI scans (n = 1447) procured from public databases. Our evaluation focused on the accuracy and reproducibility of these tools in estimating hippocampal volume. The findings suggest that both SynthSeg and TigerBx are on a par with Aseg and FIRST in terms of segmentation accuracy and reproducibility, but offer a significant advantage in processing speed, generating results in less than 1 min compared with several minutes to hours for the latter tools. In terms of Alzheimer's disease classification based on the hippocampal atrophy rate, SynthSeg and TigerBx exhibited superior performance. In conclusion, we evaluated the capabilities of two deep learning-based segmentation techniques. The results underscore their potential value in clinical and research environments, particularly when investigating neurological conditions associated with hippocampal structures.
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Affiliation(s)
- Hsi-Chun Wang
- Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Chia-Sho Chen
- Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Chung-Chin Kuo
- Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Teng-Yi Huang
- Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Kuei-Hong Kuo
- Division of Medical Image, Far Eastern Memorial Hospital, New Taipei City, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tzu-Chao Chuang
- Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan
| | - Yi-Ru Lin
- Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
| | - Hsiao-Wen Chung
- Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
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2
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Sackl M, Tinauer C, Urschler M, Enzinger C, Stollberger R, Ropele S. Fully Automated Hippocampus Segmentation using T2-informed Deep Convolutional Neural Networks. Neuroimage 2024; 298:120767. [PMID: 39103064 DOI: 10.1016/j.neuroimage.2024.120767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 07/26/2024] [Accepted: 07/31/2024] [Indexed: 08/07/2024] Open
Abstract
Hippocampal atrophy (tissue loss) has become a fundamental outcome parameter in clinical trials on Alzheimer's disease. To accurately estimate hippocampus volume and track its volume loss, a robust and reliable segmentation is essential. Manual hippocampus segmentation is considered the gold standard but is extensive, time-consuming, and prone to rater bias. Therefore, it is often replaced by automated programs like FreeSurfer, one of the most commonly used tools in clinical research. Recently, deep learning-based methods have also been successfully applied to hippocampus segmentation. The basis of all approaches are clinically used T1-weighted whole-brain MR images with approximately 1 mm isotropic resolution. However, such T1 images show low contrast-to-noise ratios (CNRs), particularly for many hippocampal substructures, limiting delineation reliability. To overcome these limitations, high-resolution T2-weighted scans are suggested for better visualization and delineation, as they show higher CNRs and usually allow for higher resolutions. Unfortunately, such time-consuming T2-weighted sequences are not feasible in a clinical routine. We propose an automated hippocampus segmentation pipeline leveraging deep learning with T2-weighted MR images for enhanced hippocampus segmentation of clinical T1-weighted images based on a series of 3D convolutional neural networks and a specifically acquired multi-contrast dataset. This dataset consists of corresponding pairs of T1- and high-resolution T2-weighted images, with the T2 images only used to create more accurate manual ground truth annotations and to train the segmentation network. The T2-based ground truth labels were also used to evaluate all experiments by comparing the masks visually and by various quantitative measures. We compared our approach with four established state-of-the-art hippocampus segmentation algorithms (FreeSurfer, ASHS, HippoDeep, HippMapp3r) and demonstrated a superior segmentation performance. Moreover, we found that the automated segmentation of T1-weighted images benefits from the T2-based ground truth data. In conclusion, this work showed the beneficial use of high-resolution, T2-based ground truth data for training an automated, deep learning-based hippocampus segmentation and provides the basis for a reliable estimation of hippocampal atrophy in clinical studies.
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Affiliation(s)
- Maximilian Sackl
- Department of Neurology, Medical University of Graz, Austria; BioTechMed-Graz, Austria
| | | | - Martin Urschler
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria; BioTechMed-Graz, Austria
| | | | - Rudolf Stollberger
- Institute of Biomedical Imaging, Graz University of Technology, Austria; BioTechMed-Graz, Austria
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Austria; BioTechMed-Graz, Austria.
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Zhang S, Yuan J, Sun Y, Wu F, Liu Z, Zhai F, Zhang Y, Somekh J, Peleg M, Zhu YC, Huang Z. Machine learning on longitudinal multi-modal data enables the understanding and prognosis of Alzheimer's disease progression. iScience 2024; 27:110263. [PMID: 39040055 PMCID: PMC11261013 DOI: 10.1016/j.isci.2024.110263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 03/01/2024] [Accepted: 06/11/2024] [Indexed: 07/24/2024] Open
Abstract
Alzheimer's disease (AD) is a complex pathophysiological disease. Allowing for heterogeneity, not only in disease manifestations but also in different progression patterns, is critical for developing effective disease models that can be used in clinical and research settings. We introduce a machine learning model for identifying underlying patterns in Alzheimer's disease (AD) trajectory using longitudinal multi-modal data from the ADNI cohort and the AIBL cohort. Ten biologically and clinically meaningful disease-related states were identified from data, which constitute three non-overlapping stages (i.e., neocortical atrophy [NCA], medial temporal atrophy [MTA], and whole brain atrophy [WBA]) and two distinct disease progression patterns (i.e., NCA → WBA and MTA → WBA). The index of disease-related states provided a remarkable performance in predicting the time to conversion to AD dementia (C-Index: 0.923 ± 0.007). Our model shows potential for promoting the understanding of heterogeneous disease progression and early predicting the conversion time to AD dementia.
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Affiliation(s)
- Suixia Zhang
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China
| | - Jing Yuan
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Yu Sun
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - Fei Wu
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - Ziyue Liu
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Feifei Zhai
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Yaoyun Zhang
- DAMO Academy, Alibaba Group, 969 Wenyixi Rd, Hangzhou 310058, P.R. China
| | - Judith Somekh
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
| | - Mor Peleg
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Zhengxing Huang
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - for the Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle Study of Aging
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
- DAMO Academy, Alibaba Group, 969 Wenyixi Rd, Hangzhou 310058, P.R. China
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China
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Ysbæk-Nielsen AT. Exploring volumetric abnormalities in subcortical L-HPA axis structures in pediatric generalized anxiety disorder. Nord J Psychiatry 2024; 78:402-410. [PMID: 38573199 DOI: 10.1080/08039488.2024.2335980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 03/22/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Pediatric generalized anxiety disorder (GAD) is debilitating and increasingly prevalent, yet its etiology remains unclear. Some believe the disorder to be propagated by chronic dysregulation of the limbic-hypothalamic-pituitary-adrenal (L-HPA) axis, but morphometric studies of implicated subcortical areas have been largely inconclusive. Recognizing that certain subcortical subdivisions are more directly involved in L-HPA axis functioning, this study aims to detect specific abnormalities in these critical areas. METHODS Thirty-eight MRI scans of preschool children with (n = 15) and without (n = 23) GAD underwent segmentation and between-group volumetric comparisons of the basolateral amygdala (BLA), ventral hippocampal subiculum (vSC), and mediodorsal medial magnocellular (MDm) area of the thalamus. RESULTS Children with GAD displayed significantly larger vSC compared to healthy peers, F(1, 31) = 6.50, pFDR = .048. On average, children with GAD presented with larger BLA and MDm, Fs(1, 31) ≥ 4.86, psFDR ≤ .054. Exploratory analyses revealed right-hemispheric lateralization of all measures, most notably the MDm, F(1, 31) = 8.13, pFDR = .024, the size of which scaled with symptom severity, r = .83, pFDR = .033. CONCLUSION The BLA, vSC, and MDm are believed to be involved in the regulation of anxiety and stress, both individually and collectively through the excitation and inhibition of the L-HPA axis. All were found to be enlarged in children with GAD, perhaps reflecting hypertrophy related to hyperexcitability, or early neuronal overgrowth. Longitudinal studies should investigate the relationship between these early morphological differences and the long-term subcortical atrophy previously observed.
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Gao N, Chen H, Guo X, Hao X, Ma T. Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression. Neuroimage Clin 2024; 43:103623. [PMID: 38821013 PMCID: PMC11179422 DOI: 10.1016/j.nicl.2024.103623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 04/12/2024] [Accepted: 05/25/2024] [Indexed: 06/02/2024]
Abstract
Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multiple independent scans. To accurately segment the hippocampal morphology from longitudinal 3T T1-weighted MR images, we propose a diffeomorphic geodesic guided deep learning method called the GeoLongSeg to mitigate the longitudinal variabilities that unrelated to diseases by enhancing intra-individual morphological consistency. Specifically, we integrate geodesic shape regression, an evolutional model that estimates smooth deformation process of anatomical shapes, into a two-stage segmentation network. We adopt a 3D U-Net in the first-stage network with an enhanced attention mechanism for independent segmentation. Then, a hippocampal shape evolutional trajectory is estimated by geodesic shape regression and fed into the second network to refine the independent segmentation. We verify that GeoLongSeg outperforms other four state-of-the-art segmentation pipelines in longitudinal morphological consistency evaluated by test-retest reliability, variance ratio and atrophy trajectories. When assessing hippocampal atrophy in longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), results based on GeoLongSeg exhibit spatial and temporal local atrophy in bilateral hippocampi of dementia patients. These features derived from GeoLongSeg segmentation exhibit the greatest discriminatory capability compared to the outcomes of other methods in distinguishing between patients and normal controls. Overall, GeoLongSeg provides an accurate and efficient segmentation network for extracting hippocampal morphology from longitudinal MR images, which assist precise atrophy measurement of the hippocampus in early stage of dementia.
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Affiliation(s)
- Na Gao
- School of Electronic & Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China
| | - Hantao Chen
- School of Electronic & Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China
| | - Xutao Guo
- School of Electronic & Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China; Peng Cheng Laboratory, Shenzhen, China
| | - Xingyu Hao
- School of Electronic & Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China
| | - Ting Ma
- School of Electronic & Information Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, China; Peng Cheng Laboratory, Shenzhen, China; Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, Guangdong, China.
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6
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Fragueiro A, Cury C, Santacroce F, Burles F, Iaria G, Committeri G. Medial positioning of the hippocampus and hippocampal fissure volume in developmental topographical disorientation. Hippocampus 2024; 34:204-216. [PMID: 38214182 DOI: 10.1002/hipo.23599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/08/2023] [Accepted: 12/18/2023] [Indexed: 01/13/2024]
Abstract
Developmental topographical disorientation (DTD) refers to the lifelong inability to orient by means of cognitive maps in familiar surroundings despite otherwise well-preserved general cognitive functions, and the absence of any acquired brain injury or neurological condition. While reduced functional connectivity between the hippocampus and other brain regions has been reported in DTD individuals, no structural differences in gray matter tissue for the whole brain neither for the hippocampus were detected. Considering that the human hippocampus is the main structure associated with cognitive map-based navigation, here, we investigated differences in morphological and morphometric hippocampal features between individuals affected by DTD (N = 20) and healthy controls (N = 238). Specifically, we focused on a developmental anomaly of the hippocampus that is characterized by the incomplete infolding of hippocampal subfields during fetal development, giving the hippocampus a more round or pyramidal shape, called incomplete hippocampal inversion (IHI). We rated IHI according to standard criteria and extracted hippocampal subfield volumes after FreeSurfer's automatic segmentation. We observed similar IHI prevalence in the group of individuals with DTD with respect to the control population. Neither differences in whole hippocampal nor major hippocampal subfield volumes have been observed between groups. However, when assessing the IHI independent criteria, we observed that the hippocampus in the DTD group is more medially positioned comparing to the control group. In addition, we observed bigger hippocampal fissure volume for the DTD comparing to the control group. Both of these findings were stronger for the right hippocampus comparing to the left. Our results provide new insights regarding the hippocampal morphology of individuals affected by DTD, highlighting the role of structural anomalies during early prenatal development in line with the developmental nature of the spatial disorientation deficit.
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Affiliation(s)
- Agustina Fragueiro
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, Rennes, France
| | - Claire Cury
- Univ Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, Empenn-ERL U 1228, Rennes, France
| | - Federica Santacroce
- Department of Neuroscience, Imaging and Clinical Sciences, and ITAB, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Ford Burles
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Giuseppe Iaria
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada
| | - Giorgia Committeri
- Department of Neuroscience, Imaging and Clinical Sciences, and ITAB, University G. d'Annunzio of Chieti-Pescara, Chieti, Italy
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7
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Lorenzetti V, Gaillard A, McTavish E, Grace S, Rossetti MG, Batalla A, Bellani M, Brambilla P, Chye Y, Conrod P, Cousijn J, Labuschagne I, Clemente A, Mackey S, Rendell P, Solowij N, Suo C, Li CSR, Terrett G, Thompson PM, Yücel M, Garavan H, Roberts CA. Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study. Cannabis Cannabinoid Res 2024. [PMID: 38498015 DOI: 10.1089/can.2023.0204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024] Open
Abstract
Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.
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Affiliation(s)
- Valentina Lorenzetti
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Alexandra Gaillard
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- Centre for Mental Health and Department of Health Sciences and Biostatistics, Swinburne University, Hawthorn, Australia
| | - Eugene McTavish
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Sally Grace
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Maria Gloria Rossetti
- UOC Psichiatria, Azienda Ospedaliera Universitaria Integrata (AOUI), Verona, Italy
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - Albert Batalla
- Department of Psychiatry, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Marcella Bellani
- Section of Psychiatry, Department of Neuroscience, Biomedicine and Movement Science, University of Verona, Verona, Italy
| | - Paolo Brambilla
- UOC Psichiatria, Azienda Ospedaliera Universitaria Integrata (AOUI), Verona, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Yann Chye
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, Canada
| | - Janna Cousijn
- Neuroscience of Addiction Lab, Center for Substance Use and Addiction Research (CESAR), Department of Psychology, Education & Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Izelle Labuschagne
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Adam Clemente
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Peter Rendell
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Nadia Solowij
- School of Psychology, Faculty of the Arts, Social Sciences and Humanities, University of Wollongong, Wollongong, Australia
| | - Chao Suo
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Gill Terrett
- Neuroscience of Addiction and Mental Health Program, Healthy Brain and Mind Research Centre, School of Behavioural and Health Sciences, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia
| | - Paul M Thompson
- Department of Neurology, Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Marina del Rey, California, USA
| | - Murat Yücel
- QIMR Berghofer Medical Research Institute, Herston, Australia
| | - Hugh Garavan
- School of Psychology, Faculty of Health and Behavioural Sciences, University of Queensland, St Lucia, Australia
| | - Carl A Roberts
- Department of Psychology, Institute of Population Health, University of Liverpool, Liverpool, United Kingdom
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8
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Boecker H, Daamen M, Kunz L, Geiß M, Müller M, Neuss T, Henschel L, Stirnberg R, Upadhyay N, Scheef L, Martin JA, Stöcker T, Radbruch A, Attenberger U, Axmacher N, Maurer A. Hippocampal subfield plasticity is associated with improved spatial memory. Commun Biol 2024; 7:271. [PMID: 38443439 PMCID: PMC10914736 DOI: 10.1038/s42003-024-05949-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 02/21/2024] [Indexed: 03/07/2024] Open
Abstract
Physical exercise studies are generally underrepresented in young adulthood. Seventeen subjects were randomized into an intervention group (24.2 ± 3.9 years; 3 trainings/week) and 10 subjects into a passive control group (23.7 ± 4.2 years), over a duration of 6 months. Every two months, performance diagnostics, computerized spatial memory tests, and 3 Tesla magnetic resonance imaging were conducted. Here we find that the intervention group, compared to controls, showed increased cardiorespiratory fitness, spatial memory performance and subregional hippocampal volumes over time. Time-by-condition interactions occurred in right cornu ammonis 4 body and (trend only) dentate gyrus, left hippocampal tail and left subiculum. Increases in spatial memory performance correlated with hippocampal body volume changes and, subregionally, with left subicular volume changes. In conclusion, findings support earlier reports of exercise-induced subregional hippocampal volume changes. Such exercise-related plasticity may not only be of interest for young adults with clinical disorders of hippocampal function, but also for sedentary normal cohorts.
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Affiliation(s)
- Henning Boecker
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany.
| | - Marcel Daamen
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Lukas Kunz
- Department of Epileptology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Melanie Geiß
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Moritz Müller
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Thomas Neuss
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Leonie Henschel
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Rüdiger Stirnberg
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Neeraj Upadhyay
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Lukas Scheef
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Jason A Martin
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Tony Stöcker
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
| | - Alexander Radbruch
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Nikolai Axmacher
- Department of Neuropsychology, Faculty of Psychology, Ruhr University Bochum, Universitätsstr. 150, 44801, Bochum, Germany
| | - Angelika Maurer
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases, Venusberg-Campus 1/99, 53127, Bonn, Germany
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9
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Evans JW, Graves MC, Nugent AC, Zarate CA. Hippocampal volume changes after (R,S)-ketamine administration in patients with major depressive disorder and healthy volunteers. Sci Rep 2024; 14:4538. [PMID: 38402253 PMCID: PMC10894199 DOI: 10.1038/s41598-024-54370-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 02/12/2024] [Indexed: 02/26/2024] Open
Abstract
The hippocampus and amygdala have been implicated in the pathophysiology and treatment of major depressive disorder (MDD). Preclinical models suggest that stress-related changes in these regions can be reversed by antidepressants, including ketamine. Clinical studies have identified reduced volumes in MDD that are thought to be potentiated by early life stress and worsened by repeated depressive episodes. This study used 3T and 7T structural magnetic resonance imaging data to examine longitudinal changes in hippocampal and amygdalar subfield volumes associated with ketamine treatment. Data were drawn from a previous double-blind, placebo-controlled, crossover trial of healthy volunteers (HVs) unmedicated individuals with treatment-resistant depression (TRD) (3T: 18 HV, 26 TRD, 7T: 17 HV, 30 TRD) who were scanned at baseline and twice following either a 40 min IV ketamine (0.5 mg/kg) or saline infusion (acute: 1-2 days, interim: 9-10 days post infusion). No baseline differences were noted between the two groups. At 10 days post-infusion, a slight increase was observed between ketamine and placebo scans in whole left amygdalar volume in individuals with TRD. No other differences were found between individuals with TRD and HVs at either field strength. These findings shed light on the timing of ketamine's effects on cortical structures.
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Affiliation(s)
- Jennifer W Evans
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, 10 Center Dr., Bldg 10, Rm 7-3335, Bethesda, MD, 20814, USA.
| | - Morgan C Graves
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, 10 Center Dr., Bldg 10, Rm 7-3335, Bethesda, MD, 20814, USA
| | - Allison C Nugent
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, 10 Center Dr., Bldg 10, Rm 7-3335, Bethesda, MD, 20814, USA
- MEG Core, NIMH, Bethesda, MD, USA
| | - Carlos A Zarate
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, 10 Center Dr., Bldg 10, Rm 7-3335, Bethesda, MD, 20814, USA
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10
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Chu T, Liu Y, Gui B, Zhang Z, Zhang G, Dong F, Dong J, Lin S. Hippocampal Subregions Volume and Texture for the Diagnosis of Mild Cognitive Impairment. Exp Aging Res 2024:1-12. [PMID: 38357913 DOI: 10.1080/0361073x.2024.2313940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Accepted: 01/16/2024] [Indexed: 02/16/2024]
Abstract
The aim was to examine the diagnostic efficacy of hippocampal subregions volume and texture in differentiating amnestic mild cognitive impairment (MCI) from normal aging changes. Ninety MCI subjects and eighty-eight well-matched healthy controls (HCs) were selected. Twelve hippocampal subregions volume and texture features were extracted using Freesurfer and MaZda based on T1 weighted MRI. Then, two-sample t-test and Least Absolute Shrinkage and Selection Operator (LASSO) regression were developed to select a subset of the original features. Support vector machine (SVM) was used to perform the classification task and the area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the diagnostic efficacy of the model. The volume features with high discriminative power were mainly located in the bilateral CA1 and CA4, while texture feature were gray-level non-uniformity, run length non-uniformity and fraction. Our model based on hippocampal subregions volume and texture features achieved better classification performance with an AUC of 0.90. The volume and texture of hippocampal subregions can be utilized for the diagnosis of MCI. Moreover, we found that the features that contributed most to the model were mainly textural features, followed by volume. These results may guide future studies using structural scans to classify patients with MCI.
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Affiliation(s)
- Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
| | - Yajun Liu
- Imaging Department, Liaocheng Infectious Disease Hospital, Liaocheng, Shandong, P. R.China
| | - Bin Gui
- Department of Radiology, Wendeng Orthopedic Hospital, Weihai, Shandong, P. R. China
| | - Zhongsheng Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
| | - Gang Zhang
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
| | - Fanghui Dong
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
| | - Jianli Dong
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
| | - Shujuan Lin
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, Shandong, P. R. China
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11
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Monereo-Sánchez J, Jansen JFA, van Boxtel MPJ, Backes WH, Köhler S, Stehouwer CDA, Linden DEJ, Schram MT. Association of hippocampal subfield volumes with prevalence, course and incidence of depressive symptoms: The Maastricht Study. Br J Psychiatry 2024; 224:66-73. [PMID: 37993980 PMCID: PMC10807974 DOI: 10.1192/bjp.2023.143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 08/09/2023] [Accepted: 09/26/2023] [Indexed: 11/24/2023]
Abstract
BACKGROUND Late-life depression has been associated with volume changes of the hippocampus. However, little is known about its association with specific hippocampal subfields over time. AIMS We investigated whether hippocampal subfield volumes were associated with prevalence, course and incidence of depressive symptoms. METHOD We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1-weighted and fluid-attenuated inversion recovery 3T magnetic resonance images. Depressive symptoms were assessed at baseline and annually over 7 years of follow-up (9-item Patient Health Questionnaire). We used negative binominal, logistic, and Cox regression analyses, corrected for multiple comparisons, and adjusted for demographic, cardiovascular and lifestyle factors. RESULTS A total of n = 4174 participants were included (mean age 60.0 years, s.d. = 8.6, 51.8% female). Larger right hippocampal fissure volume was associated with prevalent depressive symptoms (odds ratio (OR) = 1.26, 95% CI 1.08-1.48). Larger bilateral hippocampal fissure (OR = 1.37-1.40, 95% CI 1.14-1.71), larger right molecular layer (OR = 1.51, 95% CI 1.14-2.00) and smaller right cornu ammonis (CA)3 volumes (OR = 0.61, 95% CI 0.48-0.79) were associated with prevalent depressive symptoms with a chronic course. No associations of hippocampal subfield volumes with incident depressive symptoms were found. Yet, lower left hippocampal amygdala transition area (HATA) volume was associated with incident depressive symptoms with chronic course (hazard ratio = 0.70, 95% CI 0.55-0.89). CONCLUSIONS Differences in hippocampal fissure, molecular layer and CA volumes might co-occur or follow the onset of depressive symptoms, in particular with a chronic course. Smaller HATA was associated with an increased risk of incident (chronic) depression. Our results could capture a biological foundation for the development of chronic depressive symptoms, and stresses the need to discriminate subtypes of depression to unravel its biological underpinnings.
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Affiliation(s)
- Jennifer Monereo-Sánchez
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; and Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, the Netherlands
| | - Jacobus F. A. Jansen
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; and Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, the Netherlands
| | - Martin P. J. van Boxtel
- Alzheimer Centrum Limburg, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands
| | - Walter H. Backes
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, the Netherlands; and School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands
| | - Sebastian Köhler
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; and Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, the Netherlands
| | - Coen D. A. Stehouwer
- School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, the Netherlands; and Department of Internal Medicine, Maastricht University Medical Center, the Netherlands
| | - David E. J. Linden
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands
| | - Miranda T. Schram
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, the Netherlands; Department of Internal Medicine, Maastricht University Medical Center, the Netherlands; and Maastricht Heart + Vascular Center, Maastricht University Medical Center, the Netherlands
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12
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Huang J, Cheng R, Liu X, Chen L, Luo T. Unraveling the link: white matter damage, gray matter atrophy and memory impairment in patients with subcortical ischemic vascular disease. Front Neurosci 2024; 18:1355207. [PMID: 38362024 PMCID: PMC10867202 DOI: 10.3389/fnins.2024.1355207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 01/17/2024] [Indexed: 02/17/2024] Open
Abstract
Introduction Prior MRI studies have shown that patients with subcortical ischemic vascular disease (SIVD) exhibited white matter damage, gray matter atrophy and memory impairment, but the specific characteristics and interrelationships of these abnormal changes have not been fully elucidated. Materials and methods We collected the MRI data and memory scores from 29 SIVD patients with cognitive impairment (SIVD-CI), 29 SIVD patients with cognitive unimpaired (SIVD-CU) and 32 normal controls (NC). Subsequently, the thicknesses and volumes of the gray matter regions that are closely related to memory function were automatically assessed using FreeSurfer software. Then, the volume, fractional anisotropy (FA), mean diffusivity (MD), amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values of white matter hyperintensity (WMH) region and normal-appearing white matter (NAWM) were obtained using SPM, DPARSF, and FSL software. Finally, the analysis of covariance, spearman correlation and mediation analysis were used to analyze data. Results Compared with NC group, patients in SIVD-CI and SIVD-CU groups showed significantly abnormal volume, FA, MD, ALFF, and ReHo values of WMH region and NAWM, as well as significantly decreased volume and thickness values of gray matter regions, mainly including thalamus, middle temporal gyrus and hippocampal subfields such as cornu ammonis (CA) 1. These abnormal changes were significantly correlated with decreased visual, auditory and working memory scores. Compared with the SIVD-CU group, the significant reductions of the left CA2/3, right amygdala, right parasubiculum and NAWM volumes and the significant increases of the MD values in the WMH region and NAWM were found in the SIVD-CI group. And the increased MD values were significantly related to working memory scores. Moreover, the decreased CA1 and thalamus volumes mediated the correlations between the abnormal microstructure indicators in WMH region and the decreased memory scores in the SIVD-CI group. Conclusion Patients with SIVD had structural and functional damages in both WMH and NAWM, along with specific gray matter atrophy, which were closely related to memory impairment, especially CA1 atrophy and thalamic atrophy. More importantly, the volumes of some temporomesial regions and the MD values of WMH regions and NAWM may be potentially helpful neuroimaging indicators for distinguishing between SIVD-CI and SIVD-CU patients.
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Affiliation(s)
- Jing Huang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Runtian Cheng
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaoshuang Liu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Li Chen
- Department of Radiology, The Affiliated Hospital of North Sichuan Medical College, Nanchong, China
| | - Tianyou Luo
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
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13
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van Dijk MT, Talati A, Kashyap P, Desai K, Kelsall NC, Gameroff MJ, Aw N, Abraham E, Cullen B, Cha J, Anacker C, Weissman MM, Posner J. Dentate Gyrus Microstructure Is Associated With Resilience After Exposure to Maternal Stress Across Two Human Cohorts. Biol Psychiatry 2024; 95:27-36. [PMID: 37393047 PMCID: PMC10755082 DOI: 10.1016/j.biopsych.2023.06.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND Maternal stress (MS) is a well-documented risk factor for impaired emotional development in offspring. Rodent models implicate the dentate gyrus (DG) of the hippocampus in the effects of MS on offspring depressive-like behaviors, but mechanisms in humans remain unclear. Here, we tested whether MS was associated with depressive symptoms and DG micro- and macrostructural alterations in offspring across 2 independent cohorts. METHODS We analyzed DG diffusion tensor imaging-derived mean diffusivity (DG-MD) and volume in a three-generation family risk for depression study (TGS; n = 69, mean age = 35.0 years) and in the Adolescent Brain Cognitive Development (ABCD) Study (n = 5196, mean age = 9.9 years) using generalized estimating equation models and mediation analysis. MS was assessed by the Parenting Stress Index (TGS) and a measure compiled from the Adult Response Survey from the ABCD Study. The Patient Health Questionnaire-9 and rumination scales (TGS) and the Child Behavior Checklist (ABCD Study) measured offspring depressive symptoms at follow-up. The Schedule for Affective Disorders and Schizophrenia-Lifetime interview was used to assign depression diagnoses. RESULTS Across cohorts, MS was associated with future symptoms and higher DG-MD (indicating disrupted microstructure) in offspring. Higher DG-MD was associated with higher symptom scores measured 5 years (in the TGS) and 1 year (in the ABCD Study) after magnetic resonance imaging. In the ABCD Study, DG-MD was increased in high-MS offspring who had depressive symptoms at follow-up, but not in offspring who remained resilient or whose mother had low MS. CONCLUSIONS Converging results across 2 independent samples extend previous rodent studies and suggest a role for the DG in exposure to MS and offspring depression.
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Affiliation(s)
- Milenna T van Dijk
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
| | - Ardesheer Talati
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
| | - Pratik Kashyap
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
| | - Karan Desai
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
| | - Nora C Kelsall
- Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
| | - Marc J Gameroff
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York
| | - Natalie Aw
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland
| | - Eyal Abraham
- Division of Child and Adolescent Psychiatry, New York State Psychiatric Institute, New York, New York
| | - Breda Cullen
- School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom
| | - Jiook Cha
- Department of Psychology, Seoul National University, Seoul, Republic of Korea
| | - Christoph Anacker
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York; Division of Systems Neuroscience, New York State Psychiatric Institute, New York, New York; Columbia University Institute for Developmental Sciences, New York, New York
| | - Myrna M Weissman
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York; Division of Translational Epidemiology, New York State Psychiatric Institute, New York, New York; Columbia University Institute for Developmental Sciences, New York, New York; Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York.
| | - Jonathan Posner
- Department of Psychiatry and Behavioral Sciences, Duke University, Durham, North Carolina
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Nasrullah N, Khorashad Sorouri B, Lundmark A, Seiger R, Savic I. Occupational stress is associated with sex and subregion specific modifications of the amygdala volumes. Stress 2023; 26:2247102. [PMID: 37771232 DOI: 10.1080/10253890.2023.2247102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 08/07/2023] [Indexed: 09/30/2023] Open
Abstract
Background: Despite the rapid increase in reports of exhaustion syndrome (ES) due to daily occupational stress, the mechanisms underlying ES are unknown. In the present study, we investigated whether occupational ES is associated with specific modifications of the subfields of the amygdala and hippocampus resembling those described in other chronic stress conditions. Special focus was paid to possible sex differences.Methods: As a follow up to our previous studies of occupational ES, we carried out MRI-based subfield segmentation of the hippocampus and amygdala volumes in 58 patients with occupational ES (22 males) and 65 age-matched controls (27 males) (age range 30-46 years).Results: There was a significant and bilateral enlargement of the lateral, basal and central nucleus of the amygdala in patients with ES (corrected for the total intracranial volume (ICV)). These differences were detected only in females. Higher values in the right central and right basal amygdala remained when the whole amygdala volume was used as reference, instead of the ICV. Notably, in female patients the volumes of these specific nuclei were positively correlated with the degree of perceived stress. No changes in the hippocampus subfields were detected in female or male patients.Conclusions: The findings underline that ES is a chronic stress condition, suggesting that not only extreme forms of stress, but also the everyday stress is associated with localized differences from controls in the amygdala. The absence of significant alterations among men with ES despite a similar degree of perceived stress supports the notion that women seem more susceptible to stress-related cerebral changes, and may explain the higher prevalence of ES among women.
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Affiliation(s)
- Nilab Nasrullah
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - B Khorashad Sorouri
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - Anton Lundmark
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - Rene Seiger
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
| | - Ivanka Savic
- Department of Women's and Children's Health, Karolinska Institute and Neurology Clinic, Karolinska University Hospital, Stockholm, Sweden
- Department of Neurology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, California, USA
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Wang H, Lei C, Zhao D, Gao L, Gao J. DeepHipp: accurate segmentation of hippocampus using 3D dense-block based on attention mechanism. BMC Med Imaging 2023; 23:158. [PMID: 37833644 PMCID: PMC10576314 DOI: 10.1186/s12880-023-01103-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 09/14/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND The hippocampus is a key area of the brain responsible for learning, memory, and other abilities. Accurately segmenting the hippocampus and precisely calculating the volume of the hippocampus is of great significance for predicting Alzheimer's disease and amnesia. Most of the segmentation algorithms currently involved are based on templates, such as the more popular FreeSufer. METHODS This study proposes Deephipp, a deep learning network based on a 3D dense block using an attention mechanism for accurate segmentation of the hippocampus. DeepHipp is based on the following novelties: (i) DeepHipp adopts powerful data augmentation schemes to enhance the segmentation ability. (ii) DeepHipp is designed to incorporate 3D dense-block to capture multiple-scale features of the hippocampus. (iii) DeepHipp creatively uses the attention mechanism in the field of hippocampal image segmentation, extracting useful hippocampus information in a massive feature map, and improving the accuracy and sensitivity of the model. CONCLUSIONS We describe the illustrative results and show extensive qualitative and quantitative comparisons with other methods. Our achievement demonstrates that the accuracy of DeepHipp can reach 83.63%, which is superior to most existing methods in terms of accuracy and efficiency of hippocampus segmentation. It is noticeable that deep learning can potentially lead to an effective segmentation of medical images.
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Affiliation(s)
- Han Wang
- Department of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Cai Lei
- Department of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
| | - Di Zhao
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Liwei Gao
- Department of Radiation Oncology China, Japan Friendship Hospital, Beijing, China
| | - Jingyang Gao
- Department of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
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16
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Liu D, Chen J, Ge H, Yan Z, Luo B, Hu X, Yang K, Liu Y, Xiao C, Zhang W, Liu H. Structural plasticity of the contralesional hippocampus and its subfields in patients with glioma. Eur Radiol 2023; 33:6107-6115. [PMID: 37036480 DOI: 10.1007/s00330-023-09582-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 11/14/2022] [Accepted: 02/17/2023] [Indexed: 04/11/2023]
Abstract
OBJECTIVES To characterize the structural plasticity of the contralesional hippocampus and its subfields in patients with unilateral glioma. METHODS 3D T1-weighted MRI images were collected from 55 patients with tumors infiltrating the left (HipL, n = 27) or right (HipR, n = 28) hippocampus, along with 30 age- and sex-matched healthy controls (HC). Gray matter volume differences of the contralesional hippocampal regions and three control regions (superior frontal gyrus, caudate nucleus, and superior occipital gyrus) were evaluated using voxel-based morphometry (VBM) analyses. Volumetric differences in the hippocampus and its subregional volume were measured using the FreeSurfer software. RESULTS Compared with HC, patients with unilateral hippocampal glioma exhibited significantly larger gray matter volume in the contralesional hippocampus and parahippocampal regions (cluster = 571 voxels for HipL; cluster 1 = 538 voxels and cluster 2 = 88 voxels for HipR; family-wise error corrected p < 0.05). No significant alterations were found in control regions. Volumetric analyses showed the same trend in the contralesional hippocampal subregions for both patient groups, including the CA1 head, CA3 head, hippocampus amygdala transition area (HATA), fimbria, and the granule cell molecular layer of the dentate gyrus head (GC-ML-DG head). Notably, the differences of the contralesional HATA (HipL: η2 = 0.418, corrected p = 0.002; HipR: η2 = 0.313, corrected p = 0.052) and fimbria (HipL: η2 = 0.450, corrected p < 0.001; HipR: η2 = 0.358, corrected p = 0.012) still held after the Bonferroni correction. CONCLUSIONS Our findings provide evidence for macrostructural plasticity of the contralateral hippocampus in patients with unilateral hippocampal glioma. Specifically, HATA and fimbria exhibit great potential in this process. KEY POINTS • Glioma infiltration of the hippocampal regions induces a significant increase in gray matter volume on the contralateral side. • Specifically, the HATA and fimbria regions exhibit favorable plastic potential in the process of lesion-induced structural remolding.
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Affiliation(s)
- Dongming Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Jiu Chen
- Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Fourth Clinical College of Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Institute of Brain Sciences, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Honglin Ge
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Zhen Yan
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Bei Luo
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Xinhua Hu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
- Institute of Brain Sciences, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Kun Yang
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Yong Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China
| | - Chaoyong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Wenbin Zhang
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China.
- Institute of Brain Sciences, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
| | - Hongyi Liu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, No.264, Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China.
- Institute of Brain Sciences, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
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Manmatharayan A, Kogan M, Matias C, Syed M, Shelley I, Chinni A, Kang K, Talekar K, Faro SH, Mohamed FB, Sharan A, Wu C, Alizadeh M. Automated subfield volumetric analysis of amygdala, hippocampus, and thalamic nuclei in mesial temporal lobe epilepsy. World Neurosurg X 2023; 19:100212. [PMID: 37304157 PMCID: PMC10250154 DOI: 10.1016/j.wnsx.2023.100212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 05/03/2023] [Accepted: 05/08/2023] [Indexed: 06/13/2023] Open
Abstract
Purpose Identifying relationships between clinical features and quantitative characteristics of the amygdala-hippocampal and thalamic subregions in mesial temporal lobe epilepsy (mTLE) may offer insights into pathophysiology and the basis for imaging prognostic markers of treatment outcome. Our aim was to ascertain different patterns of atrophy or hypertrophy in mesial temporal sclerosis (MTS) patients and their associations with post-surgical seizure outcomes. To assess this aim, this study is designed in 2 folds: (1) hemispheric changes within MTS group and (2) association with postsurgical seizure outcomes. Methods and materials 27 mTLE subjects with mesial temporal sclerosis (MTS) were scanned for conventional 3D T1w MPRAGE images and T2w scans. With respect to 12 months post-surgical seizure outcomes, 15 subjects reported being seizure free (SF) and 12 reported continued seizures. Quantitative automated segmentation and cortical parcellation were performed using Freesurfer. Automatic labeling and volume estimation of hippocampal subfields, amygdala, and thalamic subnuclei were also performed. The volume ratio (VR) for each label was computed and compared between (1) between contralateral and ipsilateral MTS using Wilcoxon rank-sum test and (2) SF and not seizure free (NSF) groups using linear regression analysis. False Discovery rate (FDR) with significant level of 0.05 were used in both analyses to correct for multiple comparisons. Results Amygdala: The medial nucleus of the amygdala was the most significantly reduced in patients with continued seizures when compared to patients who remained seizure free. Hippocampus: Comparison of ipsilateral and contralateral volumes with seizure outcomes showed volume loss was most evident in the mesial hippocampal regions such as CA4 and hippocampal fissure. Volume loss was also most explicit in the presubiculum body in patients with continued seizures at the time of their follow-up. Ipsilateral MTS compared to contralateral MTS analysis showed the heads of the ipsilateral subiculum, presubiculum, parasubiculum, dentate gyrus, CA4, and CA3 were more significantly affected than their respective bodies. Volume loss was most noted in mesial hippocampal regions. Thalamus: VPL and PuL were the most significantly reduced thalamic nuclei in NSF patients. In all statistically significant areas, volume reduction was observed in the NSF group. No significant volume reductions were noted in the thalamus and amygdala when comparing ipsilateral to contralateral sides in mTLE subjects. Conclusions Varying degrees of volume loss were demonstrated in the hippocampus, thalamus, and amygdala subregions of MTS, especially between patients who remained seizure-free and those who did not. The results obtained can be used to further understand mTLE pathophysiology. Clinical relevance/application In the future, we hope these results can be used to deepen the understanding of mTLE pathophysiology, leading to improved patient outcomes and treatments.
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Affiliation(s)
- Arichena Manmatharayan
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Michael Kogan
- Department of Neurosurgery, University of New Mexico, Albuquerque, NM, 87131-0001, USA
| | - Caio Matias
- Department of Neurosurgery, Thomas Jefferson University, 909 Walnut Street, 2nd Floor, Philadelphia, PA, 19107, USA
| | - Mashaal Syed
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - India Shelley
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Amar Chinni
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Kichang Kang
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Kiran Talekar
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Scott H. Faro
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Feroze B. Mohamed
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Ashwini Sharan
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Chengyuan Wu
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
| | - Mahdi Alizadeh
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St, Philadelphia, PA, 19107, USA
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18
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Kahhale I, Buser NJ, Madan CR, Hanson JL. Quantifying numerical and spatial reliability of hippocampal and amygdala subdivisions in FreeSurfer. Brain Inform 2023; 10:9. [PMID: 37029203 PMCID: PMC10082143 DOI: 10.1186/s40708-023-00189-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 03/24/2023] [Indexed: 04/09/2023] Open
Abstract
On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had "excellent" numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability.
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19
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Relations of hippocampal subfields atrophy patterns with memory and biochemical changes in end stage renal disease. Sci Rep 2023; 13:2982. [PMID: 36804419 PMCID: PMC9941083 DOI: 10.1038/s41598-023-29083-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/30/2023] [Indexed: 02/22/2023] Open
Abstract
End-stage renal disease (ESRD) results in hippocampal volume reduction, but the hippocampal subfields atrophy patterns cannot be identified. We explored the volumes and asymmetry of the hippocampal subfields and their relationships with memory function and biochemical changes. Hippocampal global and subfields volumes were derived from 33 ESRD patients and 46 healthy controls (HCs) from structural MRI. We compared the volume and asymmetric index of each subfield, with receiver operating characteristic curve analysis to evaluate the differentiation between ESRD and HCs. The relations of hippocampal subfield volumes with memory performance and biochemical data were investigated in ESRD group. ESRD patients had smaller hippocampal subfield volumes, mainly in the left CA1 body, left fimbria, right molecular layer head, right molecular layer body and right HATA. The right molecular layer body exhibited the highest accuracy for differentiating ESRD from HCs, with a sensitivity of 80.43% and specificity of 72.73%. Worse learning process (r = 0.414, p = 0.032), immediate recall (r = 0.396, p = 0.041) and delayed recall (r = 0.482, p = 0.011) was associated with left fimbria atrophy. The left fimbria volume was positively correlated with Hb (r = 0.388, p = 0.05); the left CA1 body volume was negatively correlated with Urea (r = - 0.469, p = 0.016). ESRD patients showed global and hippocampal subfields atrophy. Left fimbria atrophy was related to memory function. Anemia and Urea level may be associated with the atrophy of left fimbria and CA1 body, respectively.
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20
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Fel JT, Ellis CT, Turk-Browne NB. Automated and manual segmentation of the hippocampus in human infants. Dev Cogn Neurosci 2023; 60:101203. [PMID: 36791555 PMCID: PMC9957787 DOI: 10.1016/j.dcn.2023.101203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 01/25/2023] [Accepted: 01/25/2023] [Indexed: 01/30/2023] Open
Abstract
The hippocampus, critical for learning and memory, undergoes substantial changes early in life. Investigating the developmental trajectory of hippocampal structure and function requires an accurate method for segmenting this region from anatomical MRI scans. Although manual segmentation is regarded as the "gold standard" approach, it is laborious and subjective. This has fueled the pursuit of automated segmentation methods in adults. However, little is known about the reliability of these automated protocols in infants, particularly when anatomical scan quality is degraded by head motion or the use of shorter and quieter infant-friendly sequences. During a task-based fMRI protocol, we collected quiet T1-weighted anatomical scans from 42 sessions with awake infants aged 4-23 months. Two expert tracers first segmented the hippocampus in both hemispheres manually. The resulting inter-rater reliability (IRR) was only moderate, reflecting the difficulty of infant segmentation. We then used four protocols to predict these manual segmentations: average adult template, average infant template, FreeSurfer software, and Automated Segmentation of Hippocampal Subfields (ASHS) software. ASHS generated the most reliable hippocampal segmentations in infants, exceeding the manual IRR of experts. Automated methods thus provide robust hippocampal segmentations of noisy T1-weighted infant scans, opening new possibilities for interrogating early hippocampal development.
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Affiliation(s)
- J T Fel
- Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - C T Ellis
- Department of Psychology, Stanford University, Stanford, CA 94305, USA
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT 06511, USA; Wu Tsai Institute, Yale University, New Haven, CT 06511, USA.
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21
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Categorical and Dimensional Deficits in Hippocampal Subfields Among Schizophrenia, Obsessive-Compulsive Disorder, Bipolar Disorder, and Major Depressive Disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:91-101. [PMID: 35803485 DOI: 10.1016/j.bpsc.2022.06.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Revised: 06/19/2022] [Accepted: 06/22/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND The hippocampus is a core region of interest for all major mental disorders, and its subfields implement distinctive functions. It is unclear whether the mental disorders exhibit common patterns of hippocampal impairments, and we lack knowledge on whether and how hippocampal subfields represent deficit spectra across mental disorders. METHODS Using brain images of 1123 individuals scanned on a single magnetic resonance imaging scanner, we examined the commonality, specificity, and symptom associations of the volume of hippocampal subfields across patients with schizophrenia, patients with obsessive-compulsive disorder, patients with bipolar disorder, patients with major depressive disorder, and healthy control subjects. We further performed a transdiagnostic analysis of the individual variability of the volume of hippocampal subfields to reflect cross-disease gradients in the hippocampus. RESULTS We found common and disease-specific abnormalities in a few hippocampal fields and identified 2 reliable transdiagnostic factors in the hippocampal subfields, each reflecting a spectrum of mental disorders. The plane spanned by the 2 most reliable factors provided a clearer view of hippocampal volume abnormality spectra among the major mental disorders. In addition, functional and genetic enrichment analyses supported the different roles of the 2 hippocampal factors in mental disorders. CONCLUSIONS The volume of hippocampal subfields reflected some commonality and specificity among the 3 major mental disorders. We propose a new pathophysiological dimensional view of the hippocampus, reflecting at least 2 spectra of mental disorders, suggesting multivariate links among the diseases. This work highlights the value of the complementary categorical and dimensional views of the hippocampal deficits in mental disorders.
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22
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Ayoub LJ, Zhu J, Lee SJ, Mugisha N, Patel K, Duerden EG, Stinson J, Verriotis M, Noel M, Kong D, Moayedi M, McAndrews MP. Age-related effects on the anterior and posterior hippocampal volumes in 6-21 year olds: A model selection approach. Hippocampus 2023; 33:37-46. [PMID: 36519826 DOI: 10.1002/hipo.23487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 11/24/2022] [Accepted: 11/28/2022] [Indexed: 12/23/2022]
Abstract
Although recent studies support significant differences in intrinsic structure, function, and connectivity along the longitudinal axis of the hippocampus, few studies have investigated the normative development of this dimension. In addition, factors known to influence hippocampal structure, such as sex or puberty, have yet to be characterized when assessing age-related effects on its subregions. This study addresses this gap by investigating the relationship of the anterior (antHC) and posterior (postHC) hippocampus volumes with age, and how these are moderated by sex or puberty, in structural magnetic resonance imaging scans from 183 typically developing participants aged 6-21 years. Based on previous literature, we first anticipated that non-linear models would best represent the relationship between age and the antHC and postHC volumes. We found that age-related effects are region-specific, such that the antHC volume remains stable with increasing age, while the postHC shows a cubic function characterized by overall volume increase with age but a slower rate during adolescence. Second, we hypothesized that models, which include biological sex or pubertal status would best describe these relationships. Contrary to expectation, models comprising either biological sex or pubertal status did not significantly improve model performance. Further longitudinal research is needed to evaluate their effects on the antHC and postHC development.
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Affiliation(s)
- Lizbeth J Ayoub
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada.,University of Toronto Centre for the Study of Pain, Toronto, Ontario, Canada.,Division of Clinical and Computational Neuroscience, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Junhao Zhu
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Steven J Lee
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
| | - Nancy Mugisha
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
| | - Kyle Patel
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - Emma G Duerden
- Applied Psychology, Faculty of Education, Western University, London, Ontario, Canada
| | - Jennifer Stinson
- Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Madeleine Verriotis
- Pain Research, Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, UK.,Department of Anaesthesia and Pain Management, Great Ormond Street Hospital NHS Foundation Trust, London, UK
| | - Melanie Noel
- Department of Psychology, University of Calgary, Calgary, Alberta, Canada.,Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada.,Hotchkiss Brain Institute, Calgary, Alberta, Canada
| | - Dehan Kong
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Massieh Moayedi
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada.,University of Toronto Centre for the Study of Pain, Toronto, Ontario, Canada.,Division of Clinical and Computational Neuroscience, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada.,Department of Dentistry, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Mary Pat McAndrews
- Division of Clinical and Computational Neuroscience, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada.,Department of Psychology, University of Toronto, Toronto, Ontario, Canada
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23
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Dick AS, Ralph Y, Farrant K, Reeb-Sutherland B, Pruden S, Mattfeld AT. Volumetric development of hippocampal subfields and hippocampal white matter connectivity: Relationship with episodic memory. Dev Psychobiol 2022; 64:e22333. [PMID: 36426794 DOI: 10.1002/dev.22333] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 08/22/2022] [Accepted: 09/02/2022] [Indexed: 01/27/2023]
Abstract
The hippocampus is a complex structure composed of distinct subfields. It has been central to understanding neural foundations of episodic memory. In the current cross-sectional study, using a large sample of 830, 3- to 21-year-olds from a unique, publicly available dataset we examined the following questions: (1) Is there elevated grey matter volume of the hippocampus and subfields in late compared to early development? (2) How does hippocampal volume compare with the rest of the cerebral cortex at different developmental stages? and (3) What is the relation between hippocampal volume and connectivity with episodic memory performance? We found hippocampal subfield volumes exhibited a nonlinear relation with age and showed a lag in volumetric change with age when compared to adjacent cortical regions (e.g., entorhinal cortex). We also observed a significant reduction in cortical volume across older cohorts, while hippocampal volume showed the opposite pattern. In addition to age-related differences in gray matter volume, dentate gyrus/cornu ammonis 3 volume was significantly related to episodic memory. We did not, however, find any associations with episodic memory performance and connectivity through the uncinate fasciculus, fornix, or cingulum. The results are discussed in the context of current research and theories of hippocampal development and its relation to episodic memory.
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Affiliation(s)
- Anthony Steven Dick
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Yvonne Ralph
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Kristafor Farrant
- Department of Psychology, Florida International University, Miami, Florida, USA
| | | | - Shannon Pruden
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Aaron T Mattfeld
- Department of Psychology, Florida International University, Miami, Florida, USA
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24
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Gotlib IH, Miller JG, Borchers LR, Coury SM, Costello LA, Garcia JM, Ho TC. Effects of the COVID-19 Pandemic on Mental Health and Brain Maturation in Adolescents: Implications for Analyzing Longitudinal Data. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2022; 3:S2667-1743(22)00142-2. [PMID: 36471743 PMCID: PMC9713854 DOI: 10.1016/j.bpsgos.2022.11.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 11/05/2022] [Accepted: 11/07/2022] [Indexed: 12/03/2022] Open
Abstract
Background The COVID-19 pandemic has caused significant stress and disruption for young people, likely leading to alterations in their mental health and neurodevelopment. In this context, it is not clear whether youth who lived through the pandemic and its shutdowns are comparable psychobiologically to their age- and sex-matched peers assessed before the pandemic. This question is particularly important for researchers who are analyzing longitudinal data that span the pandemic. Methods In this study we compared carefully matched youth assessed before the pandemic (n=81) and after the pandemic-related shutdowns ended (n=82). Results We found that youth assessed after the pandemic shutdowns had more severe internalizing mental health problems, reduced cortical thickness, larger hippocampal and amygdala volume, and more advanced brain age. Conclusions Thus, not only does the COVID-19 pandemic appear to have led to poorer mental health and accelerated brain aging in adolescents, but it also poses significant challenges to researchers analyzing data from longitudinal studies of normative development that were interrupted by the pandemic.
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Affiliation(s)
- Ian H. Gotlib
- Department of Psychology, Stanford University, Stanford, California
| | - Jonas G. Miller
- Department of Psychology, Stanford University, Stanford, California
| | | | - Sache M. Coury
- Department of Psychology, Stanford University, Stanford, California
| | | | - Jordan M. Garcia
- Department of Psychology, Stanford University, Stanford, California
| | - Tiffany C. Ho
- Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California
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25
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Fu X, Zhang Z, Zhou Y, Chen Q, Yang LZ, Li H. The Split-Half Reliability and Construct Validity of the Virtual Reality-Based Path Integration Task in the Healthy Population. Brain Sci 2022; 12:brainsci12121635. [PMID: 36552095 PMCID: PMC9775933 DOI: 10.3390/brainsci12121635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/21/2022] [Accepted: 11/26/2022] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVE The virtual reality (VR)-based path integration task shows substantial promise in predicting dementia risk. However, the reliability and validity in healthy populations need further exploration. The present study investigates the relationship between task indicators and brain structures in a healthy population using a VR-based navigation task, particularly the entorhinal cortex (EC) and hippocampus. METHODS Sixty healthy adults were randomly recruited to perform a VR-based path integration task, the digit span task (DST), and an MRI scan. The indicators of the VR-based path integration task were calculated, including the absolute distance error (ADE), degree of angle deviation (DAD), degree of path deviation (DPD), and return time (Time). The reliability of the above indicators was then estimated using the split-half method and Cronbach's alpha. Correlation and regression analyses were then performed to examine the associations between these indicators and age, general cognitive ability (DST), and brain structural measures. RESULTS ADE, DAD, and DPD showed reasonable split-half reliability estimates (0.84, 0.81, and 0.72) and nice Cronbach's alpha estimates (0.90, 0.86, and 0.96). All indicators correlated with age and DST. ADE and DAD were sensitive predictors of hippocampal volume, and return time was a predictor of EC thickness. CONCLUSION Our findings demonstrate that the VR-based path integration task exhibits good reliability and validity in the healthy population. The task indicators are age-sensitive, can capture working memory capacity, and are closely related to the integrity of individual EC and hippocampal structures.
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Affiliation(s)
- Xiao Fu
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China
| | - Zhenglin Zhang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- University of Science and Technology of China, Hefei 230026, China
| | - Yanfei Zhou
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China
| | - Qi Chen
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei 230031, China
| | - Li-Zhuang Yang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
- Correspondence: may
| | - Hai Li
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
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26
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Qi W, Marx J, Zingman M, Li Y, Petkova E, Blessing E, Ardekani B, Sakalli Kani A, Cather C, Freudenreich O, Holt D, Zhao J, Wang J, Goff DC. Hippocampal Subfield Volumes Predict Disengagement from Maintenance Treatment in First Episode Schizophrenia. Schizophr Bull 2022; 49:34-42. [PMID: 36370124 PMCID: PMC9810017 DOI: 10.1093/schbul/sbac043] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVES Disengagement from treatment is common in first episode schizophrenia (FES) and is associated with poor outcomes. Our aim was to determine whether hippocampal subfield volumes predict disengagement during maintenance treatment of FES. METHODS FES patients were recruited from sites in Boston, New York, Shanghai, and Changsha. After stabilization on antipsychotic medication, participants were randomized to add-on citalopram or placebo and followed for 12 months. Demographic, clinical and cognitive factors at baseline were compared between completers and disengagers in addition to volumes of hippocampal subfields. RESULTS Baseline data were available for 95 randomized participants. Disengagers (n = 38, 40%) differed from completers (n = 57, 60%) by race (more likely Black; less likely Asian) and in more alcohol use, parkinsonism, negative symptoms and more impairment in visual learning and working memory. Bilateral dentate gyrus (DG), CA1, CA2/3 and whole hippocampal volumes were significantly smaller in disengagers compared to completers. When all the eight volumes were entered into the model simultaneously, only left DG volume significantly predicted disengagement status and remained significant after adjusting for age, sex, race, intracranial volume, antipsychotic dose, duration of untreated psychosis, citalopram status, alcohol status, and smoking status (P < .01). Left DG volume predicted disengagement with 57% sensitivity and 83% specificity. CONCLUSIONS Smaller left DG was significantly associated with disengagement status over 12 months of maintenance treatment in patients with FES participating in a randomized clinical trial. If replicated, these findings may provide a biomarker to identify patients at risk for disengagement and a potential target for interventions.
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Affiliation(s)
| | | | - Michael Zingman
- Department of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA
| | - Yi Li
- Department of Population Health, Division of Biostatistics, NYU School of Medicine, 180 Madison Avenue, New York, NY, USA
| | - Eva Petkova
- Department of Population Health, Division of Biostatistics, NYU School of Medicine, 180 Madison Avenue, New York, NY, USA,Nathan Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY, USA
| | - Esther Blessing
- Department of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA
| | - Babak Ardekani
- Department of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA,Nathan Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY, USA
| | - Ayse Sakalli Kani
- Department of Psychiatry, NYU Langone Health, 1 Park Avenue, New York, NY, USA,4New York State Psychiatric Institute, Columbia University Medical Center, 601 West 168th St., New York, NY, USA
| | - Corinne Cather
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA
| | - Oliver Freudenreich
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA
| | - Daphne Holt
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA, USA
| | - Jingping Zhao
- National Clinical Research Center for Mental Disorders, Mental Health Institute, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Donald C Goff
- To whom correspondence should be addressed; Psychiatry Department, NYU Langone Health, One Park Ave, New York, NY 10016, USA; tel: 646-754-4843, e-mail:
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Devika K, Mahapatra D, Subramanian R, Ramana Murthy Oruganti V. Dense Attentive GAN-based One-Class Model for Detection of Autism and ADHD. JOURNAL OF KING SAUD UNIVERSITY - COMPUTER AND INFORMATION SCIENCES 2022. [DOI: 10.1016/j.jksuci.2022.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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28
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Smith ET, Skolasinska P, Qin S, Sun A, Fishwick P, Park DC, Basak C. Cognitive and structural predictors of novel task learning, and contextual predictors of time series of daily task performance during the learning period. Front Aging Neurosci 2022; 14:936528. [PMID: 36212037 PMCID: PMC9540228 DOI: 10.3389/fnagi.2022.936528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 08/29/2022] [Indexed: 11/21/2022] Open
Abstract
Investigation into methods of addressing cognitive loss exhibited later in life is of paramount importance to the field of cognitive aging. The field continues to make significant strides in designing efficacious cognitive interventions to mitigate cognitive decline, and the very act of learning a demanding task has been implicated as a potential mechanism of augmenting cognition in both the field of cognitive intervention and studies of cognitive reserve. The present study examines individual-level predictors of complex skill learning and day-to-day performance on a gamified working memory updating task, the BirdWatch Game, intended for use as a cognitive intervention tool in older adults. A measure of verbal episodic memory and the volume of a brain region involved in verbal working memory and cognitive control (the left inferior frontal gyrus) were identified as predictors of learning rates on the BirdWatch Game. These two neuro-cognitive measures were more predictive of learning when considered in conjunction than when considered separately, indicating a complementary effect. Additionally, auto-regressive time series forecasting analyses were able to identify meaningful daily predictors (that is, mood, stress, busyness, and hours of sleep) of performance-over-time on the BirdWatch Game in 50% of cases, with the specific pattern of contextual influences on performance being highly idiosyncratic between participants. These results highlight the specific contribution of language processing and cognitive control abilities to the learning of the novel task examined in this study, as well as the variability of subject-level influences on task performance during task learning.
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Affiliation(s)
- Evan T. Smith
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
- Department of Psychology, University of Texas at Dallas, Richardson, TX, United States
| | - Paulina Skolasinska
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
- Department of Psychology, University of Texas at Dallas, Richardson, TX, United States
| | - Shuo Qin
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
| | - Andrew Sun
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
| | - Paul Fishwick
- School of Arts and Technology, University of Texas at Dallas, Richardson, TX, United States
| | - Denise C. Park
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
- Department of Psychology, University of Texas at Dallas, Richardson, TX, United States
| | - Chandramallika Basak
- Center for Vital Longevity, University of Texas at Dallas, Dallas, TX, United States
- Department of Psychology, University of Texas at Dallas, Richardson, TX, United States
- *Correspondence: Chandramallika Basak
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Liu G, Li Y, Xu Y, Li W. Type 2 diabetes is associated with increased risk of dementia, but not mild cognitive impairment: a cross-sectional study among the elderly in Chinese communities. Front Aging Neurosci 2022; 14:1004954. [PMID: 36185492 PMCID: PMC9524142 DOI: 10.3389/fnagi.2022.1004954] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Previous studies have confirmed that diabetes is associated with cognitive impairment, but there is little data on this among older Chinese. Methods: This study included 192 dementia patients, 610 patients with mild cognitive impairment (MCI), and 2,218 normal controls. Their general demographic information (such as gender, age, education, etc.), disease-related information (hypertension), and diabetes information (such as whether you have diabetes, course of the disease, etc) were collected by standardized questionnaires. The mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess their overall cognitive function, Moreover, 84 healthy, randomly selected older adults also underwent brain MRI scans at the same time, and the target brain regions included the hippocampus, the third, fourth, and fifth ventricles. Results: The proportion of type 2 diabetes was significantly higher in the dementia group (25.5%) than that in the normal elderly group (15.6%) and the MCI group (17.7%). By using stepwise multiple logistics regression analysis, we found that type 2 diabetes was associated with dementia (p = 0.005*, OR = 1.805, 95%CI: 1.199–2.761), but not with MCI (p > 0.05). The volume of the fourth ventricle of the healthy elderly with diabetes was significantly larger than that of the healthy elderly without diabetes (p < 0.05), but there was no statistical difference (p > 0.05) in the volume of the hippocampus, the third ventricle, and the fifth ventricle between the two groups. However, we did not find an association between the fourth ventricle and cognitive scores (MMSE and MoCA). Conclusions: In conclusion, type 2 diabetes in elderly Chinese people is associated with dementia, but not MCI. Type 2 diabetes may impair cognitive function by affecting the volume of the fourth ventricle. However, larger longitudinal follow-up studies are needed to confirm these conclusions.
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Affiliation(s)
- Guojun Liu
- Department of Rehabilitation Medicine, The Third People’s Hospital of Lanzhou, Lanzhou, China
| | - Yong Li
- Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, China
- Department of Nephrology, Affiliated Hospital of Hubei University of Chinese Medicine, Wuhan, China
- Hubei Provincial Academy of Traditional Chinese Medicine, Wuhan, China
| | - Yuzhen Xu
- Department of Rehabilitation, The Second Affiliated Hospital of Shandong First Medical University, Taian, China
- *Correspondence: Wei Li Yuzhen Xu
| | - Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
- *Correspondence: Wei Li Yuzhen Xu
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Choice of Voxel-based Morphometry processing pipeline drives variability in the location of neuroanatomical brain markers. Commun Biol 2022; 5:913. [PMID: 36068295 PMCID: PMC9448776 DOI: 10.1038/s42003-022-03880-1] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 08/23/2022] [Indexed: 11/12/2022] Open
Abstract
Fundamental and clinical neuroscience has benefited tremendously from the development of automated computational analyses. In excess of 600 human neuroimaging papers using Voxel-based Morphometry (VBM) are now published every year and a number of different automated processing pipelines are used, although it remains to be systematically assessed whether they come up with the same answers. Here we examined variability between four commonly used VBM pipelines in two large brain structural datasets. Spatial similarity and between-pipeline reproducibility of the processed gray matter brain maps were generally low between pipelines. Examination of sex-differences and age-related changes revealed considerable differences between the pipelines in terms of the specific regions identified. Machine learning-based multivariate analyses allowed accurate predictions of sex and age, however accuracy differed between pipelines. Our findings suggest that the choice of pipeline alone leads to considerable variability in brain structural markers which poses a serious challenge for reproducibility and interpretation. Four common processing pipelines tested on two Voxel-based Morphometry (VBM) datasets yield considerable variations in results, raising issues on the interpretability and robustness of VBM results.
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31
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Castegnaro A, Howett D, Li A, Harding E, Chan D, Burgess N, King J. Assessing mild cognitive impairment using object-location memory in immersive virtual environments. Hippocampus 2022; 32:660-678. [PMID: 35916343 PMCID: PMC9543035 DOI: 10.1002/hipo.23458] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/24/2022] [Accepted: 07/16/2022] [Indexed: 11/12/2022]
Abstract
Pathological changes in the medial temporal lobe (MTL) are found in the early stages of Alzheimer's disease (AD) and aging. The earliest pathological accumulation of tau colocalizes with the areas of the MTL involved in object processing as part of a wider anterolateral network. Here, we sought to assess the diagnostic potential of memory for object locations in iVR environments in individuals at high risk of AD dementia (amnestic mild cognitive impairment [aMCI] n = 23) as compared to age-related cognitive decline. Consistent with our primary hypothesis that early AD would be associated with impaired object location, aMCI patients exhibited impaired spatial feature binding. Compared to both older (n = 24) and younger (n = 53) controls, aMCI patients, recalled object locations with significantly less accuracy (p < .001), with a trend toward an impaired identification of the object's correct context (p = .05). Importantly, these findings were not explained by deficits in object recognition (p = .6). These deficits differentiated aMCI from controls with greater accuracy (AUC = 0.89) than the standard neuropsychological tests. Within the aMCI group, 16 had CSF biomarkers indicative of their likely AD status (MCI+ n = 9 vs. MCI- n = 7). MCI+ showed lower accuracy in the object-context association than MCI- (p = .03) suggesting a selective deficit in object-context binding postulated to be associated with anterior-temporal areas. MRI volumetric analysis across healthy older participants and aMCI revealed that test performance positively correlates with lateral entorhinal cortex volumes (p < .05) and hippocampus volumes (p < .01), consistent with their hypothesized role in binding contextual and spatial information with object identity. Our results indicate that tests relying on the anterolateral object processing stream, and in particular requiring successful binding of an object with spatial information, may aid detection of pre-dementia AD due to the underlying early spread of tau pathology.
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Affiliation(s)
- Andrea Castegnaro
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - David Howett
- School of Psychological ScienceUniversity of BristolBristolUK
| | - Adrienne Li
- Department of PsychologyYork UniversityTorontoOntarioCanada
| | - Elizabeth Harding
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Dennis Chan
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Neil Burgess
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - John King
- Department of Clinical, Educational and Health PsychologyUniversity College LondonLondonUK
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Li W, Li Y, Chen Y, Yue L, Xiao S. Association between physical exercise, executive function, and cerebellar cortex: A cross-sectional study among the elderly in Chinese communities. Front Aging Neurosci 2022; 14:975329. [PMID: 36081892 PMCID: PMC9445432 DOI: 10.3389/fnagi.2022.975329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 08/03/2022] [Indexed: 11/25/2022] Open
Abstract
Background Previous studies have confirmed that physical exercise may be beneficial for brain health, but there is little data on this among older Chinese. Objective The purpose of this study was to explore the relationship between physical exercise and cognitive impairment, and to explore the possible mechanism by which physical exercise prevents cognitive decline. Materials and methods 192 older adults with dementia, 610 older adults with mild cognitive impairment (MCI), and 2,218 healthy older adults were included in the study. Through standardized questionnaires, we obtained their general demographic information (such as gender, age, education, etc.), disease-related information (hypertension and diabetes) and physical exercise information (such as whether they did physical exercise and the frequency of physical exercise, etc.). The mini-mental state examination (MMSE) and Montreal Cognitive Assessment (MoCA) were used to assess their overall cognitive function, while the Wechsler block diagram was used to assess their executive function. Moreover, 164 healthy, randomly selected older adults also underwent brain MRI scans at the same time, and the target brain regions included hippocampus, gray matter, and cerebellar cortex. Results By using stepwise multiple logistics regression analysis, we found that physical exercise was associated with both MCI (p = 0.001*, OR = 0.689, 95%CI: 0.553–0.859) and dementia (p < 0.001*, OR = 0.501, 95%CI: 0.354–0.709), independent of gender, age, education, and other factors. The results of ROC curve showed that the area under the curve of physical exercise in predicting MCI and dementia was 0.551 (p < 0.001*, 95%CI: 0.525–0.577) and 0.628 (p = 0.001*, 95%CI: 0.585–0.671), respectively. The results of partial correlation analysis showed that physical exercise was associated with left cerebellar cortex (r = 0.163, p = 0.023), right cerebellar cortex (r = 0.175, p = 0.015) and Wechsler block diagram score (r = 0.235, p = 0.011). Moreover, the results of linear regression analysis mediation model showed that physical exercise may affect Wechsler block diagram score through influencing the thickness of right cerebellum cortex, and the latter may play a partial mediation effect (indirect B = 0.001, p = 0.045). Conclusion Physical exercise might be a protective factor for mild cognitive impairment and dementia among the Chinese elderly, and there might be an association among physical exercise, executive function, and the thickness of the cerebellar cortex.
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Affiliation(s)
- Wei Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
| | - Yong Li
- Department of Nephrology, Hubei Provincial Hospital of Traditional Chinese Medicine, Wuhan, China
- Department of Nephrology, Affiliated Hospital of Hubei University of Chinese Medicine, Wuhan, China
- Hubei Provincial Academy of Traditional Chinese Medicine, Wuhan, China
| | - Yaopian Chen
- Department of Sleep Medicine, Wenzhou Seventh People’s Hospital, Wenzhou, China
- *Correspondence: Yaopian Chen,
| | - Ling Yue
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
- Ling Yue,
| | - Shifu Xiao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Alzheimer’s Disease and Related Disorders Center, Shanghai Jiao Tong University, Shanghai, China
- Shifu Xiao,
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Ciolac D, Gonzalez-Escamilla G, Winter Y, Melzer N, Luessi F, Radetz A, Fleischer V, Groppa SA, Kirsch M, Bittner S, Zipp F, Muthuraman M, Meuth SG, Grothe M, Groppa S. Altered grey matter integrity and network vulnerability relate to epilepsy occurrence in patients with multiple sclerosis. Eur J Neurol 2022; 29:2309-2320. [PMID: 35582936 DOI: 10.1111/ene.15405] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 03/22/2022] [Accepted: 05/13/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND To investigate the relevance of compartmentalized grey matter (GM) pathology and network reorganization in MS patients with concomitant epilepsy. METHODS From 3T MRI scans of 30 MS patients with epilepsy (MSE; age 41±15 years, 21 females, disease duration 8±6 years, median Expanded Disability Status Scale (EDSS) 3), 60 MS patients without epilepsy (MS; age 41±12 years, 35 females, disease duration 6±4 years, EDSS 2), and 60 healthy subjects (HS; age 40±13 years, 27 females) regional volumes of GM lesions and of cortical, subcortical, and hippocampal structures were quantified. Network topology and vulnerability were modeled within the graph theoretical framework. The receiver operating characteristic (ROC) analysis was applied to assess the accuracy of GM pathology measures to discriminate between MSE and MS patients. RESULTS Higher lesion volumes within the hippocampus, mesiotemporal cortex, and amygdala were detected in MSE compared to MS (all p<0.05). MSE displayed lower cortical volumes mainly in temporal and parietal areas compared to MS and HS (all p<0.05). Lower volumes of hippocampal tail and presubiculum were identified in both MSE and MS patients compared to HS (all p<0.05). Network topology in MSE was characterized by higher transitivity and assortativity, and higher vulnerability compared to MS and HS (all p<0.05). Hippocampal lesion volume yielded the highest accuracy (area under the ROC curve 0.80 [0.67-0.91]) in discriminating between MSE and MS patients. CONCLUSIONS High lesion load, altered integrity of mesiotemporal GM structures, and network reorganization are associated with a greater propensity of epilepsy occurrence in MS.
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Affiliation(s)
- Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.,Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova.,Department of Neurology, Institute of Emergency Medicine, Chisinau, Republic of Moldova
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Yaroslav Winter
- Mainz Comprehensive Epilepsy and Sleep Medicine Center, Department of Neurology, Johannes Gutenberg University Mainz, Mainz, Germany.,Department of Neurology, Philipps-University, Marburg, Germany
| | - Nico Melzer
- Department of Neurology, Heinrich Heine University, Düsseldorf, Germany
| | - Felix Luessi
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Angela Radetz
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Stanislav A Groppa
- Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau, Republic of Moldova.,Department of Neurology, Institute of Emergency Medicine, Chisinau, Republic of Moldova
| | - Michael Kirsch
- Institute for Diagnostic Radiology and Neuroradiology, University Medicine of Greifswald, Germany
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Sven G Meuth
- Department of Neurology, Heinrich Heine University, Düsseldorf, Germany
| | - Matthias Grothe
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
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Buch S, Chen Y, Jella P, Ge Y, Haacke EM. Vascular mapping of the human hippocampus using Ferumoxytol-enhanced MRI. Neuroimage 2022; 250:118957. [PMID: 35122968 PMCID: PMC9484293 DOI: 10.1016/j.neuroimage.2022.118957] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2021] [Revised: 12/09/2021] [Accepted: 01/30/2022] [Indexed: 11/21/2022] Open
Abstract
The hippocampus is a small but complex grey matter structure that plays an important role in spatial and episodic memory and can be affected by a wide range of pathologies including vascular abnormalities. In this work, we introduce the use of Ferumoxytol, an ultra-small superparamagnetic iron oxide (USPIO) agent, to induce susceptibility in the arteries (as well as increase the susceptibility in the veins) to map the hippocampal micro-vasculature and to evaluate the quantitative change in tissue fractional vascular density (FVD), in each of its subfields. A total of 39 healthy subjects (aged 35.4 ± 14.2 years, from 18 to 81 years old) were scanned with a high-resolution (0.22×0.44×1 mm3) dual-echo SWI sequence acquired at four time points during a gradual increase in Ferumoxytol dose (final dose = 4 mg/kg). The volumes of each subfield were obtained automatically from the pre-contrast T1-weighted data. The dynamically acquired SWI data were co-registered and adaptively combined to reduce the blooming artifacts from large vessels, preserving the contrast from smaller vessels. The resultant SWI data were used to segment the hippocampal vasculature and to measure the FVD ((volume occupied by vessels)/(total volume)) for each subfield. The hippocampal fissure, along with the fimbria, granular cell layer of the dentate gyrus and cornu ammonis layers (except for CA1), showed higher micro-vascular FVD than the other parts of hippocampus. The CA1 region exhibited a significant correlation with age (R = -0.37, p < 0.05). demonstrating an overall loss of hippocampal vascularity in the normal aging process. Moreover, the vascular density reduction was more prominent than the age correlation with the volume reduction (R = -0.1, p > 0.05) of the CA1 subfield, which would suggest that vascular degeneration may precede tissue atrophy.
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Affiliation(s)
- Sagar Buch
- Department of Radiology, Wayne State University, Detroit, MI, USA
| | - Yongsheng Chen
- Department of Neurology, Wayne State University, Detroit, MI, USA
| | - Pavan Jella
- Department of Radiology, Wayne State University, Detroit, MI, USA
| | - Yulin Ge
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
| | - E Mark Haacke
- Department of Radiology, Wayne State University, Detroit, MI, USA
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Zahid U, Hedges EP, Dimitrov M, Murray RM, Barker GJ, Kempton MJ. Impact of physiological factors on longitudinal structural MRI measures of the brain. Psychiatry Res 2022; 321:111446. [PMID: 35131573 PMCID: PMC8924876 DOI: 10.1016/j.pscychresns.2022.111446] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 01/14/2022] [Accepted: 01/24/2022] [Indexed: 11/24/2022]
Abstract
Longitudinal MRI is used in clinical research studies to examine illness progression, neurodevelopment, and the effect of medical interventions. Such studies typically report changes in brain volume of less than 5%. However, there is a concern that these findings could be obscured or confounded by small changes in brain volume estimates caused by physiological factors such as, dehydration, blood pressure, caffeine levels, and circadian rhythm. In this study, MRI scans using the ADNI-III protocol were acquired from 20 participants (11 female) at two time points (mean interval = 20.3 days). Hydration, systolic and diastolic blood pressure, caffeine intake, and time of day were recorded at both visits. Images were processed using FreeSurfer. Three a priori hypothesised brain regions (hippocampus, lateral ventricles, and total brain) were selected, and an exploratory analysis was conducted on FreeSurfer's auto-segmented brain regions. There was no significant effect of the physiological factors on changes in the hypothesised brain regions. We provide estimates for the maximum percentage change in regional brain volumes that could be expected to occur from normal variation in each of the physiological measures. In this study, normal variations in physiological parameters did not have a detectable effect on longitudinal changes in brain volume.
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Affiliation(s)
- Uzma Zahid
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom.
| | - Emily P Hedges
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Mihail Dimitrov
- Department of Forensic & Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Robin M Murray
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, United Kingdom
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Wittayer M, Hoyer C, Roßmanith C, Platten M, Gass A, Szabo K. Hippocampal subfield involvement in patients with transient global amnesia. J Neuroimaging 2022; 32:264-267. [PMID: 35106877 DOI: 10.1111/jon.12973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/12/2022] [Accepted: 01/12/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND AND PURPOSE Transient global amnesia (TGA) is a rare neurological disorder causing a transient disturbance of episodic long-term memory. Its etiology remains yet to be identified; the only consistently reported findings in patients with TGA are small hyperintense lesions in the hippocampus on diffusion-weighted magnetic resonance imaging (DWI). The aim of this study was to define whether these lesions are subfield specific, as suggested previously. METHODS High-resolution multiplanar reformation T1 and DWI of the hippocampus were acquired in 25 patients after TGA with a total of 43 hippocampal lesions. Hippocampal subfields were determined using the FreeSurfer software and the location of the DWI lesions was transformed to the T1 images after data co-registration. Additionally, hippocampal subfield volumes in each patient were calculated and compared with that of 20 healthy controls. RESULTS Hippocampal lesions were most frequently detected in the cornu ammonis area 1 (CA1) subfield (30.2%), the hippocampal tail (28.0%), and the subiculum (21.0%); however, lesions were also found in other subfields. There was no significant difference between patients and controls concerning the volumes of the hippocampal subfields. CONCLUSIONS Contrasting previous assumptions, we found DWI hyperintense lesions not to be restricted to the CA1 subfield. The visualization of focal hippocampal lesions on diffusion imaging located to several different hippocampal subfields suggests a potential pathophysiology of TGA independent of microstructural hippocampal anatomy and subfield-specific vulnerability.
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Affiliation(s)
- Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Carolin Hoyer
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Christina Roßmanith
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
| | - Kristina Szabo
- Department of Neurology, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Mannheim Center for Translational Neurosciences (MCTN), Heidelberg University, Mannheim, Germany
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Li S, Bai R, Yang Y, Zhao R, Upreti B, Wang X, Liu S, Cheng Y, Xu J. Abnormal cortical thickness and structural covariance networks in systemic lupus erythematosus patients without major neuropsychiatric manifestations. Arthritis Res Ther 2022; 24:259. [PMID: 36443835 PMCID: PMC9703716 DOI: 10.1186/s13075-022-02954-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 11/11/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) has been confirmed to have subtle changes in brain structure before the appearance of obvious neuropsychiatric symptoms. Previous literature mainly focuses on brain structure loss in non-NPSLE; however, the results are heterogeneous, and the impact of structural changes on the topological structure of patients' brain networks remains to be determined. In this study, we combined neuroimaging and network analysis methods to evaluate the changes in cortical thickness and its structural covariance networks (SCNs) in patients with non-NPSLE. METHODS We compare the cortical thickness of non-NPSLE patients (N=108) and healthy controls (HCs, N=88) using both surface-based morphometry (SBM) and regions of interest (ROI) methods, respectively. After that, we analyzed the correlation between the abnormal cortical thickness results found in the ROI method and a series of clinical features. Finally, we constructed the SCNs of two groups using the regional cortical thickness and analyzed the abnormal SCNs of non-NPSLE. RESULTS By SBM method, we found that cortical thickness of 34 clusters in the non-NPSLE group was thinner than that in the HC group. ROI method based on Destrieux atlas showed that cortical thickness of 57 regions in the non-NPSLE group was thinner than that in the HC group and related to the course of disease, autoantibodies, the cumulative amount of immunosuppressive agents, and cognitive psychological scale. In the SCN analysis, the cortical thickness SCNs of the non-NPSLE group did not follow the small-world attribute at a few densities, and the global clustering coefficient appeared to increase. The area under the curve analysis showed that there were significant differences between the two groups in clustering coefficient, degree, betweenness, and local efficiency. There are a total of seven hubs for non-NPSLE, and five hubs in HCs, the two groups do not share a common hub distribution. CONCLUSION Extensive and obvious reduction in cortical thickness and abnormal topological organization of SCNs are observed in non-NPSLE patients. The observed abnormalities may not only be the realization of brain damage caused by the disease, but also the contribution of the compensatory changes within the nervous system.
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Affiliation(s)
- Shu Li
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ru Bai
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yifan Yang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Ruotong Zhao
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Bibhuti Upreti
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiangyu Wang
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuang Liu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Yuqi Cheng
- Department of Psychiatry, First Affiliated Hospital of Kunming Medical University, Kunming, China.
| | - Jian Xu
- Department of Rheumatology and Immunology, First Affiliated Hospital of Kunming Medical University, Kunming, China.
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Zhang S, Fan W, Hu H, Wen L, Gong M, Liu B, Hu J, Li G, Zhang D. Subcortical Volume Changes in Early Menopausal Women and Correlation With Neuropsychological Tests. Front Aging Neurosci 2021; 13:738679. [PMID: 34955807 PMCID: PMC8692945 DOI: 10.3389/fnagi.2021.738679] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/16/2021] [Indexed: 01/04/2023] Open
Abstract
Background: The aging process and declining estradiol levels are two important factors that cause structural brain alterations. Many prior studies have investigated these two elements and revealed controversial results in menopausal women. Here, a cross-sectional study was designed to individually evaluate estradiol-related structural changes in the brain. Methods: A total of 45 early menopausal women and 54 age-matched premenopausal controls were enrolled and subjected to magnetic resonance imaging (MRI) scans, blood biochemistry tests, and neuropsychological tests. MRI structural images were analyzed using FreeSurfer to detect changes in subcortical and cortical volumes as well as cortical thickness. Finally, structural brain data as well as clinical and neuropsychological data were used for Pearson's correlation analyses to individually determine estradiol-related structural and functional changes in the brains of early menopausal women. Results: Compared with the premenopausal controls, the early menopausal women showed significant subcortical volumetric loss in the left amygdala and right amygdala, higher serum follicle-stimulating hormone (FSH) levels, more recognizable climacteric and depressive symptoms, decreased quality of sleep, and decreased working memory and executive functions. Simultaneously, FSH levels were related to lower working memory accuracy and longer working memory reaction time. Decreased subcortical volume in the bilateral amygdala was also related to lower working memory accuracy and longer executive reaction time in early menopausal women. Conclusion: The data suggest that estradiol deficiency in early menopausal women can lead to subcortical volume and functional brain changes, which may contribute to further understanding the neurobiological role of declined estradiol levels in early menopausal women.
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Affiliation(s)
- Si Zhang
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Weijie Fan
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Hao Hu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Li Wen
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Mingfu Gong
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Bo Liu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Junhao Hu
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Guanghui Li
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
| | - Dong Zhang
- Department of Radiology, XinQiao Hosptial, Third Military Medical University, Chongqing, China
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Michels L, Buechler R, Kucian K. Increased structural covariance in brain regions for number processing and memory in children with developmental dyscalculia. J Neurosci Res 2021; 100:522-536. [PMID: 34933406 PMCID: PMC9306474 DOI: 10.1002/jnr.24998] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 10/19/2021] [Accepted: 11/18/2021] [Indexed: 01/05/2023]
Abstract
Developmental dyscalculia (DD) is a developmental learning disability associated with deficits in processing numerical and mathematical information. Several studies demonstrated functional network alterations in DD. Yet, there are no studies, which examined the structural network integrity in DD. We compared whole‐brain maps of volume based structural covariance between 19 (4 males) children with DD and 18 (4 males) typically developing children. We found elevated structural covariance in the DD group between the anterior intraparietal sulcus to the middle temporal and frontal gyrus (p < 0.05, corrected). A hippocampus subfield analysis showed higher structural covariance in the DD group for area CA3 to the parahippocampal and calcarine sulcus, angular gyrus and anterior part of the intraparietal sulcus as well as to the lingual gyrus. Lower structural covariance in this group was seen for the subiculum to orbitofrontal gyrus, anterior insula and middle frontal gyrus. In contrast, the primary motor cortex (control region) revealed no difference in structural covariance between groups. Our results extend functional magnetic resonance studies by revealing abnormal gray matter integrity in children with DD. These findings thus indicate that the pathophysiology of DD is mediated by both structural and functional abnormalities in a network involved in number processing and memory function.
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Affiliation(s)
- Lars Michels
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Neuroscience Centre Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Roman Buechler
- Department of Neuroradiology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Karin Kucian
- Neuroscience Centre Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.,Centre for MR-Research, University Children's Hospital Zurich, Zurich, Switzerland.,Children's Research Centre, University Children's Hospital Zurich, Zurich, Switzerland
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40
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Genon S, Bernhardt BC, La Joie R, Amunts K, Eickhoff SB. The many dimensions of human hippocampal organization and (dys)function. Trends Neurosci 2021; 44:977-989. [PMID: 34756460 DOI: 10.1016/j.tins.2021.10.003] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 09/06/2021] [Accepted: 10/05/2021] [Indexed: 11/19/2022]
Abstract
The internal organization of hippocampal formation has been studied for more than a century. Although early accounts emphasized its subfields along the medial-lateral axis, findings in recent decades have highlighted also the anterior-to-posterior (i.e., longitudinal) axis as a key contributor to this brain region's functional organization. Hence, understanding of hippocampal function likely demands characterizing both medial-to-lateral and anterior-to-posterior axes, an approach that has been concretized by recent advances in in vivo parcellation and gradient mapping techniques. Following a short historical overview, we review the evidence provided by these approaches in brain-mapping studies, as well as the perspectives they open for addressing the behavioral relevance of the interacting organizational axes in healthy and clinical populations.
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Affiliation(s)
- Sarah Genon
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.
| | | | - Renaud La Joie
- Memory and Aging Center, Weill Institute for Neuroscience, University of California, San Francisco, San Francisco, CA, USA
| | - Katrin Amunts
- Institute of Neuroscience and Medicine, Structural and Functional Organisation of the Brain (INM-1), Research Centre Jülich, Jülich, Germany; C. & O. Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
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41
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Du X, Zhang Y, Zhao Q, Qin W, Ma G, Fu J, Zhang Q. Effects of INSR genetic polymorphism on hippocampal volume and episodic memory in chinese type 2 diabetes. Acta Diabetol 2021; 58:1471-1480. [PMID: 34085146 DOI: 10.1007/s00592-021-01750-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 05/26/2021] [Indexed: 11/28/2022]
Abstract
AIMS We aimed to investigate the effect of the type 2 diabetes-specific insulin/IGF signaling genetic variants on the hippocampal volume and their relationships with episodic memory in Chinese patients with type 2 diabetes. METHODS Analysis of variance was used to evaluate the genotype-by-diagnosis interaction effect on hippocampal volume in Chinese participants (109 patients with type 2 diabetes, 116 healthy controls). Mediation analysis was performed to test whether the hippocampal volume would mediate the association between genotype and episodic memory in patients with type 2 diabetes. RESULTS INSR (rs8101064) exhibited a significant genotype-by-diagnosis interaction effect on the bilateral hippocampal volumes (left, P = 0.020; right, P = 0.004, PFDR < 0.05). The T allele carriers exhibited smaller bilateral hippocampal volumes than the CC homozygotes in patients with type 2 diabetes (left, P = 0.004; right, P = 0.002). Mediation analysis revealed the significant mediation effect of the left hippocampal volume on the association between INSR (rs8101064) genetic polymorphism and the short- and long-term memory scores in patients with type 2 diabetes (short-term memory: 95% CI, -2.716, -0.266; long-term memory: 95% CI, -0.823, -0.103). CONCLUSIONS Hyperglycemia exposure and INSR (rs8101064) genetic polymorphism had an interaction effect on the hippocampal volume, and the T allele of the INSR (rs8101064) may serve as a risk factor for the decreased hippocampal volume in Chinese patients with type 2 diabetes. The left hippocampal volume mediated the effect of INSR (rs8101064) genetic polymorphism on episodic memory in Chinese patients with type 2 diabetes, which provided a biological pathway for understanding how the INSR (rs8101064) genetic polymorphism affects episodic memory in type 2 diabetes.
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Affiliation(s)
- Xin Du
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yang Zhang
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Qiuyue Zhao
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Wen Qin
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Guangyang Ma
- Department of Radiology, Tianjin Medical University Metabolic Diseases Hospital, Tianjin, 300060, China
| | - Jilian Fu
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Quan Zhang
- Department of Medical imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
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42
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Estimating the effect of a scanner upgrade on measures of grey matter structure for longitudinal designs. PLoS One 2021; 16:e0239021. [PMID: 34610020 PMCID: PMC8491918 DOI: 10.1371/journal.pone.0239021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Accepted: 08/13/2021] [Indexed: 12/28/2022] Open
Abstract
Longitudinal imaging studies are crucial for advancing the understanding of brain development over the lifespan. Thus, more and more studies acquire imaging data at multiple time points or with long follow-up intervals. In these studies changes to magnetic resonance imaging (MRI) scanners often become inevitable which may decrease the reliability of the MRI assessments and introduce biases. We therefore investigated the difference between MRI scanners with subsequent versions (3 Tesla Siemens Verio vs. Skyra) on the cortical and subcortical measures of grey matter in 116 healthy, young adults using the well-established longitudinal FreeSurfer stream for T1-weighted brain images. We found excellent between-scanner reliability for cortical and subcortical measures of grey matter structure (intra-class correlation coefficient > 0.8). Yet, paired t-tests revealed statistically significant differences in at least 67% of the regions, with percent differences around 2 to 4%, depending on the outcome measure. Offline correction for gradient distortions only slightly reduced these biases. Further, T1-imaging based quality measures reflecting gray-white matter contrast systematically differed between scanners. We conclude that scanner upgrades during a longitudinal study introduce bias in measures of cortical and subcortical grey matter structure. Therefore, before upgrading a MRI scanner during an ongoing study, researchers should prepare to implement an appropriate correction method for these effects.
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43
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Seiger R, Hammerle FP, Godbersen GM, Reed MB, Spurny-Dworak B, Handschuh P, Klöbl M, Unterholzner J, Gryglewski G, Vanicek T, Lanzenberger R. Comparison and Reliability of Hippocampal Subfield Segmentations Within FreeSurfer Utilizing T1- and T2-Weighted Multispectral MRI Data. Front Neurosci 2021; 15:666000. [PMID: 34602964 PMCID: PMC8480394 DOI: 10.3389/fnins.2021.666000] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Accepted: 05/28/2021] [Indexed: 11/13/2022] Open
Abstract
The accurate segmentation of in vivo magnetic resonance imaging (MRI) data is a crucial prerequisite for the reliable assessment of disease progression, patient stratification or the establishment of putative imaging biomarkers. This is especially important for the hippocampal formation, a brain area involved in memory formation and often affected by neurodegenerative or psychiatric diseases. FreeSurfer, a widely used automated segmentation software, offers hippocampal subfield delineation with multiple input options. While a single T1-weighted (T1) sequence is regularly used by most studies, it is also possible and advised to use a high-resolution T2-weighted (T2H) sequence or multispectral information. In this investigation it was determined whether there are differences in volume estimations depending on the input images and which combination of these deliver the most reliable results in each hippocampal subfield. 41 healthy participants (age = 25.2 years ± 4.2 SD) underwent two structural MRIs at three Tesla (time between scans: 23 days ± 11 SD) using three different structural MRI sequences, to test five different input configurations (T1, T2, T2H, T1 and T2, and T1 and T2H). We compared the different processing pipelines in a cross-sectional manner and assessed reliability using test-retest variability (%TRV) and the dice coefficient. Our analyses showed pronounced significant differences and large effect sizes between the processing pipelines in several subfields, such as the molecular layer (head), CA1 (head), hippocampal fissure, CA3 (head and body), fimbria and CA4 (head). The longitudinal analysis revealed that T1 and multispectral analysis (T1 and T2H) showed overall higher reliability across all subfields than T2H alone. However, the specific subfields had a substantial influence on the performance of segmentation results, regardless of the processing pipeline. Although T1 showed good test-retest metrics, results must be interpreted with caution, as a standard T1 sequence relies heavily on prior information of the atlas and does not take the actual fine structures of the hippocampus into account. For the most accurate segmentation, we advise the use of multispectral information by using a combination of T1 and high-resolution T2-weighted sequences or a T2 high-resolution sequence alone.
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Affiliation(s)
- René Seiger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Fabian P Hammerle
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Godber M Godbersen
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Murray B Reed
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Benjamin Spurny-Dworak
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Patricia Handschuh
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Manfred Klöbl
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Jakob Unterholzner
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Thomas Vanicek
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
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Blood pressure variability and medial temporal atrophy in apolipoprotein ϵ4 carriers. Brain Imaging Behav 2021; 16:792-801. [PMID: 34581957 PMCID: PMC9009865 DOI: 10.1007/s11682-021-00553-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/31/2021] [Indexed: 12/12/2022]
Abstract
Blood pressure variability is an emerging risk factor for dementia but relationships with markers of neurodegeneration and Alzheimer's disease risk are understudied. We investigated blood pressure variability over one year and follow-up medial temporal brain volume change in apolipoprotein ϵ4 carriers and non-carriers, and in those with and without Alzheimer's disease biomarker abnormality. 1051 Alzheimer's Disease Neuroimaging Initiative participants without history of dementia or stroke underwent 3-4 blood pressure measurements over 12 months and ≥ 1 MRI thereafter. A subset (n = 252) underwent lumbar puncture to determine Alzheimer's disease cerebral spinal fluid amyloid-beta and phosphorylated tau biomarker abnormality. Blood pressure variability over 12 months was calculated as variability independent of mean. Longitudinal hippocampal and entorhinal cortex volume data were extracted from serial brain MRI scans obtained after the final blood pressure measurement. Apolipoprotein ϵ4 carrier status was defined as at least one ϵ4 allele. Bayesian growth modelling revealed a significant interaction of blood pressure variability by ϵ4 by time on hippocampal (ß: -2.61 [95% credible interval -3.02, -2.12]) and entorhinal cortex (ß: -1.47 [95% credible interval -1.71, -1.17]) volume decline. A similar pattern emerged in subsets with Alzheimer's disease pathophysiology (i.e., abnormal levels of both amyloid-beta and phosphorylated tau). Findings suggest that elevated blood pressure variability is related to medial temporal volume loss specifically in ϵ4 carriers, and in those with Alzheimer's disease biomarker abnormality. Findings could implicate blood pressure variability in medial temporal neurodegeneration observed in older ϵ4 carriers and those with prodromal Alzheimer's disease.
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45
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Sandry J, Dobryakova E. Global hippocampal and selective thalamic nuclei atrophy differentiate chronic TBI from Non-TBI. Cortex 2021; 145:37-56. [PMID: 34689031 DOI: 10.1016/j.cortex.2021.08.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 05/04/2021] [Accepted: 08/12/2021] [Indexed: 12/27/2022]
Abstract
Traumatic brain injury (TBI) may increase susceptibility to neurodegenerative diseases later in life. One neurobiological parallel between chronic TBI and neurodegeneration may be accelerated aging and the nature of atrophy across subcortical gray matter structures. The main aim of the present investigation is to evaluate and rank the degree that subcortical gray matter atrophy differentiates chronic moderate-severe TBI from non-TBI participants by evaluating morphometric differences between groups. Forty individuals with moderate-severe chronic TBI (9.23 yrs from injury) and 33 healthy controls (HC) underwent high resolution 3D T1-weighted structural magnetic resonance imaging. Whole brain volume was classified into white matter, cortical and subcortical gray matter structures with hippocampi and thalami further segmented into subfields and nuclei, respectively. Extensive atrophy was observed across nearly all brain regions for chronic TBI participants. A series of multivariate logistic regression models identified subcortical gray matter structures of the hippocampus and thalamus as the most sensitive to differentiating chronic TBI from non-TBI participants (McFadden R2 = .36, p < .001). Further analyses revealed the pattern of hippocampal atrophy to be global, occurring across nearly all subfields. The pattern of thalamic atrophy appeared to be much more selective and non-uniform, with largest between-group differences evident for nuclei bordering the ventricles. Subcortical gray matter was negatively correlated with time since injury (r = -.31, p = .054), while white matter and cortical gray matter were not. Cognitive ability was lower in the chronic TBI group (Cohen's d = .97, p = .003) and correlated with subcortical structures including the pallidum (r2 = .23, p = .038), thalamus (r2 = .36, p = .007) and ventral diencephalon (r2 = .23, p = .036). These data may support an accelerated aging hypothesis in chronic moderate-severe TBI that coincides with a similar neuropathological profile found in neurodegenerative diseases.
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Affiliation(s)
- Joshua Sandry
- Psychology Department, Montclair State University, Montclair, NJ, USA.
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury Research, Kessler Foundation, East Hanover, NJ, USA; Department of Physical Medicine and Rehabilitation, Rutgers-New Jersey Medical School Newark, NJ, USA
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46
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Ciolac D, Gonzalez-Escamilla G, Radetz A, Fleischer V, Person M, Johnen A, Landmeyer NC, Krämer J, Muthuraman M, Meuth SG, Groppa S. Sex-specific signatures of intrinsic hippocampal networks and regional integrity underlying cognitive status in multiple sclerosis. Brain Commun 2021; 3:fcab198. [PMID: 34514402 PMCID: PMC8417841 DOI: 10.1093/braincomms/fcab198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/27/2021] [Accepted: 07/15/2021] [Indexed: 11/24/2022] Open
Abstract
The hippocampus is an anatomically compartmentalized structure embedded in highly wired networks that are essential for cognitive functions. The hippocampal vulnerability has been postulated in acute and chronic neuroinflammation in multiple sclerosis, while the patterns of occurring inflammation, neurodegeneration or compensation have not yet been described. Besides focal damage to hippocampal tissue, network disruption is an important contributor to cognitive decline in multiple sclerosis patients. We postulate sex-specific trajectories in hippocampal network reorganization and regional integrity and address their relationship to markers of neuroinflammation, cognitive/memory performance and clinical severity. In a large cohort of multiple sclerosis patients (n = 476; 337 females, age 35 ± 10 years, disease duration 16 ± 14 months) and healthy subjects (n = 110, 54 females; age 34 ± 15 years), we utilized MRI at baseline and at 2-year follow-up to quantify regional hippocampal volumetry and reconstruct single-subject hippocampal networks. Through graph analytical tools we assessed the clustered topology of the hippocampal networks. Mixed-effects analyses served to model sex-based differences in hippocampal network and subfield integrity between multiple sclerosis patients and healthy subjects at both time points and longitudinally. Afterwards, hippocampal network and subfield integrity were related to clinical and radiological variables in dependency of sex attribution. We found a more clustered network architecture in both female and male patients compared to their healthy counterparts. At both time points, female patients displayed a more clustered network topology in comparison to male patients. Over time, multiple sclerosis patients developed an even more clustered network architecture, though with a greater magnitude in females. We detected reduced regional volumes in most of the addressed hippocampal subfields in both female and male patients compared to healthy subjects. Compared to male patients, females displayed lower volumes of para- and presubiculum but higher volumes of the molecular layer. Longitudinally, volumetric alterations were more pronounced in female patients, which showed a more extensive regional tissue loss. Despite a comparable cognitive/memory performance between female and male patients over the follow-up period, we identified a strong interrelation between hippocampal network properties and cognitive/memory performance only in female patients. Our findings evidence a more clustered hippocampal network topology in female patients with a more extensive subfield volume loss over time. A stronger relation between cognitive/memory performance and the network topology in female patients suggests greater entrainment of the brain’s reserve. These results may serve to adapt sex-targeted neuropsychological interventions.
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Affiliation(s)
- Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany.,Department of Neurology, Institute of Emergency Medicine, Chisinau 2004, Moldova.,Laboratory of Neurobiology and Medical Genetics, Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau 2004, Moldova
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Angela Radetz
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Maren Person
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Andreas Johnen
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Nils C Landmeyer
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Julia Krämer
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Sven G Meuth
- Department of Neurology, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
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Association between the expression of lncRNA BASP-AS1 and volume of right hippocampal tail moderated by episode duration in major depressive disorder: a CAN-BIND 1 report. Transl Psychiatry 2021; 11:469. [PMID: 34508068 PMCID: PMC8433329 DOI: 10.1038/s41398-021-01592-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 08/16/2021] [Accepted: 08/26/2021] [Indexed: 02/08/2023] Open
Abstract
The pathophysiology of major depressive disorder (MDD) encompasses an array of changes at molecular and neurobiological levels. As chronic stress promotes neurotoxicity there are alterations in the expression of genes and gene-regulatory molecules. The hippocampus is particularly sensitive to the effects of stress and its posterior volumes can deliver clinically valuable information about the outcomes of antidepressant treatment. In the present work, we analyzed individuals with MDD (N = 201) and healthy controls (HC = 104), as part of the CAN-BIND-1 study. We used magnetic resonance imaging (MRI) to measure hippocampal volumes, evaluated gene expression with RNA sequencing, and assessed DNA methylation with the (Infinium MethylationEpic Beadchip), in order to investigate the association between hippocampal volume and both RNA expression and DNA methylation. We identified 60 RNAs which were differentially expressed between groups. Of these, 21 displayed differential methylation, and seven displayed a correlation between methylation and expression. We found a negative association between expression of Brain Abundant Membrane Attached Signal Protein 1 antisense 1 RNA (BASP1-AS1) and right hippocampal tail volume in the MDD group (β = -0.218, p = 0.021). There was a moderating effect of the duration of the current episode on the association between the expression of BASP1-AS1 and right hippocampal tail volume in the MDD group (β = -0.48, 95% C.I. [-0.80, -0.16]. t = -2.95 p = 0.004). In conclusion, we found that overexpression of BASP1-AS1 was correlated with DNA methylation, and was negatively associated with right tail hippocampal volume in MDD.
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Droby A, Thaler A, Giladi N, Hutchison RM, Mirelman A, Ben Bashat D, Artzi M. Whole brain and deep gray matter structure segmentation: Quantitative comparison between MPRAGE and MP2RAGE sequences. PLoS One 2021; 16:e0254597. [PMID: 34358242 PMCID: PMC8345829 DOI: 10.1371/journal.pone.0254597] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 06/29/2021] [Indexed: 11/29/2022] Open
Abstract
Objective T1-weighted MRI images are commonly used for volumetric assessment of brain structures. Magnetization prepared 2 rapid gradient echo (MP2RAGE) sequence offers superior gray (GM) and white matter (WM) contrast. This study aimed to quantitatively assess the agreement of whole brain tissue and deep GM (DGM) volumes obtained from MP2RAGE compared to the widely used MP-RAGE sequence. Methods Twenty-nine healthy participants were included in this study. All subjects underwent a 3T MRI scan acquiring high-resolution 3D MP-RAGE and MP2RAGE images. Twelve participants were re-scanned after one year. The whole brain, as well as DGM segmentation, was performed using CAT12, volBrain, and FSL-FAST automatic segmentation tools based on the acquired images. Finally, contrast-to-noise ratio between WM and GM (CNRWG), the agreement between the obtained tissue volumes, as well as scan-rescan variability of both sequences were explored. Results Significantly higher CNRWG was detected in MP2RAGE vs. MP-RAGE (Mean ± SD = 0.97 ± 0.04 vs. 0.8 ± 0.1 respectively; p<0.0001). Significantly higher total brain GM, and lower cerebrospinal fluid volumes were obtained from MP2RAGE vs. MP-RAGE based on all segmentation methods (p<0.05 in all cases). Whole-brain voxel-wise comparisons revealed higher GM tissue probability in the thalamus, putamen, caudate, lingual gyrus, and precentral gyrus based on MP2RAGE compared with MP-RAGE. Moreover, significantly higher WM probability was observed in the cerebellum, corpus callosum, and frontal-and-temporal regions in MP2RAGE vs. MP-RAGE. Finally, MP2RAGE showed a higher mean percentage of change in total brain GM compared to MP-RAGE. On the other hand, MP-RAGE demonstrated a higher overtime percentage of change in WM and DGM volumes compared to MP2RAGE. Conclusions Due to its higher CNR, MP2RAGE resulted in reproducible brain tissue segmentation, and thus is a recommended method for volumetric imaging biomarkers for the monitoring of neurological diseases.
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Affiliation(s)
- Amgad Droby
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- * E-mail:
| | - Avner Thaler
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Nir Giladi
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | | | - Anat Mirelman
- Laboratory for Early Markers of Neurodegeneration (LEMON), Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Dafna Ben Bashat
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Moran Artzi
- Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
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Weis CN, Webb EK, Huggins AA, Kallenbach M, Miskovich TA, Fitzgerald JM, Bennett KP, Krukowski JL, deRoon-Cassini TA, Larson CL. Stability of hippocampal subfield volumes after trauma and relationship to development of PTSD symptoms. Neuroimage 2021; 236:118076. [PMID: 33878374 PMCID: PMC8284190 DOI: 10.1016/j.neuroimage.2021.118076] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 03/01/2021] [Accepted: 04/08/2021] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The hippocampus plays a central role in post-traumatic stress disorder (PTSD) pathogenesis, and the majority of neuroimaging research on PTSD has studied the hippocampus in its entirety. Although extensive literature demonstrates changes in hippocampal volume are associated with PTSD, fewer studies have probed the relationship between symptoms and the hippocampus' functionally and structurally distinct subfields. We utilized data from a longitudinal study examining post-trauma outcomes to determine whether hippocampal subfield volumes change post-trauma and whether specific subfields are significantly associated with, or prospectively related to, PTSD symptom severity. As a secondary aim, we leveraged our unique study design sample to also investigate reliability of hippocampal subfield volumes using both cross-sectional and longitudinal pipelines available in FreeSurfer v6.0. METHODS Two-hundred and fifteen traumatically injured individuals were recruited from an urban Emergency Department. Two-weeks post-injury, participants underwent two consecutive days of neuroimaging (time 1: T1, and time 2: T2) with magnetic resonance imaging (MRI) and completed self-report assessments. Six-months later (time 3: T3), participants underwent an additional scan and were administered a structured interview assessing PTSD symptoms. First, we calculated reliability of hippocampal measurements at T1 and T2 (automatically segmented with FreeSurfer v6.0). We then examined the prospective (T1 subfields) and cross-sectional (T3 subfields) relationship between volumes and PTSD. Finally, we tested whether change in subfield volumes between T1 and T3 explained PTSD symptom variability. RESULTS After controlling for sex, age, and total brain volume, none of the subfield volumes (T1) were prospectively related to T3 PTSD symptoms nor were subfield volumes (T3) associated with current PTSD symptoms (T3). Tl - T2 reliability of all hippocampal subfields ranged from good to excellent (intraclass correlation coefficient (ICC) values > 0.83), with poorer reliability in the hippocampal fissure. CONCLUSION Our study was a novel examination of the prospective relationship between hippocampal subfield volumes in relation to PTSD in a large trauma-exposed urban sample. There was no significant relationship between subfield volumes and PTSD symptoms, however, we confirmed FreeSurfer v6.0 hippocampal subfield segmentation is reliable when applied to a traumatically-injured sample, using both cross-sectional and longitudinal analysis pipelines. Although hippocampal subfield volumes may be an important marker of individual variability in PTSD, findings are likely conditional on the timing of the measurements (e.g. acute or chronic post-trauma periods) and analysis strategy (e.g. cross-sectional or prospective).
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Affiliation(s)
- C N Weis
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States.
| | - E K Webb
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - A A Huggins
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - M Kallenbach
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - T A Miskovich
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - J M Fitzgerald
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - K P Bennett
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - J L Krukowski
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - T A deRoon-Cassini
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
| | - C L Larson
- University of Wisconsin Milwaukee, Psychology, Department of Psychology, 334 Garland Hall, 2441 E. Hartford Ave, Milwaukee, WI 53211, United States
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Kwak K, Niethammer M, Giovanello KS, Styner M, Dayan E. Differential Role for Hippocampal Subfields in Alzheimer's Disease Progression Revealed with Deep Learning. Cereb Cortex 2021; 32:467-478. [PMID: 34322704 DOI: 10.1093/cercor/bhab223] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Mild cognitive impairment (MCI) is often considered the precursor of Alzheimer's disease. However, MCI is associated with substantially variable progression rates, which are not well understood. Attempts to identify the mechanisms that underlie MCI progression have often focused on the hippocampus but have mostly overlooked its intricate structure and subdivisions. Here, we utilized deep learning to delineate the contribution of hippocampal subfields to MCI progression. We propose a dense convolutional neural network architecture that differentiates stable and progressive MCI based on hippocampal morphometry with an accuracy of 75.85%. A novel implementation of occlusion analysis revealed marked differences in the contribution of hippocampal subfields to the performance of the model, with presubiculum, CA1, subiculum, and molecular layer showing the most central role. Moreover, the analysis reveals that 10.5% of the volume of the hippocampus was redundant in the differentiation between stable and progressive MCI.
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Affiliation(s)
- Kichang Kwak
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Marc Niethammer
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kelly S Giovanello
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Martin Styner
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Eran Dayan
- Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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