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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] [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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Devignes Q, Ren B, Clancy KJ, Howell K, Pollmann Y, Martinez-Sanchez L, Beard C, Kumar P, Rosso IM. Trauma-related intrusive memories and anterior hippocampus structural covariance: an ecological momentary assessment study in posttraumatic stress disorder. Transl Psychiatry 2024; 14:74. [PMID: 38307849 PMCID: PMC10837434 DOI: 10.1038/s41398-024-02795-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 01/09/2024] [Accepted: 01/17/2024] [Indexed: 02/04/2024] Open
Abstract
Trauma-related intrusive memories (TR-IMs) are hallmark symptoms of posttraumatic stress disorder (PTSD), but their neural correlates remain partly unknown. Given its role in autobiographical memory, the hippocampus may play a critical role in TR-IM neurophysiology. The anterior and posterior hippocampi are known to have partially distinct functions, including during retrieval of autobiographical memories. This study aimed to investigate the relationship between TR-IM frequency and the anterior and posterior hippocampi morphology in PTSD. Ninety-three trauma-exposed adults completed daily ecological momentary assessments for fourteen days to capture their TR-IM frequency. Participants then underwent anatomical magnetic resonance imaging to obtain measures of anterior and posterior hippocampal volumes. Partial least squares analysis was applied to identify a structural covariance network that differentiated the anterior and posterior hippocampi. Poisson regression models examined the relationship of TR-IM frequency with anterior and posterior hippocampal volumes and the resulting structural covariance network. Results revealed no significant relationship of TR-IM frequency with hippocampal volumes. However, TR-IM frequency was significantly negatively correlated with the expression of a structural covariance pattern specifically associated with the anterior hippocampus volume. This association remained significant after accounting for the severity of PTSD symptoms other than intrusion symptoms. The network included the bilateral inferior temporal gyri, superior frontal gyri, precuneus, and fusiform gyri. These novel findings indicate that higher TR-IM frequency in individuals with PTSD is associated with lower structural covariance between the anterior hippocampus and other brain regions involved in autobiographical memory, shedding light on the neural correlates underlying this core symptom of PTSD.
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Affiliation(s)
- Quentin Devignes
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
| | - Boyu Ren
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric Biostatistics Laboratory, McLean Hospital, Belmont, MA, USA
| | - Kevin J Clancy
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Kristin Howell
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA
| | - Yara Pollmann
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA
| | | | - Courtney Beard
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Depression and Anxiety Disorders, McLean Hospital, Belmont, MA, USA
| | - Poornima Kumar
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Isabelle M Rosso
- Center for Depression, Anxiety and Stress Disorders, McLean Hospital, Belmont, MA, USA.
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA.
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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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Connaughton M, O’Hanlon E, Silk TJ, Paterson J, O’Neill A, Anderson V, Whelan R, McGrath J. The Limbic System in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder: A Longitudinal Structural Magnetic Resonance Imaging Analysis. BIOLOGICAL PSYCHIATRY GLOBAL OPEN SCIENCE 2024; 4:385-393. [PMID: 38298776 PMCID: PMC10829648 DOI: 10.1016/j.bpsgos.2023.10.005] [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: 07/03/2023] [Revised: 10/09/2023] [Accepted: 10/17/2023] [Indexed: 02/02/2024] Open
Abstract
Background During childhood and adolescence, attention-deficit/hyperactivity disorder (ADHD) is associated with changes in symptoms and brain structures, but the link between brain structure and function remains unclear. The limbic system, often termed the "emotional network," plays an important role in a number of neurodevelopmental disorders, yet this brain network remains largely unexplored in ADHD. Investigating the developmental trajectories of key limbic system structures during childhood and adolescence will provide novel insights into the neurobiological underpinnings of ADHD. Methods Structural magnetic resonance imaging data (380 scans), emotional regulation (Affective Reactivity Index), and ADHD symptom severity (Conners 3 ADHD Index) were measured at up to 3 time points between 9 and 14 years of age in a sample of children and adolescents with ADHD (n = 57) and control children (n = 109). Results Compared with the control group, the ADHD group had lower volume of the amygdala (left: β standardized [β_std] = -0.38; right: β_std = -0.34), hippocampus (left: β_std = -0.44; right: β_std = -0.34), cingulate gyrus (left: β_std = -0.42; right: β_std = -0.32), and orbitofrontal cortex (right: β_std = -0.33) across development (9-14 years). There were no significant group-by-age interactions in any of the limbic system structures. Exploratory analysis found a significant Conners 3 ADHD Index-by-age interaction effect on the volume of the left mammillary body (β_std = 0.17) in the ADHD group across the 3 study time points. Conclusions Children and adolescents with ADHD displayed lower volume and atypical development in limbic system structures. Furthermore, atypical limbic system development was associated with increased symptom severity, highlighting a potential neurobiological correlate of ADHD severity.
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Affiliation(s)
- Michael Connaughton
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erik O’Hanlon
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Timothy J. Silk
- Department of Developmental Neuroimaging, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
- Centre for Social and Early Emotional Development and School of Psychology, Deakin University, Geelong, Victoria, Australia
| | - Julia Paterson
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Aisling O’Neill
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Vicki Anderson
- Department of Developmental Neuroimaging, Murdoch Children’s Research Institute, Melbourne, Victoria, Australia
- Department of Psychology, Royal Children’s Hospital, Melbourne, Victoria, Australia
| | - Robert Whelan
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jane McGrath
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
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Feng Q, Wang L, Tang X, Ge X, Hu H, Liao Z, Ding Z. Machine learning classifiers and associations of cognitive performance with hippocampal subfields in amnestic mild cognitive impairment. Front Aging Neurosci 2023; 15:1273658. [PMID: 38099266 PMCID: PMC10719844 DOI: 10.3389/fnagi.2023.1273658] [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: 08/07/2023] [Accepted: 11/10/2023] [Indexed: 12/17/2023] Open
Abstract
Background Neuroimaging studies have demonstrated alterations in hippocampal volume and hippocampal subfields among individuals with amnestic mild cognitive impairment (aMCI). However, research on using hippocampal subfield volume modeling to differentiate aMCI from normal controls (NCs) is limited, and the relationship between hippocampal volume and overall cognitive scores remains unclear. Methods We enrolled 50 subjects with aMCI and 44 NCs for this study. Initially, a univariate general linear model was employed to analyze differences in the volumes of hippocampal subfields. Subsequently, two sets of dimensionality reduction methods and four machine learning techniques were applied to distinguish aMCI from NCs based on hippocampal subfield volumes. Finally, we assessed the correlation between the relative volumes of hippocampal subfields and cognitive test variables (Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment Scale (MoCA)). Results Significant volume differences were observed in several hippocampal subfields, notably in the left hippocampus. Specifically, the volumes of the hippocampal tail, subiculum, CA1, presubiculum, molecular layer, GC-ML-DG, CA3, CA4, and fimbria differed significantly between the two groups. The highest area under the curve (AUC) values for left and right hippocampal machine learning classifiers were 0.678 and 0.701, respectively. Moreover, the volumes of the left subiculum, left molecular layer, right subiculum, right CA1, right molecular layer, right GC-ML-DG, and right CA4 exhibited the strongest and most consistent correlations with MoCA scores. Conclusion Hippocampal subfield volume may serve as a predictive marker for aMCI. These findings underscore the sensitivity of hippocampal subfield volume to overall cognitive performance.
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Affiliation(s)
- Qi Feng
- Department of Radiology, Hangzhou First People’s Hospital, Hangzhou, China
| | - Luoyu Wang
- Department of Radiology, Hangzhou First People’s Hospital, Hangzhou, China
| | - Xue Tang
- School of Medical Imaging, Hangzhou Medical College, Hangzhou, China
| | - Xiuhong Ge
- Department of Radiology, Hangzhou First People’s Hospital, Hangzhou, China
| | - Hanjun Hu
- Zhejiang Chinese Medical University, Hangzhou, China
| | - Zhengluan Liao
- Department of Psychiatry, Zhejiang Provincial People’s Hospital/People’s Hospital of Hangzhou Medical College, Hangzhou, China
| | - Zhongxiang Ding
- Department of Radiology, Hangzhou First People’s Hospital, Hangzhou, China
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Monereo-Sánchez J, Jansen JFA, Köhler S, van Boxtel MPJ, Backes WH, Stehouwer CDA, Kroon AA, Kooman JP, Schalkwijk CG, Linden DEJ, Schram MT. The association of prediabetes and type 2 diabetes with hippocampal subfields volume: The Maastricht study. Neuroimage Clin 2023; 39:103455. [PMID: 37356423 PMCID: PMC10310479 DOI: 10.1016/j.nicl.2023.103455] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/13/2023] [Accepted: 06/18/2023] [Indexed: 06/27/2023]
Abstract
AIMS/HYPOTHESIS We investigated whether prediabetes, type 2 diabetes, and continuous measures of hyperglycemia are associated with tissue volume differences in specific subfields of the hippocampus. METHODS We used cross-sectional data from 4,724 participants (58.7 ± 8.5 years, 51.5% women) of The Maastricht Study, a population-based prospective cohort. Glucose metabolism status was assessed with an oral glucose tolerance test, and defined as type 2 diabetes (n = 869), prediabetes (n = 671), or normal glucose metabolism (n = 3184). We extracted 12 hippocampal subfield volumes per hemisphere with FreeSurfer v6.0 using T1w and FLAIR 3T MRI images. We used multiple linear regression and linear trend analysis, and adjusted for total intracranial volume, demographic, lifestyle, and cardiovascular risk factors. RESULTS Type 2 diabetes was significantly associated with smaller volumes in the hippocampal subfield fimbria (standardized beta coefficient ± standard error (β ± SE) = -0.195 ± 0.04, p-value < 0.001), the hippocampus proper, i.e. Cornu Ammonis (CA) 1, CA2/3, CA4, dentate gyrus, subiculum and presubiculum (β ± SE < -0.105 ± 0.04, p-value < 0.006); as well as the hippocampal tail (β ± SE = -0.162 ± 0.04, p-value < 0.001). Prediabetes showed no significant associations. However, linear trend analysis indicated a dose-response relation from normal glucose metabolism, to prediabetes, to type 2 diabetes. Multiple continuous measures of hyperglycemia were associated with smaller volumes of the subfields fimbria (β ± SE < -0.010 ± 0.011, p-value < 0.001), dentate gyrus (β ± SE < -0.013 ± 0.010, p-value < 0.002), CA3 (β ± SE < -0.014 ± 0.011, p-value < 0.001), and tail (β ± SE < -0.006 ± 0.012, p-value < 0.003). CONCLUSIONS/INTERPRETATION Type 2 diabetes and measures of hyperglycemia are associated with hippocampal subfield atrophy, independently of lifestyle and cardiovascular risk factors. We found evidence for a dose-response relationship from normal glucose metabolism, to prediabetes, to type 2 diabetes. Prediabetes stages could give a window of opportunity for the early prevention of brain disease.
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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; 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; Department of Radiology & Nuclear Medicine, Maastricht University Medical Center, The Netherlands.
| | - Sebastian Köhler
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, The Netherlands; 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.
| | - Martin P J van Boxtel
- School for Mental Health & Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands; Department of Psychiatry and Neuropsychology, Maastricht University Medical Center, The Netherlands; 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; School for Cardiovascular Diseases, Faculty of Health, Medicine and Life Sciences, Maastricht University, The Netherlands.
| | - Coen D A Stehouwer
- 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.
| | - Abraham A Kroon
- 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.
| | - Jeroen P Kooman
- Department of Internal Medicine, Maastricht University Medical Center, The Netherlands; School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, The Netherlands.
| | - Casper G Schalkwijk
- 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.
| | - 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; Maastricht Heart+Vascular Center, Maastricht University Medical Center, The Netherlands.
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Atrophy asymmetry in hippocampal subfields in patients with Alzheimer's disease and mild cognitive impairment. Exp Brain Res 2023; 241:495-504. [PMID: 36593344 DOI: 10.1007/s00221-022-06543-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023]
Abstract
Volumetric analysis of hippocampal subfields and their asymmetry assessment recently has been useful biomarkers in neuroscience. In this study, hippocampal subfields atrophy and pattern of their asymmetry in the patient with Alzheimer's disease (AD) and mild cognitive impairment (MCI) were evaluated. MRI images of 20 AD patients, 20 MCI patients, and 20 healthy control (HC) were selected. The volumes of hippocampal subfields were extracted automatically using Freesurfer toolkit. The subfields asymmetry index (AI) and laterality ([Formula: see text]) were also evaluated. Analysis of covariance was used to compare the subfields volume between three patient groups (age and gender as covariates). We used ANOVA (P < 0.05) test for multiple comparisons with Bonferroni's post hoc correction method. Hippocampal subfields volume in AD patients were significantly lower than HC and MCI groups (P < 0.02); however, no significant difference was observed between MCI and HC groups. The asymmetry index (AI) in some subfields was significantly different between AD and MCI, as well as between AD and HC, while there was not any significant difference between MCI groups with HC. In all three patient groups, rightward laterality ([Formula: see text]) was seen in several subfields except subiculum, presubiculum, and parasubiculum, while in AD patient, rightward lateralization slightly decrease. Hippocampal subfields asymmetry can be used as a quantitative biomarker in neurocognitive disorders. In this study, it was observed that the asymmetry index of some subfields in AD is significantly different from MCI. In AD, patient rightward laterality was less MCI an HC group.
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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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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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10
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Lee JK, Andrews DS, Ozturk A, Solomon M, Rogers S, Amaral DG, Nordahl CW. Altered Development of Amygdala-Connected Brain Regions in Males and Females with Autism. J Neurosci 2022; 42:6145-6155. [PMID: 35760533 PMCID: PMC9351637 DOI: 10.1523/jneurosci.0053-22.2022] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 04/30/2022] [Accepted: 06/08/2022] [Indexed: 02/05/2023] Open
Abstract
Altered amygdala development is implicated in the neurobiology of autism, but little is known about the coordinated development of the brain regions directly connected with the amygdala. Here we investigated the volumetric development of an amygdala-connected network, defined as the set of brain regions with monosynaptic connections with the amygdala, in autism from early to middle childhood. A total of 950 longitudinal structural MRI scans were acquired from 282 children (93 female) with autism and 128 children with typical development (61 female) at up to four time points (mean ages: 39, 52, 64, and 137 months, respectively). Volumes from 32 amygdala-connected brain regions were examined using mixed effects multivariate distance matrix regression. The Social Responsiveness Scale-2 was administered to assess degree of autistic traits and social impairments. The amygdala-connected network exhibited persistent diagnostic differences (p values ≤ 0.03) that increased over time (p values ≤ 0.02). These differences were most prominent in autistics with more impacted social functioning at baseline. This pattern was not observed across regions without monosynaptic amygdala connection. We observed qualitative sex differences. In males, the bilateral subgenual anterior cingulate cortices were most affected, while in females the left fusiform and superior temporal gyri were most affected. In conclusion, (1) autism is associated with widespread alterations to the development of brain regions connected with the amygdala, which were associated with autistic social behaviors; and (2) autistic males and females exhibited different patterns of alterations, adding to a growing body of evidence of sex differences in the neurobiology of autism.SIGNIFICANCE STATEMENT Global patterns of development across brain regions with monosynaptic connection to the amygdala differentiate autism from typical development, and are modulated by social functioning in early childhood. Alterations to brain regions within the amygdala-connected network differed in males and females with autism. Results also indicate larger volumetric differences in regions having monosynaptic connection with the amygdala than in regions without monosynaptic connection.
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Affiliation(s)
- Joshua K Lee
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Derek S Andrews
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Arzu Ozturk
- Department of Radiology, University of California Davis School of Medicine, Sacramento, California 95817
| | - Marjorie Solomon
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Sally Rogers
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - David G Amaral
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
| | - Christine Wu Nordahl
- MIND Institute, University of California Davis School of Medicine, Sacramento, California 95817
- Department of Psychiatry and Behavioral Sciences
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11
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Kannappan B, Gunasekaran TI, te Nijenhuis J, Gopal M, Velusami D, Kothandan G, Lee KH. Polygenic score for Alzheimer’s disease identifies differential atrophy in hippocampal subfield volumes. PLoS One 2022; 17:e0270795. [PMID: 35830443 PMCID: PMC9278752 DOI: 10.1371/journal.pone.0270795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 06/20/2022] [Indexed: 01/18/2023] Open
Abstract
Hippocampal subfield atrophy is a prime structural change in the brain, associated with cognitive aging and neurodegenerative diseases such as Alzheimer’s disease. Recent developments in genome-wide association studies (GWAS) have identified genetic loci that characterize the risk of hippocampal volume loss based on the processes of normal and abnormal aging. Polygenic risk scores are the genetic proxies mimicking the genetic role of the pre-existing vulnerabilities of the underlying mechanisms influencing these changes. Discriminating the genetic predispositions of hippocampal subfield atrophy between cognitive aging and neurodegenerative diseases will be helpful in understanding the disease etiology. In this study, we evaluated the polygenic risk of Alzheimer’s disease (AD PGRS) for hippocampal subfield atrophy in 1,086 individuals (319 cognitively normal (CN), 591 mild cognitively impaired (MCI), and 176 Alzheimer’s disease dementia (ADD)). Our results showed a stronger association of AD PGRS effect on the left hemisphere than on the right hemisphere for all the hippocampal subfield volumes in a mixed clinical population (CN+MCI+ADD). The subfields CA1, CA4, hippocampal tail, subiculum, presubiculum, molecular layer, GC-ML-DG, and HATA showed stronger AD PGRS associations with the MCI+ADD group than with the CN group. The subfields CA3, parasubiculum, and fimbria showed moderately higher AD PGRS associations with the MCI+ADD group than with the CN group. Our findings suggest that the eight subfield regions, which were strongly associated with AD PGRS are likely involved in the early stage ADD and a specific focus on the left hemisphere could enhance the early prediction of ADD.
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Affiliation(s)
- Balaji Kannappan
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Tamil Iniyan Gunasekaran
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Jan te Nijenhuis
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
- * E-mail: (JN); (KHL)
| | - Muthu Gopal
- Health Systems Research & MRHRU, ICMR-National Institute of Epidemiology, Tirunelveli, Tamil Nadu, India
| | - Deepika Velusami
- Department of Physiology, Sri Manakula Vinayagar Medical College and Hospital, Puducherry, Tamil Nadu, India
| | - Gugan Kothandan
- Biopolymer Modeling and Protein Chemistry Laboratory, Centre of Advanced Study in Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu, India
| | - Kun Ho Lee
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju, Republic of Korea
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
- Korea Brain Research Institute, Daegu, Republic of Korea
- * E-mail: (JN); (KHL)
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12
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Coad BM, Ghomroudi PA, Sims R, Aggleton JP, Vann SD, Metzler-Baddeley C. Apolipoprotein ε4 modifies obesity-related atrophy in the hippocampal formation of cognitively healthy adults. Neurobiol Aging 2022; 113:39-54. [PMID: 35303671 PMCID: PMC9084919 DOI: 10.1016/j.neurobiolaging.2022.02.004] [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: 11/11/2021] [Revised: 01/18/2022] [Accepted: 02/12/2022] [Indexed: 12/02/2022]
Abstract
Age-related inverted U-shaped curve of hippocampal myelin/neurite packing. Reduced hippocampal myelin/neurite packing and size/complexity in obesity. APOE modifies the effects of obesity on hippocampal size/complexity. Age-related slowing of spatial navigation but no risk effects on cognition. CA/DG predict episodic memory and subiculum predicts spatial navigation performance.
Characterizing age- and risk-related hippocampal vulnerabilities may inform about the neural underpinnings of cognitive decline. We studied the impact of three risk-factors, Apolipoprotein (APOE)-ε4, a family history of dementia, and central obesity, on the CA1, CA2/3, dentate gyrus and subiculum of 158 cognitively healthy adults (38-71 years). Subfields were labelled with the Automatic Segmentation of Hippocampal Subfields and FreeSurfer (version 6) protocols. Volumetric and microstructural measurements from quantitative magnetization transfer and Neurite Orientation Density and Dispersion Imaging were extracted for each subfield and reduced to three principal components capturing apparent myelin/neurite packing, size/complexity, and metabolism. Aging was associated with an inverse U-shaped curve on myelin/neurite packing and affected all subfields. Obesity led to reductions in myelin/neurite packing and size/complexity regardless of APOE and family history of dementia status. However, amongst individuals with a healthy Waist-Hip-Ratio, APOE ε4 carriers showed lower size/complexity than non-carriers. Segmentation protocol type did not affect this risk pattern. These findings reveal interactive effects between APOE and central obesity on the hippocampal formation of cognitively healthy adults.
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