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Alex AM, Aguate F, Botteron K, Buss C, Chong YS, Dager SR, Donald KA, Entringer S, Fair DA, Fortier MV, Gaab N, Gilmore JH, Girault JB, Graham AM, Groenewold NA, Hazlett H, Lin W, Meaney MJ, Piven J, Qiu A, Rasmussen JM, Roos A, Schultz RT, Skeide MA, Stein DJ, Styner M, Thompson PM, Turesky TK, Wadhwa PD, Zar HJ, Zöllei L, de Los Campos G, Knickmeyer RC. A global multicohort study to map subcortical brain development and cognition in infancy and early childhood. Nat Neurosci 2024; 27:176-186. [PMID: 37996530 PMCID: PMC10774128 DOI: 10.1038/s41593-023-01501-6] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 10/16/2023] [Indexed: 11/25/2023]
Abstract
The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and children born preterm or with low birthweight showed catch-up growth with age. Socioeconomic factors exerted region- and time-specific effects. Regarding cognition, males scored lower than females; preterm birth affected all developmental areas tested, and socioeconomic factors affected visual reception and receptive language. Brain-cognition correlations revealed region-specific associations.
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Affiliation(s)
- Ann M Alex
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
| | - Fernando Aguate
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
- Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, MI, USA
| | - Kelly Botteron
- Mallinickrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Claudia Buss
- Department of Medical Psychology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Yap-Seng Chong
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
| | - Stephen R Dager
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Kirsten A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Sonja Entringer
- Department of Medical Psychology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Marielle V Fortier
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Diagnostic & Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore
| | - Nadine Gaab
- Harvard Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica B Girault
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Nynke A Groenewold
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- South African Medical Research Council (SA-MRC) Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
| | - Heather Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Weili Lin
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Michael J Meaney
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore
- NUS (Suzhou) Research Institute, National University of Singapore, Suzhou, China
- The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
- Institute of Data Science, National University of Singapore, Singapore, Singapore
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
- Department of Health Technology and Informatics, Hong Kong Polytechnic University, Hung Hom, China
| | - Jerod M Rasmussen
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
| | - Annerine Roos
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Robert T Schultz
- Center for Autism Research, Children's Hospital of Philadelphia and the University of Pennsylvania, Philadelphia, PA, USA
| | - Michael A Skeide
- Research Group Learning in Early Childhood, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dan J Stein
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
- SAMRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Martin Styner
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carboro, NC, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, CA, USA
| | - Ted K Turesky
- Harvard Graduate School of Education, Harvard University, Cambridge, MA, USA
| | - Pathik D Wadhwa
- Department of Pediatrics, University of California Irvine, Irvine, CA, USA
- Development, Health and Disease Research Program, University of California Irvine, Irvine, CA, USA
- Departments of Psychiatry and Human Behavior, Obstetrics & Gynecology, Epidemiology, University of California, Irvine, Irvine, CA, USA
| | - Heather J Zar
- South African Medical Research Council (SA-MRC) Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, University of Cape Town, Faculty of Health Sciences, Cape Town, South Africa
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Gustavo de Los Campos
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA
- Departments of Epidemiology & Biostatistics, Michigan State University, East Lansing, MI, USA
- Department of Statistics & Probability, Michigan State University, East Lansing, MI, USA
| | - Rebecca C Knickmeyer
- Institute for Quantitative Health Sciences and Engineering, Michigan State University, East Lansing, MI, USA.
- Department of Pediatrics and Human Development, Michigan State University, East Lansing, MI, USA.
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Iqbal S, Leon-Rojas JE, Galovic M, Vos SB, Hammers A, de Tisi J, Koepp MJ, Duncan JS. Volumetric analysis of the piriform cortex in temporal lobe epilepsy. Epilepsy Res 2022; 185:106971. [PMID: 35810570 PMCID: PMC10510027 DOI: 10.1016/j.eplepsyres.2022.106971] [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: 08/31/2021] [Revised: 05/13/2022] [Accepted: 06/22/2022] [Indexed: 11/03/2022]
Abstract
The piriform cortex, at the confluence of the temporal and frontal lobes, generates seizures in response to chemical convulsants and electrical stimulation. Resection of more than 50% of the piriform cortex in anterior temporal lobe resection for refractory temporal lobe epilepsy (TLE) was associated with a 16-fold higher chance of seizure freedom. The objectives of the current study were to implement a robust protocol to measure piriform cortex volumes and to quantify the correlation of these volumes with clinical characteristics of TLE. Sixty individuals with unilateral TLE (33 left) and 20 healthy controls had volumetric analysis of left and right piriform cortex and hippocampi. A protocol for segmenting and measuring the volumes of the piriform cortices was implemented, with good inter-rater and test-retest reliability. The right piriform cortex volume was consistently larger than the left piriform cortex in both healthy controls and patients with TLE. In controls, the mean volume of the right piriform cortex was 17.7% larger than the left, and the right piriform cortex extended a mean of 6 mm (Range: -4 to 12) more anteriorly than the left. This asymmetry was also seen in left and right TLE. In TLE patients overall, the piriform cortices were not significantly smaller than in controls. Hippocampal sclerosis was associated with decreased ipsilateral and contralateral piriform cortex volumes. The piriform cortex volumes, both ipsilateral and contralateral to the epileptic temporal lobe, were smaller with a longer duration of epilepsy. There was no significant association between piriform cortex volumes and the frequency of focal seizures with impaired awareness or the number of anti-seizure medications taken. Implementation of robust segmentation will enable consistent neurosurgical resection in anterior temporal lobe surgery for refractory TLE..
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Affiliation(s)
- Sabahat Iqbal
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom
| | - Jose E Leon-Rojas
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom; Facultad de Ciencias Médicas de la Salud y de la Vida, Escuela de Medicina, Universidad Internacional del Ecuador, Quito, Ecuador
| | - Marian Galovic
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom; Department of Neurology, Zurich University Hospital, Zurich, Switzerland
| | - Sjoerd B Vos
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Centre for Medical Image Computing (CMIC), Department of Computer Science, University College London, United Kingdom; Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, Kings College, London, United Kingdom; Kings College London & Guys and St Thomas' PET Centre at St. Thomas' Hospital, United Kingdom
| | - Jane de Tisi
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Matthias J Koepp
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom
| | - John S Duncan
- UK National Institute for Health Research University College London Hospitals Biomedical Research Centre, and Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom; Epilepsy Society MRI Unit, Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, United Kingdom.
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André J, Barrit S, Jissendi P. Synthetic MRI for stroke: a qualitative and quantitative pilot study. Sci Rep 2022; 12:11552. [PMID: 35798771 PMCID: PMC9262877 DOI: 10.1038/s41598-022-15204-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 06/20/2022] [Indexed: 11/09/2022] Open
Abstract
Synthetic MR provides qualitative and quantitative multi-parametric data about tissue properties in a single acquisition. Its use in stroke imaging is not yet established. We compared synthetic and conventional image quality and studied synthetic relaxometry of acute and chronic ischemic lesions to investigate its interest for stroke imaging. We prospectively acquired synthetic and conventional brain MR of 43 consecutive adult patients with suspected stroke. We studied a total of 136 lesions, of which 46 DWI-positive with restricted ADC (DWI + /rADC), 90 white matter T2/FLAIR hyperintensities (WMH) showing no diffusion restriction, and 430 normal brain regions (NBR). We assessed image quality for lesion definition according to a 3-level score by two readers of different experiences. We compared relaxometry of lesions and regions of interest. Synthetic images were superior to their paired conventional images for lesion definition except for sFLAIR (sT1 or sPSIR vs. cT1 and sT2 vs. cT2 for DWI + /rADC and WMH definition; p values < .001) with substantial to almost perfect inter-rater reliability (κ ranging from 0.711 to 0.932, p values < .001). We found significant differences in relaxometry between lesions and NBR and between acute and chronic lesions (T1, T2, and PD of DWI + /rADC or WMH vs. mirror NBR; p values < .001; T1 and PD of DWI + /rADC vs. WMH; p values of 0.034 and 0.008). Synthetic MR may contribute to stroke imaging by fast generating accessible weighted images for visual inspection derived from rapidly acquired relaxometry data. Moreover, this synthetic relaxometry could differentiate acute and chronic ischemic lesions.
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Affiliation(s)
- Joachim André
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles (ULB), Route de Lennik, 808, 1070, Anderlecht, Brussels, Belgium.
| | - Sami Barrit
- Department of Neurosurgery, Hôpital Erasme, Université Libre de Bruxelles (ULB), Brussels, Belgium
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Patel NR, Setya K, Pradhan S, Lu M, Demer LL, Tintut Y. Microarchitectural Changes of Cardiovascular Calcification in Response to In Vivo Interventions Using Deep-Learning Segmentation and Computed Tomography Radiomics. Arterioscler Thromb Vasc Biol 2022; 42:e228-e241. [PMID: 35708025 PMCID: PMC9339530 DOI: 10.1161/atvbaha.122.317761] [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: 11/16/2022]
Abstract
BACKGROUND Coronary calcification associates closely with cardiovascular risk, but its progress is accelerated in response to some interventions widely used to reduce risk. This paradox suggests that qualitative, not just quantitative, changes in calcification may affect plaque stability. To determine if the microarchitecture of calcification varies with aging, Western diet, statin therapy, and high intensity, progressive exercise, we assessed changes in a priori selected computed tomography radiomic features (intensity, size, shape, and texture). METHODS Longitudinal computed tomography scans of mice (Apoe-/-) exposed to each of these conditions were autosegmented by deep learning segmentation, and radiomic features of the largest deposits were analyzed. RESULTS Over 20 weeks of aging, intensity and most size parameters increased, but surface-area-to-volume ratio (a measure of porosity) decreased, suggesting stabilization. However, texture features (coarseness, cluster tendency, and nonuniformity) increased, suggesting heterogeneity and likely destabilization. Shape parameters showed no significant changes, except sphericity, which showed a decrease. The Western diet had significant effects on radiomic features related to size and texture, but not intensity or shape. In mice undergoing either pravastatin treatment or exercise, the selected radiomic features of their computed tomography scans were not significantly different from those of their respective controls. Interestingly, the total number of calcific deposits increased significantly less in the 2 intervention groups compared with the respective controls, suggesting more coalescence and/or fewer de novo deposits. CONCLUSIONS Thus, aging and standard interventions alter the microarchitectural features of vascular calcium deposits in ways that may alter plaque biomechanical stability.
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Affiliation(s)
- Nikhil Rajesh Patel
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.)
| | - Kulveer Setya
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.)
| | - Stuti Pradhan
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.)
| | - Mimi Lu
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.)
| | - Linda L Demer
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.).,Department of Bioengineering, University of California, Los Angeles. (L.L.D.).,Department of Physiology, University of California, Los Angeles. (L.L.D., Y.T.).,VA Greater Los Angeles Healthcare System, CA (L.L.D., Y.T.)
| | - Yin Tintut
- Department of Medicine, University of California, Los Angeles. (N.R.P., K.S., S.P., M.L., L.L.D., Y.T.).,Department of Physiology, University of California, Los Angeles. (L.L.D., Y.T.).,Department of Orthopaedic Surgery, University of California, Los Angeles. (Y.T.).,VA Greater Los Angeles Healthcare System, CA (L.L.D., Y.T.)
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Kong X, Postema MC, Guadalupe T, de Kovel C, Boedhoe PSW, Hoogman M, Mathias SR, van Rooij D, Schijven D, Glahn DC, Medland SE, Jahanshad N, Thomopoulos SI, Turner JA, Buitelaar J, van Erp TGM, Franke B, Fisher SE, van den Heuvel OA, Schmaal L, Thompson PM, Francks C. Mapping brain asymmetry in health and disease through the ENIGMA consortium. Hum Brain Mapp 2022; 43:167-181. [PMID: 32420672 PMCID: PMC8675409 DOI: 10.1002/hbm.25033] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 03/18/2020] [Accepted: 04/29/2020] [Indexed: 12/18/2022] Open
Abstract
Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.
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Affiliation(s)
- Xiang‐Zhen Kong
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
| | - Merel C. Postema
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
| | - Tulio Guadalupe
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
| | - Carolien de Kovel
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
| | - Premika S. W. Boedhoe
- Department of Psychiatry, Amsterdam NeuroscienceAmsterdam University Medical Center, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam University Medical CenterVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Martine Hoogman
- Department of Human GeneticsRadboud University Medical CenterNijmegenThe Netherlands
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CentreNijmegenThe Netherlands
| | - Samuel R. Mathias
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Daan van Rooij
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CentreNijmegenThe Netherlands
| | - Dick Schijven
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
| | - David C. Glahn
- Department of PsychiatryBoston Children's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
- Olin Neuropsychiatry Research CenterInstitute of Living, Hartford HospitalHartfordConnecticutUSA
| | - Sarah E. Medland
- Psychiatric GeneticsQIMR Berghofer Medical Research InstituteBrisbaneQueenslandAustralia
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics InstituteKeck School of Medicine of the University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics InstituteKeck School of Medicine of the University of Southern CaliforniaMarina del ReyCaliforniaUSA
| | - Jessica A. Turner
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, Emory UniversityAtlantaGeorgiaUSA
- Department of Psychology and NeuroscienceGeorgia State UniversityAtlantaGeorgiaUSA
| | - Jan Buitelaar
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CentreNijmegenThe Netherlands
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CentreNijmegenThe Netherlands
- Karakter Child and Adolescent PsychiatryNijmegenThe Netherlands
| | - Theo G. M. van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human BehaviorUniversity of California IrvineIrvineCaliforniaUSA
- Center for the Neurobiology of Learning and MemoryUniversity of California IrvineIrvineCaliforniaUSA
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenThe Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and BehaviourRadboud University Medical CenterNijmegenThe Netherlands
| | - Simon E. Fisher
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenThe Netherlands
| | - Odile A. van den Heuvel
- Department of Psychiatry, Amsterdam NeuroscienceAmsterdam University Medical Center, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam University Medical CenterVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental HealthParkvilleVictoriaAustralia
- Centre for Youth Mental HealthThe University of MelbourneMelbourneVictoriaAustralia
| | - Paul M. Thompson
- Tri‐institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS)Georgia State University, Georgia Institute of Technology, Emory UniversityAtlantaGeorgiaUSA
| | - Clyde Francks
- Language and Genetics DepartmentMax Planck Institute for PsycholinguisticsNijmegenThe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenThe Netherlands
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6
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Moog NK, Nolvi S, Kleih TS, Styner M, Gilmore JH, Rasmussen JM, Heim CM, Entringer S, Wadhwa PD, Buss C. Prospective association of maternal psychosocial stress in pregnancy with newborn hippocampal volume and implications for infant social-emotional development. Neurobiol Stress 2021; 15:100368. [PMID: 34355050 PMCID: PMC8319845 DOI: 10.1016/j.ynstr.2021.100368] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 06/30/2021] [Accepted: 07/15/2021] [Indexed: 02/06/2023] Open
Abstract
Maternal psychosocial stress during pregnancy can impact the developing fetal brain and influence offspring mental health. In this context, animal studies have identified the hippocampus and amygdala as key brain regions of interest, however, evidence in humans is sparse. We, therefore, examined the associations between maternal prenatal psychosocial stress, newborn hippocampal and amygdala volumes, and child social-emotional development. In a sample of 86 mother-child dyads, maternal perceived stress was assessed serially in early, mid and late pregnancy. Following birth, newborn (aged 5–64 postnatal days, mean: 25.8 ± 12.9) hippocampal and amygdala volume was assessed using structural magnetic resonance imaging. Infant social-emotional developmental milestones were assessed at 6- and 12-months age using the Bayley-III. After adjusting for covariates, maternal perceived stress during pregnancy was inversely associated with newborn left hippocampal volume (β = −0.26, p = .019), but not with right hippocampal (β = −0.170, p = .121) or bilateral amygdala volumes (ps > .5). Furthermore, newborn left hippocampal volume was positively associated with infant social-emotional development across the first year of postnatal life (B = 0.01, p = .011). Maternal perceived stress was indirectly associated with infant social-emotional development via newborn left hippocampal volume (B = −0.34, 95% CIBC [-0.97, −0.01]), suggesting mediation. This study provides prospective evidence in humans linking maternal psychosocial stress in pregnancy with newborn hippocampal volume and subsequent infant social-emotional development across the first year of life. These findings highlight the importance of maternal psychosocial state during pregnancy as a target amenable to interventions to prevent or attenuate its potentially unfavorable neural and behavioral consequences in the offspring. Maternal perceived stress predicted smaller neonatal left hippocampal volume (HCV). Neonatal left HCV was positively associated with infant social-emotional function. Variation in HCV may mediate maternal stress-related effects on child mental health.
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Affiliation(s)
- Nora K Moog
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Saara Nolvi
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany.,Turku Institute for Advanced Studies, Department of Psychology and Speech-Language Pathology, University of Turku, Finland
| | - Theresa S Kleih
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany.,Institute of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Martin Styner
- Departments of Psychiatry and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jerod M Rasmussen
- Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA
| | - Christine M Heim
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany.,Department of Biobehavioral Health, Pennsylvania State University, College of Health and Human Development, University Park, PA, USA
| | - Sonja Entringer
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany.,Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA.,Department of Pediatrics, University of California, Irvine, School of Medicine, Orange, CA, USA
| | - Pathik D Wadhwa
- Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA.,Department of Pediatrics, University of California, Irvine, School of Medicine, Orange, CA, USA.,Departments of Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Orange, CA, USA
| | - Claudia Buss
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Medical Psychology, Augustenburger Platz 1, 13353, Berlin, Germany.,Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA.,Department of Pediatrics, University of California, Irvine, School of Medicine, Orange, CA, USA
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7
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Development of a protocol to assess within-subject, regional white matter hyperintensity changes in aging and dementia. J Neurosci Methods 2021; 360:109270. [PMID: 34171312 DOI: 10.1016/j.jneumeth.2021.109270] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 06/14/2021] [Accepted: 06/18/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND White matter hyperintensities (WMH), associated with both dementia risk and progression, can individually progress, remain stable, or even regress influencing cognitive decline related to specific cerebrovascular-risks. This study details the development and validation of a registration protocol to assess regional, within-subject, longitudinal WMH changes (ΔWMH) that is currently lacking in the field. NEW METHOD 3D-FLAIR images (baseline and one-year-visit) were used for protocol development and validation. The method was validated by assessing the correlation between forward and reverse longitudinal registration, and between summated regional progression-regression volumes and Global ΔWMH. The clinical relevance of growth-regression ΔWMH were explored in relation to an executive function test. RESULTS MRI scans for 79 participants (73.5 ± 8.8 years) were used in this study. Global ΔWMH vs. summated regional progression-regression volumes were highly associated (r2 = 0.90; p-value < 0.001). Bi-directional registration validated the registration method (r2 = 0.999; p-value < 0.001). Growth and regression, but not overall ΔWMH, were associated with one-year declines in performance on Trial-Making-Test-B. COMPARISON WITH EXISTING METHOD(S) This method presents a unique registration protocol for maximum tissue alignment, demonstrating three distinct patterns of longitudinal within-subject ΔWMH (stable, growth and regression). CONCLUSIONS These data detail the development and validation of a registration protocol for use in assessing within-subject, voxel-level alterations in WMH volume. The methods developed for registration and intensity correction of longitudinal within-subject FLAIR images allow regional and within-lesion characterization of longitudinal ΔWMH. Assessing the impact of associated cerebrovascular-risks and longitudinal clinical changes in relation to dynamic regional ΔWMH is needed in future studies.
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8
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Texture-based markers from structural imaging correlate with motor handicap in Parkinson's disease. Sci Rep 2021; 11:2724. [PMID: 33526820 PMCID: PMC7851138 DOI: 10.1038/s41598-021-81209-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/28/2020] [Indexed: 01/17/2023] Open
Abstract
There is a growing need for surrogate biomarkers for Parkinson’s disease (PD). Structural analysis using magnetic resonance imaging with T1-weighted sequences has the potential to quantify histopathological changes. Degeneration is typically measured by the volume and shape of morphological changes. However, these changes appear late in the disease, preventing their use as surrogate markers. We investigated texture changes in 108 individuals, divided into three groups, matched in terms of sex and age: (1) healthy controls (n = 32); (2) patients with early-stage PD (n = 39); and (3) patients with late-stage PD and severe L-dopa-related complications (n = 37). All patients were assessed in off-treatment conditions. Statistical analysis of first- and second-order texture features was conducted in the substantia nigra, striatum, thalamus and sub-thalamic nucleus. Regions of interest volumetry and voxel-based morphometry were performed for comparison. Significantly different texture features were observed between the three populations, with some showing a gradual linear progression between the groups. The volumetric changes in the two PD patient groups were not significantly different. Texture features were significantly associated with clinical scores for motor handicap. These results suggest that texture features, measured in the nigrostriatal pathway at PD diagnosis, may be useful in predicting clinical progression of motor handicap.
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9
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Mu SH, Yuan BK, Tan LH. Effect of Gender on Development of Hippocampal Subregions From Childhood to Adulthood. Front Hum Neurosci 2020; 14:611057. [PMID: 33343321 PMCID: PMC7744655 DOI: 10.3389/fnhum.2020.611057] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Accepted: 11/09/2020] [Indexed: 11/28/2022] Open
Abstract
The hippocampus is known to be comprised of several subfields, but the developmental trajectories of these subfields are under debate. In this study, we analyzed magnetic resonance imaging (MRI) data from a cross-sectional sample (198 healthy Chinese) using an automated segmentation tool to delineate the development of the hippocampal subregions from 6 to 26 years of age. We also examined whether gender and hemispheric differences influence the development of these subregions. For the whole hippocampus, the trajectory of development was observed to be an inverse-u. A significant increase in volume with age was found for most of the subregions, except for the L/R-parasubiculum, L/R-fimbria, and L-HATA. Gender-related differences were also found in the development of most subregions, especially for the hippocampal tail, CA1, molecular layer HP, GC-DG, CA3, and CA4, which showed a consistent increase in females and an early increase followed by a decrease in males. A comparison of the average volumes showed that the right whole hippocampus was significantly larger, along with the R-presubiculum, R-hippocampal-fissure, L/R-CA1, and L/R-molecular layer HP in males in comparison to females. Additionally, the average volume of the right hemisphere was shown to be significantly larger for the hippocampal tail, CA1, molecular layer HP, GC-DG, CA3, and CA4. However, for the presubiculum, parasubiculum, and fimbria, the left side was shown to be larger. In conclusion, the hippocampal subregions appear to develop in various ways from childhood to adulthood, with both gender and hemispheric differences affecting their development.
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Affiliation(s)
- Shu Hua Mu
- School of Psychology, Shenzhen University, Shenzhen, China
| | - Bin Ke Yuan
- Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Li Hai Tan
- Shenzhen Institute of Neuroscience, Shenzhen, China
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10
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Nolvi S, Rasmussen JM, Graham AM, Gilmore JH, Styner M, Fair DA, Entringer S, Wadhwa PD, Buss C. Neonatal brain volume as a marker of differential susceptibility to parenting quality and its association with neurodevelopment across early childhood. Dev Cogn Neurosci 2020; 45:100826. [PMID: 32807730 PMCID: PMC7393458 DOI: 10.1016/j.dcn.2020.100826] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 06/17/2020] [Accepted: 07/08/2020] [Indexed: 02/06/2023] Open
Abstract
Parenting quality is associated with child cognitive and executive functions (EF), which are important predictors of social and academic development. However, children vary in their susceptibility to parenting behaviors, and the neurobiological underpinnings of this susceptibility are poorly understood. In a prospective longitudinal study, we examined whether neonatal total brain volume (TBV) and subregions of interest (i.e., hippocampus (HC) and anterior cingulate gyrus (ACG)) moderate the association between maternal sensitivity and cognitive/EF development across early childhood. Neonates underwent a brain magnetic resonance imaging scan. Their cognitive performance and EF was characterized at 2.0 ± 0.1 years (N = 53) and at 4.9 ± 0.8 years (N = 36) of age. Maternal sensitivity was coded based on observation of a standardized play situation at 6-mo postpartum. Neonatal TBV moderated the association between maternal sensitivity and 2-year working memory as well as all 5-year cognitive outcomes, suggesting that the positive association between maternal sensitivity and child cognition was observed only among children with large or average but not small TBV as neonates. Similar patterns were observed for TBV-corrected HC and ACG volumes. The findings suggest that larger neonatal TBV, HC and ACG may underlie susceptibility to the environment and affect the degree to which parenting quality shapes long-term cognitive development.
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Affiliation(s)
- Saara Nolvi
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Medical Psychology
| | - Jerod M Rasmussen
- Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA
| | - Alice M Graham
- The Department of Behavioral Neuroscience and the Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Martin Styner
- Departments of Psychiatry and Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Damien A Fair
- The Department of Behavioral Neuroscience and the Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Sonja Entringer
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Medical Psychology; Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA
| | - Pathik D Wadhwa
- Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA
| | - Claudia Buss
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Medical Psychology; Development, Health, and Disease Research Program, Departments of Pediatrics, Psychiatry and Human Behavior, Obstetrics and Gynecology, and Epidemiology, University of California, Irvine, School of Medicine, Irvine, CA, USA.
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11
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Ardekani BA, Izadi NO, Hadid SA, Meftah AM, Bachman AH. Effects of sex, age, and apolipoprotein E genotype on hippocampal parenchymal fraction in cognitively normal older adults. Psychiatry Res Neuroimaging 2020; 301:111107. [PMID: 32416384 DOI: 10.1016/j.pscychresns.2020.111107] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2020] [Revised: 03/24/2020] [Accepted: 04/15/2020] [Indexed: 10/24/2022]
Abstract
Early detection of Alzheimer's disease (AD) is important for timely interventions and developing new treatments. Hippocampus atrophy is an early biomarker of AD. The hippocampal parenchymal fraction (HPF) is a promising measure of hippocampal structural integrity computed from structural MRI. It is important to characterize the dependence of HPF on covariates such as age and sex in the normal population to enhance its utility as a disease biomarker. We measured the HPF in 4239 structural MRI scans from 340 cognitively normal (CN) subjects aged 59-89 years from the AD Neuroimaging Initiative database, and studied its dependence on age, sex, apolipoprotein E (APOE) genotype, brain hemisphere, intracranial volume (ICV), and education using a linear mixed-effects model. In this CN cohort, HPF was inversely associated with ICV; was greater on the right hemisphere compared to left in both sexes with the degree of right > left asymmetry being slightly more pronounced in men; declined quadratically with age and faster in APOE ϵ4 carriers compared to non-carriers; and was significantly associated with cognitive ability. Consideration of HPF as an AD biomarker should be in conjunction with other subject attributes that are shown in this research to influence HPF levels in CN older individuals.
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Affiliation(s)
- Babak A Ardekani
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Psychiatry, New York University School of Medicine, New York, NY, USA.
| | - Neema O Izadi
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Somar A Hadid
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Amir M Meftah
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Alvin H Bachman
- Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
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12
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Liu Y, Nacewicz BM, Zhao G, Adluru N, Kirk GR, Ferrazzano PA, Styner MA, Alexander AL. A 3D Fully Convolutional Neural Network With Top-Down Attention-Guided Refinement for Accurate and Robust Automatic Segmentation of Amygdala and Its Subnuclei. Front Neurosci 2020; 14:260. [PMID: 32508558 PMCID: PMC7253589 DOI: 10.3389/fnins.2020.00260] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Accepted: 03/09/2020] [Indexed: 12/17/2022] Open
Abstract
Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorders. However, most existing deep learning based approaches in neuroimaging do not investigate the specific difficulties that exist in segmenting extremely small but important brain regions such as the subnuclei of the amygdala. To tackle this challenging task, we developed a dual-branch dilated residual 3D fully convolutional network with parallel convolutions to extract more global context and alleviate the class imbalance issue by maintaining a small receptive field that is just the size of the regions of interest (ROIs). We also conduct multi-scale feature fusion in both parallel and series to compensate the potential information loss during convolutions, which has been shown to be important for small objects. The serial feature fusion enabled by residual connections is further enhanced by a proposed top-down attention-guided refinement unit, where the high-resolution low-level spatial details are selectively integrated to complement the high-level but coarse semantic information, enriching the final feature representations. As a result, the segmentations resulting from our method are more accurate both volumetrically and morphologically, compared with other deep learning based approaches. To the best of our knowledge, this work is the first deep learning-based approach that targets the subregions of the amygdala. We also demonstrated the feasibility of using a cycle-consistent generative adversarial network (CycleGAN) to harmonize multi-site MRI data, and show that our method generalizes well to challenging traumatic brain injury (TBI) datasets collected from multiple centers. This appears to be a promising strategy for image segmentation for multiple site studies and increased morphological variability from significant brain pathology.
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Affiliation(s)
- Yilin Liu
- Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
| | - Brendon M. Nacewicz
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
| | - Gengyan Zhao
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
| | - Gregory R. Kirk
- Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
| | - Peter A. Ferrazzano
- Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States
| | - Martin A. Styner
- Department of Psychiatry, University of North Carolina-Chapel Hill, Chapel Hill, NC, United States
- Department of Computer Science, University of North Carolina-Chapel Hill, Chapel Hill, NC, United States
| | - Andrew L. Alexander
- Waisman Brain Imaging Laboratory, University of Wisconsin-Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
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13
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Ardekani BA, Hadid SA, Blessing E, Bachman AH. Sexual Dimorphism and Hemispheric Asymmetry of Hippocampal Volumetric Integrity in Normal Aging and Alzheimer Disease. AJNR Am J Neuroradiol 2019; 40:276-282. [PMID: 30655257 DOI: 10.3174/ajnr.a5943] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2018] [Accepted: 12/09/2018] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Asymmetric atrophy of the hippocampus is an important clinical finding in normal aging and Alzheimer disease. In this study, we investigate the associations between the magnitude and asymmetry of hippocampal volumetric integrity and age, sex, and dementia severity. MATERIALS AND METHODS We have recently developed a rapid fully automatic algorithm to measure the hippocampal parenchymal fraction, an index of hippocampal volumetric integrity on structural MR imaging of the brain. We applied this algorithm to measure the hippocampal parenchymal fraction bilaterally on 775 MR imaging volumes scanned from 198 volunteers in a publicly available data base. All subjects were right-handed and older than 60 years of age. Subjects were categorized as cognitively healthy (n = 98), with mild cognitive impairment (n = 70), or with mild/moderate Alzheimer disease (n = 30). We used linear mixed-effects models to analyze the hippocampal parenchymal fraction and its asymmetry with respect to age, sex, dementia severity, and intracranial volume. RESULTS After controlling for age, sex, and intracranial volume, we found that the magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with dementia severity. Also, hippocampal parenchymal fraction asymmetry was significantly higher in men after controlling for all other variables, but there was no sex effect on hippocampal parenchymal fraction magnitude. The magnitude of the hippocampal parenchymal fraction decreased and its asymmetry increased significantly with age in subjects who were cognitively healthy, but associations with age were different in nature in the mild cognitive impairment and Alzheimer disease groups. CONCLUSIONS Hippocampal atrophy progresses asymmetrically with age in cognitively healthy subjects. Hippocampal parenchymal fraction asymmetry is significantly higher in men than women and in mild cognitive impairment/Alzheimer disease relative to cognitively healthy individuals.
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Affiliation(s)
- B A Ardekani
- From Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research (B.A.A., S.A.H., A.H.B.), Orangeburg, New York
- Department of Psychiatry (B.A.A., E.B.), New York University School of Medicine, New York, New York
| | - S A Hadid
- From Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research (B.A.A., S.A.H., A.H.B.), Orangeburg, New York
| | - E Blessing
- Department of Psychiatry (B.A.A., E.B.), New York University School of Medicine, New York, New York
| | - A H Bachman
- From Center for Brain Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research (B.A.A., S.A.H., A.H.B.), Orangeburg, New York
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14
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Herten A, Konrad K, Krinzinger H, Seitz J, von Polier GG. Accuracy and bias of automatic hippocampal segmentation in children and adolescents. Brain Struct Funct 2018; 224:795-810. [DOI: 10.1007/s00429-018-1802-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 11/24/2018] [Indexed: 11/30/2022]
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15
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Pereira LP, Köhler CA, Stubbs B, Miskowiak KW, Morris G, de Freitas BP, Thompson T, Fernandes BS, Brunoni AR, Maes M, Pizzagalli DA, Carvalho AF. Imaging genetics paradigms in depression research: Systematic review and meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry 2018; 86:102-113. [PMID: 29778546 PMCID: PMC6240165 DOI: 10.1016/j.pnpbp.2018.05.012] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2017] [Revised: 05/15/2018] [Accepted: 05/16/2018] [Indexed: 12/29/2022]
Abstract
Imaging genetics studies involving participants with major depressive disorder (MDD) have expanded. Nevertheless, findings have been inconsistent. Thus, we conducted a systematic review and meta-analysis of imaging genetics studies that enrolled MDD participants across major databases through June 30th, 2017. Sixty-five studies met eligibility criteria (N = 4034 MDD participants and 3293 controls), and there was substantial between-study variability in the methodological quality of included studies. However, few replicated findings emerged from this literature with only 22 studies providing data for meta-analyses (882 participants with MDD and 616 controls). Total hippocampal volumes did not significantly vary in MDD participants or controls carrying either the BDNF Val66Met 'Met' (386 participants with MDD and 376 controls) or the 5-HTTLPR short 'S' (310 participants with MDD and 230 controls) risk alleles compared to non-carriers. Heterogeneity across studies was explored through meta-regression and subgroup analyses. Gender distribution, the use of medications, segmentation methods used to measure the hippocampus, and age emerged as potential sources of heterogeneity across studies that assessed the association of 5-HTTLPR short 'S' alleles and hippocampal volumes. Our data also suggest that the methodological quality of included studies, publication year, and the inclusion of brain volume as a covariate contributed to the heterogeneity of studies that assessed the association of the BDNF Val66Met 'Met' risk allele and hippocampal volumes. In exploratory voxel-wise meta-analyses, MDD participants carrying the 5-HTTLPR short 'S' allele had white matter microstructural abnormalities predominantly in the corpus callosum, while carriers of the BDNF Val66Met 'Met' allele had larger gray matter volumes and hyperactivation of the right middle frontal gyrus compared to non-carriers. In conclusion, few replicated findings emerged from imaging genetics studies that included participants with MDD. Nevertheless, we explored and identified specific sources of heterogeneity across studies, which could provide insights to enhance the reproducibility of this emerging field.
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Affiliation(s)
- Lícia P Pereira
- Department of Clinical Medicine, Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil; Centre for Addiction & Mental Health (CAMH), Toronto, ON, Canada
| | - Cristiano A Köhler
- Department of Clinical Medicine, Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
| | - Brendon Stubbs
- Institute for Clinical Research and Education in Medicine (IREM), Padova, Italy; South London and Maudsley NHS Foundation Trust, Denmark Hill, London SE5 8AZ, United Kingdom; Psychology and Neuroscience (IoPPN), King's College London, Institute of Psychiatry,De Crespigny Park, London SE5 8 AF, United Kingdom; Faculty of Health, Social Care and Education, Anglia Ruskin University, Chelmsford CM1 1SQ, United Kingdom
| | - Kamilla W Miskowiak
- Copenhagen Affective Disorders Research Centre, Copenhagen Psychiatric Centre, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - Gerwyn Morris
- IMPACT Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, Australia
| | - Bárbara P de Freitas
- Department of Clinical Medicine, Translational Psychiatry Research Group, Faculty of Medicine, Federal University of Ceará, Fortaleza, CE, Brazil
| | - Trevor Thompson
- Faculty of Education and Health, University of Greenwich, London, United Kingdom
| | - Brisa S Fernandes
- IMPACT Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, Australia; Department of Biochemistry, Laboratory of Calcium Binding Proteins in the Central Nervous System, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
| | - André R Brunoni
- Department and Institute of Psychiatry, Service of Interdisciplinary Neuromodulation, Laboratory of Neurosciences (LIM-27), Interdisciplinary Center for Applied Neuromodulation University Hospital, University of São Paulo, São Paulo, Brazil
| | - Michael Maes
- IMPACT Strategic Research Centre, School of Medicine, Barwon Health, Deakin University, Geelong, Australia; Department of Psychiatry, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Department of Psychiatry, Medical University of Plovdiv, Plovdiv, Bulgaria
| | - Diego A Pizzagalli
- Department of Psychiatry, Harvard Medical School, Belmont, MA 02478, USA; McLean Hospital, Belmont, MA 02478, USA
| | - André F Carvalho
- McLean Hospital, Belmont, MA 02478, USA; Department of Psychiatry, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
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16
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Fraser MA, Shaw ME, Anstey KJ, Cherbuin N. Longitudinal Assessment of Hippocampal Atrophy in Midlife and Early Old Age: Contrasting Manual Tracing and Semi-automated Segmentation (FreeSurfer). Brain Topogr 2018; 31:949-962. [PMID: 29974288 DOI: 10.1007/s10548-018-0659-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 06/29/2018] [Indexed: 01/26/2023]
Abstract
It is important to have accurate estimates of normal age-related brain structure changes and to understand how the choice of measurement technique may bias those estimates. We compared longitudinal change in hippocampal volume, laterality and atrophy measured by manual tracing and FreeSurfer (version 5.3) in middle age (n = 244, 47.2[1.4] years) and older age (n = 199, 67.0[1.4] years) individuals over 8 years. The proportion of overlap (Dice coefficient) between the segmented hippocampi was calculated and we hypothesised that the proportion of overlap would be higher for older individuals as a consequence of higher atrophy. Hippocampal volumes produced by FreeSurfer were larger than manually traced volumes. Both methods produced a left less than right volume laterality difference. Over time this laterality difference increased for manual tracing and decreased for FreeSurfer leading to laterality differences in left and right estimated atrophy rates. The overlap proportion between methods was not significantly different for older individuals, but was greater for the right hippocampus. Estimated middle age annualised atrophy rates were - 0.39(1.0) left, 0.07(1.01) right, - 0.17(0.88) total for manual tracing and - 0.15(0.69) left, - 0.20(0.63) right, - 0.18(0.57) total for FreeSurfer. Older age atrophy rates were - 0.43(1.32) left, - 0.15(1.41) right, - 0.30 (1.23) total for manual tracing and - 0.34(0.79) left, - 0.68(0.78) right, - 0.51(0.65) total for FreeSurfer. FreeSurfer reliably segments the hippocampus producing atrophy rates that are comparable to manual tracing with some biases that need to be considered in study design. FreeSurfer is suited for use in large longitudinal studies where it is not cost effective to use manual tracing.
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Affiliation(s)
- Mark A Fraser
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Florey, Building 54, Mills Road, Canberra, ACT, 2601, Australia.
| | - Marnie E Shaw
- College of Engineering & Computer Science, Australian National University, Brian Anderson Building 115, 115 North Road, Canberra, ACT, 2601, Australia
| | - Kaarin J Anstey
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Florey, Building 54, Mills Road, Canberra, ACT, 2601, Australia
| | - Nicolas Cherbuin
- Centre for Research on Ageing, Health and Wellbeing, Australian National University, Florey, Building 54, Mills Road, Canberra, ACT, 2601, Australia
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17
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Milne NT, Bucks RS, Davis WA, Davis TME, Pierson R, Starkstein SE, Bruce DG. Hippocampal atrophy, asymmetry, and cognition in type 2 diabetes mellitus. Brain Behav 2018; 8:e00741. [PMID: 29568674 PMCID: PMC5853633 DOI: 10.1002/brb3.741] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2016] [Revised: 04/13/2017] [Accepted: 04/20/2017] [Indexed: 11/05/2022] Open
Abstract
INTRODUCTION Type 2 diabetes mellitus is associated with global and hippocampal atrophy and cognitive deficits, and some studies suggest that the right hippocampus may display greater vulnerability than the left. METHODS Hippocampal volumes, the hippocampal asymmetry index, and cognitive functioning were assessed in 120 nondemented adults with long duration type 2 diabetes. RESULTS The majority of the sample displayed left greater than right hippocampal asymmetry (which is the reverse of the expected direction seen with normal aging). After adjustment for age, sex, and IQ, right (but not left) hippocampal volumes were negatively associated with memory, executive function, and semantic fluency. These associations were stronger with the hippocampal asymmetry index and remained significant for memory and executive function after additional adjustment for global brain atrophy. CONCLUSIONS We conclude that asymmetric hippocampal atrophy may occur in type 2 diabetes, with greater atrophy occurring in the right than the left hippocampus, and that this may contribute to cognitive impairment in this disorder. These cross-sectional associations require further verification but may provide clues into the pathogenesis of cognitive disorders in type 2 diabetes.
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Affiliation(s)
- Nicole T Milne
- School of Psychology University of Western Australia Western Australia Australia
| | - Romola S Bucks
- School of Psychology University of Western Australia Western Australia Australia
| | - Wendy A Davis
- School of Medicine & Pharmacology University of Western Australia Western Australia Australia
| | - Timothy M E Davis
- School of Medicine & Pharmacology University of Western Australia Western Australia Australia
| | - Ronald Pierson
- Brain Image Analysis Technology Innovation Center Coralville IA USA
| | - Sergio E Starkstein
- School of Psychiatry & Clinical Neuroscience University of Western Australia Western Australia Australia
| | - David G Bruce
- School of Medicine & Pharmacology University of Western Australia Western Australia Australia
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18
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Velasco-Annis C, Akhondi-Asl A, Stamm A, Warfield SK. Reproducibility of Brain MRI Segmentation Algorithms: Empirical Comparison of Local MAP PSTAPLE, FreeSurfer, and FSL-FIRST. J Neuroimaging 2017; 28:162-172. [PMID: 29134725 DOI: 10.1111/jon.12483] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 10/06/2017] [Accepted: 10/16/2017] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND PURPOSE Segmentation of human brain structures is crucial for the volumetric quantification of brain disease. Advances in algorithmic approaches have led to automated techniques that save time compared to interactive methods. Recently, the utility and accuracy of template library fusion algorithms, such as Local MAP PSTAPLE (PSTAPLE), have been demonstrated but there is little guidance regarding its reproducibility compared to single template-based algorithms such as FreeSurfer and FSL-FIRST. METHODS Eight repeated magnetic resonance imagings of 20 subjects were segmented using FreeSurfer, FSL-FIRST, and PSTAPLE. We reported the reproducibility of segmentation-derived volume measurements for brain structures and calculated sample size estimates for detecting hypothetical rates of tissue atrophy given the observed variances. RESULTS PSTAPLE had the most reproducible volume measurements for hippocampus, putamen, thalamus, caudate, pallidum, amygdala, Accumbens area, and cortical regions. FreeSurfer was most reproducible for brainstem. PSTAPLE was the most accurate algorithm in terms of several metrics include Dice's coefficient. The sample size estimates showed that a study utilizing PSTAPLE would require tens to hundreds less subjects than the other algorithms for detecting atrophy rates typically observed in brain disease. CONCLUSIONS PSTAPLE is a useful tool for automatic human brain segmentation due to its precision and accuracy, which enable the detection of the size of the effect typically reported for neurological disorders with a substantially reduced sample size, in comparison to the other tools we assessed. This enables randomized controlled trials to be executed with reduced cost and duration, in turn, facilitating the assessment of new therapeutic interventions.
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Affiliation(s)
- Clemente Velasco-Annis
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA
| | - Alireza Akhondi-Asl
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA
| | - Aymeric Stamm
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA
| | - Simon K Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, and Harvard Medical School, Boston, MA
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19
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Discrete pre-processing step effects in registration-based pipelines, a preliminary volumetric study on T1-weighted images. PLoS One 2017; 12:e0186071. [PMID: 29023597 PMCID: PMC5638331 DOI: 10.1371/journal.pone.0186071] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 09/25/2017] [Indexed: 01/18/2023] Open
Abstract
Pre-processing MRI scans prior to performing volumetric analyses is common practice in MRI studies. As pre-processing steps adjust the voxel intensities, the space in which the scan exists, and the amount of data in the scan, it is possible that the steps have an effect on the volumetric output. To date, studies have compared between and not within pipelines, and so the impact of each step is unknown. This study aims to quantify the effects of pre-processing steps on volumetric measures in T1-weighted scans within a single pipeline. It was our hypothesis that pre-processing steps would significantly impact ROI volume estimations. One hundred fifteen participants from the OASIS dataset were used, where each participant contributed three scans. All scans were then pre-processed using a step-wise pipeline. Bilateral hippocampus, putamen, and middle temporal gyrus volume estimations were assessed following each successive step, and all data were processed by the same pipeline 5 times. Repeated-measures analyses tested for a main effects of pipeline step, scan-rescan (for MRI scanner consistency) and repeated pipeline runs (for algorithmic consistency). A main effect of pipeline step was detected, and interestingly an interaction between pipeline step and ROI exists. No effect for either scan-rescan or repeated pipeline run was detected. We then supply a correction for noise in the data resulting from pre-processing.
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20
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Guadalupe T, Mathias SR, vanErp TGM, Whelan CD, Zwiers MP, Abe Y, Abramovic L, Agartz I, Andreassen OA, Arias-Vásquez A, Aribisala BS, Armstrong NJ, Arolt V, Artiges E, Ayesa-Arriola R, Baboyan VG, Banaschewski T, Barker G, Bastin ME, Baune BT, Blangero J, Bokde ALW, Boedhoe PSW, Bose A, Brem S, Brodaty H, Bromberg U, Brooks S, Büchel C, Buitelaar J, Calhoun VD, Cannon DM, Cattrell A, Cheng Y, Conrod PJ, Conzelmann A, Corvin A, Crespo-Facorro B, Crivello F, Dannlowski U, de Zubicaray GI, de Zwarte SMC, Deary IJ, Desrivières S, Doan NT, Donohoe G, Dørum ES, Ehrlich S, Espeseth T, Fernández G, Flor H, Fouche JP, Frouin V, Fukunaga M, Gallinat J, Garavan H, Gill M, Suarez AG, Gowland P, Grabe HJ, Grotegerd D, Gruber O, Hagenaars S, Hashimoto R, Hauser TU, Heinz A, Hibar DP, Hoekstra PJ, Hoogman M, Howells FM, Hu H, Hulshoff Pol HE, Huyser C, Ittermann B, Jahanshad N, Jönsson EG, Jurk S, Kahn RS, Kelly S, Kraemer B, Kugel H, Kwon JS, Lemaitre H, Lesch KP, Lochner C, Luciano M, Marquand AF, Martin NG, Martínez-Zalacaín I, Martinot JL, Mataix-Cols D, Mather K, McDonald C, McMahon KL, Medland SE, Menchón JM, Morris DW, Mothersill O, Maniega SM, Mwangi B, et alGuadalupe T, Mathias SR, vanErp TGM, Whelan CD, Zwiers MP, Abe Y, Abramovic L, Agartz I, Andreassen OA, Arias-Vásquez A, Aribisala BS, Armstrong NJ, Arolt V, Artiges E, Ayesa-Arriola R, Baboyan VG, Banaschewski T, Barker G, Bastin ME, Baune BT, Blangero J, Bokde ALW, Boedhoe PSW, Bose A, Brem S, Brodaty H, Bromberg U, Brooks S, Büchel C, Buitelaar J, Calhoun VD, Cannon DM, Cattrell A, Cheng Y, Conrod PJ, Conzelmann A, Corvin A, Crespo-Facorro B, Crivello F, Dannlowski U, de Zubicaray GI, de Zwarte SMC, Deary IJ, Desrivières S, Doan NT, Donohoe G, Dørum ES, Ehrlich S, Espeseth T, Fernández G, Flor H, Fouche JP, Frouin V, Fukunaga M, Gallinat J, Garavan H, Gill M, Suarez AG, Gowland P, Grabe HJ, Grotegerd D, Gruber O, Hagenaars S, Hashimoto R, Hauser TU, Heinz A, Hibar DP, Hoekstra PJ, Hoogman M, Howells FM, Hu H, Hulshoff Pol HE, Huyser C, Ittermann B, Jahanshad N, Jönsson EG, Jurk S, Kahn RS, Kelly S, Kraemer B, Kugel H, Kwon JS, Lemaitre H, Lesch KP, Lochner C, Luciano M, Marquand AF, Martin NG, Martínez-Zalacaín I, Martinot JL, Mataix-Cols D, Mather K, McDonald C, McMahon KL, Medland SE, Menchón JM, Morris DW, Mothersill O, Maniega SM, Mwangi B, Nakamae T, Nakao T, Narayanaswaamy JC, Nees F, Nordvik JE, Onnink AMH, Opel N, Ophoff R, Paillère Martinot ML, Papadopoulos Orfanos D, Pauli P, Paus T, Poustka L, Reddy JY, Renteria ME, Roiz-Santiáñez R, Roos A, Royle NA, Sachdev P, Sánchez-Juan P, Schmaal L, Schumann G, Shumskaya E, Smolka MN, Soares JC, Soriano-Mas C, Stein DJ, Strike LT, Toro R, Turner JA, Tzourio-Mazoyer N, Uhlmann A, Hernández MV, van den Heuvel OA, van der Meer D, van Haren NEM, Veltman DJ, Venkatasubramanian G, Vetter NC, Vuletic D, Walitza S, Walter H, Walton E, Wang Z, Wardlaw J, Wen W, Westlye LT, Whelan R, Wittfeld K, Wolfers T, Wright MJ, Xu J, Xu X, Yun JY, Zhao J, Franke B, Thompson PM, Glahn DC, Mazoyer B, Fisher SE, Francks C. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex. Brain Imaging Behav 2017; 11:1497-1514. [PMID: 27738994 PMCID: PMC5540813 DOI: 10.1007/s11682-016-9629-z] [Show More Authors] [Citation(s) in RCA: 118] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.
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Affiliation(s)
- Tulio Guadalupe
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- International Max Planck Research School for Language Sciences, Nijmegen, The Netherlands
| | - Samuel R Mathias
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, 06519, USA
| | - Theo G M vanErp
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Christopher D Whelan
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
- Molecular and Cellular Therapeutics, The Royal College of Surgeons, Dublin 2, Ireland
| | - Marcel P Zwiers
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Yoshinari Abe
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Lucija Abramovic
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Ingrid Agartz
- NORMENT - KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Research and Development, Diakonhjemmet Hospital, Oslo, Norway
- Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institutet, Stockholm, Sweden
| | - Ole A Andreassen
- NORMENT - KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT - KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Alejandro Arias-Vásquez
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Benjamin S Aribisala
- Department of Computer Science, Lagos State University, Lagos, Nigeria
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
| | - Nicola J Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
- Mathematics and Statistics, Murdoch University, Murdoch, Australia
| | - Volker Arolt
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes -Sorbonne Paris Cité, Paris, France
| | - Rosa Ayesa-Arriola
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain
| | - Vatche G Baboyan
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
| | - Gareth Barker
- Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Mark E Bastin
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
| | - Bernhard T Baune
- Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA, 5005, Australia
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College Dublin, Dublin, Ireland
| | - Premika S W Boedhoe
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, VU/VUMC, Amsterdam, The Netherlands
| | - Anushree Bose
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Silvia Brem
- University Clinic for and Adolescent Psychiatry UCCAP, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Henry Brodaty
- Centre for Healthy Brain Ageing (CHeBA), & Dementia Collaborative Research Centre, School of Psychiatry, UNSW Medicine, University of New South Wales, Sydney, Australia
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Samantha Brooks
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Christian Büchel
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Raboud University, Nijmegen, The Netherlands
- Karakter Child and Adolescent Psychiatry, Radboud university medical center, Nijmegen, The Netherlands
| | - Vince D Calhoun
- Departments of Electrical and Computer Engineering,Neurosciences, Computer Science, and Psychiatry, The University of New Mexico, Albuquerque, NM, USA
- The Mind Research Network, Albuquerque, NM, USA
| | - Dara M Cannon
- Centre for Neuroimaging, Cognition & Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, H91 TK33, Ireland
| | - Anna Cattrell
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Yuqi Cheng
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Patricia J Conrod
- Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital, Montréal, Canada
- Department of Psychological Medicine and Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Annette Conzelmann
- Department of Psychology (Biological Psychology, Clinical Psychology, and Psychotherapy), University of Würzburg, Germany, Tübingen, Würzburg, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Aiden Corvin
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Benedicto Crespo-Facorro
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain
| | | | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, University of Marburg, Marburg, Germany
| | - Greig I de Zubicaray
- Faculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane City, Australia
| | - Sonja M C de Zwarte
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology, University of Edinburgh, Edinburgh, UK
| | - Sylvane Desrivières
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Nhat Trung Doan
- NORMENT - KG Jebsen Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT - KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Gary Donohoe
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition & Genomics Centre (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, SW4 794, Galway, Ireland
- Department of Psychiatry & trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Erlend S Dørum
- NORMENT - KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Stefan Ehrlich
- Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
- Department of Psychiatry, Massachusetts General Hospital, Boston, USA
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, USA
| | - Thomas Espeseth
- NORMENT - KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- NORMENT - KG Jebsen Centre, Department of Psychology, University of Oslo, Oslo, Norway
| | - Guillén Fernández
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Raboud University, Nijmegen, The Netherlands
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Jean-Paul Fouche
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Vincent Frouin
- Neurospin, Commissariat à l'Energie Atomique, CEA-Saclay Center, Paris, France
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Martinistrasse 52, 20246, Hamburg, Germany
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Michael Gill
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- Trinity College Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Andrea Gonzalez Suarez
- Service of Neurology, University Hospital Marqués de Valdecilla (IDIVAL), University of Cantabria (UC), Santander, Spain
- CIBERNED, Centro de Investigación Biomédica en red Enfermedades Neurodegenerativas, Madrid, Spain
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Hans J Grabe
- Department of Psychiatry, University Medicine Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, HELIOS Hospital Stralsund, Stralsund, Germany
| | | | - Oliver Gruber
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, D-37075, Göttingen, Germany
| | - Saskia Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ryota Hashimoto
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Tobias U Hauser
- University Clinic for Child and Adolescent Psychiatry (UCCAP), University of Zurich, Zurich, Switzerland
- Wellcome Trust Centre for Neuroimaging, University College London, London, UK
- UCL Max Planck Centre for Computational Psychiatry and Ageing, University College London, London, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Derrek P Hibar
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - Pieter J Hoekstra
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Martine Hoogman
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Fleur M Howells
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Hao Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 Wan Ping Nan Road, Shanghai, 200030, China
| | | | - Chaim Huyser
- De Bascule, Academic Center for Child and Adolescent Psychiatry, Amsterdam, The Netherlands
- AMC, department of child and adolescent psychiatry, Amsterdam, The Netherlands
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Neda Jahanshad
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Erik G Jönsson
- Department of Clinical Neuroscience, Psychiatry Section, Karolinska Institutet, Stockholm, Sweden
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine. Psychiatry section, University of Oslo, Oslo, Norway
| | - Sarah Jurk
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Rene S Kahn
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Sinead Kelly
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Los Angeles, 90292, USA
| | - Bernd Kraemer
- Center for Translational Research in Systems Neuroscience and Psychiatry, Department of Psychiatry and Psychotherapy, University Medical Center, D-37075, Göttingen, Germany
| | - Harald Kugel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Jun Soo Kwon
- Department of Psychiatry & Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, Republic of Korea
- Department of Brain & Cognitive Sciences, College of Natural Science, Seoul National University, Seoul, Republic of Korea
| | - Herve Lemaitre
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes -Sorbonne Paris Cité, Paris, France
| | - Klaus-Peter Lesch
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
- Department of Translational Neuroscience, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Christine Lochner
- Department of Psychiatry, University of Stellenbosch and MRC Unit on Anxiety & Stress Disorders, Tygerberg, Cape Town, South Africa
| | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, Psychology, University of Edinburgh, Edinburgh, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, London, UK
| | | | - Ignacio Martínez-Zalacaín
- Department of Psychiatry, Bellvitge University Hospital - Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes - Sorbonne Paris Cité, and Maison de Solenn, Paris, France
- Maison de Solenn, Paris, France
| | - David Mataix-Cols
- Department of Clinical Neuroscience,Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden
| | - Karen Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Colm McDonald
- Centre for Neuroimaging, Cognition & Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine, Nursing and Health Sciences, National University of Ireland Galway, Galway, H91 TK33, Ireland
| | - Katie L McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - José M Menchón
- Department of Psychiatry, Bellvitge University Hospital - Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain
- CIBER Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
- Department of Clinical Sciences, University of Barcelona, Barcelona, Spain
| | - Derek W Morris
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition & Genomics Centre (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, SW4 794, Galway, Ireland
| | - Omar Mothersill
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging, Cognition & Genomics Centre (NICOG), School of Psychology and Discipline of Biochemistry, National University of Ireland Galway, SW4 794, Galway, Ireland
| | - Susana Munoz Maniega
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Benson Mwangi
- UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, UT Houston Medical School, Houston, TX, USA
| | - Takashi Nakamae
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
- Department of Neural Computation for Decision-Making, ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Science, Kyushu University, Fukuoka, Japan
| | | | - Frauke Nees
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Jan E Nordvik
- Sunnaas Rehabilitation Hospital HT, Nesodden, Norway
| | - A Marten H Onnink
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Roel Ophoff
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
- Center for Neurobehavioral Genetics, University of California, Los Angeles, USA
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes -Sorbonne Paris Cité, Paris, France
- AP-HP, Department of Adolescent Psychopathology and Medicine, Maison de Solenn, Cochin Hospital, Paris, France
| | | | - Paul Pauli
- Department of Psychiatry and Psychotherapy, University of Würzburg, Würzburg, Germany
| | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, M6A 2E1, Toronto, ON, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany
- Department of Child and Adolescent Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Janardhan Yc Reddy
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | - Roberto Roiz-Santiáñez
- Department of Psychiatry, University Hospital Marqués de Valdecilla, School of Medicine, University of Cantabria-IDIVAL, Santander, Spain
- CIBERSAM, Centro Investigación Biomédica en Red Salud Mental, Santander, Spain
| | - Annerine Roos
- Department of Psychiatry, University of Stellenbosch and MRC Unit on Anxiety & Stress Disorders, Tygerberg, Cape Town, South Africa
| | - Natalie A Royle
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Perminder Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Pascual Sánchez-Juan
- Service of Neurology, University Hospital Marqués de Valdecilla (IDIVAL), University of Cantabria (UC), Santander, Spain
- CIBERNED, Centro de Investigación Biomédica en red Enfermedades Neurodegenerativas, Madrid, Spain
| | - Lianne Schmaal
- Department of Psychiatry, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Gunter Schumann
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Elena Shumskaya
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Jair C Soares
- Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX, 77054, USA
| | - Carles Soriano-Mas
- Department of Psychiatry, Bellvitge University Hospital - Institut d'Investigació Biomèdica de Bellvitge (IDIBELL), Barcelona, Spain
- CIBER Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Barcelona, Spain
- Department of Psychobiology and Methodology of Health Sciences, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Dan J Stein
- Department of Psychiatry, University of Cape Town and MRC Unit on Anxiety & Stress Disorders, Cape Town, South Africa
| | - Lachlan T Strike
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Roberto Toro
- Laboratory of Human Genetics and Cognitive Functions, Institut Pasteur, 75015, Paris, France
| | - Jessica A Turner
- The Mind Research Network, Albuquerque, NM, USA
- Department of Psychology, Georgia State University, Atlanta, GA, USA
- Department of Neuroscience, Georgia State University, Atlanta, GA, USA
| | | | - Anne Uhlmann
- Department of Psychiatry and Mental Health, University of Cape Town, Observatory, Cape Town, South Africa
| | - Maria Valdés Hernández
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Odile A van den Heuvel
- Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
- Neuroscience Campus Amsterdam, VU/VUMC, Amsterdam, The Netherlands
- Department of Psychiatry, VU University Medical Center, Amsterdam, The Netherlands
| | - Dennis van der Meer
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Neeltje E M van Haren
- Brain Centre Rudolf Magnus, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Nora C Vetter
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Daniella Vuletic
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - Susanne Walitza
- University Clinic for Child and Adolescent Psychiatry (UCCAP), University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Esther Walton
- Department of Child and Adolescent Psychiatry, Faculty of Medicine of the TU Dresden, Dresden, Germany
- Department of Psychology, Georgia State University, Atlanta, GA, USA
| | - Zhen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, No. 600 Wan Ping Nan Road, Shanghai, 200030, China
| | - Joanna Wardlaw
- Brain Research Imaging Centre, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Department of Neuroimaging Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales (UNSW), Sydney, Australia
| | - Lars T Westlye
- NORMENT - KG Jebsen Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Robert Whelan
- Department of Psychology, University College Dublin, Dublin, Ireland
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Site Rostock, Greifswald, Germany
| | - Thomas Wolfers
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Raboud University, Nijmegen, The Netherlands
| | - Margaret J Wright
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
- Queensland Brain Institute and Centre for Advanced Imaging, The University of Queensland, Brisbane, Australia
| | - Jian Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Xiufeng Xu
- Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Je-Yeon Yun
- Seoul National University Hospital, Seoul, Republic of Korea
| | - JingJing Zhao
- Cognitive Genetics and Therapy Group, School of Psychology & Discipline of Biochemistry, National University of Ireland Galway, Galway, SW4 794, Ireland
- School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Barbara Franke
- Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud university medical center, Nijmegen, The Netherlands
- Department of Psychiatry, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Paul M Thompson
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, Keck School of Medicine of the University of Southern California, Marina del Rey, CA, USA
| | - David C Glahn
- Department of Psychiatry, Yale University, New Haven, CT, 06511, USA
- Olin Neuropsychiatric Research Center, Hartford, CT, 06114, USA
| | - Bernard Mazoyer
- UMR5296 CNRS, CEA and University of Bordeaux, Bordeaux, France
| | - Simon E Fisher
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Raboud University, Nijmegen, The Netherlands
| | - Clyde Francks
- Language & Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Raboud University, Nijmegen, The Netherlands.
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Sterling N, Lewis M, Du G, Huang X. Structural Imaging and Parkinson's Disease: Moving Toward Quantitative Markers of Disease Progression. JOURNAL OF PARKINSON'S DISEASE 2016; 6:557-67. [PMID: 27258697 PMCID: PMC5008231 DOI: 10.3233/jpd-160824] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Accepted: 04/27/2016] [Indexed: 12/16/2022]
Abstract
Parkinson's disease (PD) is a progressive age-related neurodegenerative disorder. Although the pathological hallmark of PD is dopaminergic cell death in the substantia nigra pars compacta, widespread neurodegenerative changes occur throughout the brain as disease progresses. Postmortem studies, for example, have demonstrated the presence of Lewy pathology, apoptosis, and loss of neurotransmitters and interneurons in both cortical and subcortical regions of PD patients. Many in vivo structural imaging studies have attempted to gauge PD-related pathology, particularly in gray matter, with the hope of identifying an imaging biomarker. Reports of brain atrophy in PD, however, have been inconsistent, most likely due to differences in the studied populations (i.e. different disease stages and/or clinical subtypes), experimental designs (i.e. cross-sectional vs. longitudinal), and image analysis methodologies (i.e. automatic vs. manual segmentation). This review attempts to summarize the current state of gray matter structural imaging research in PD in relationship to disease progression, reconciling some of the differences in reported results, and to identify challenges and future avenues.
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Affiliation(s)
- N.W. Sterling
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - M.M. Lewis
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - G. Du
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
| | - X. Huang
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Radiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Neurosurgery, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
- Department of Kinesiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey, PA, USA
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Graham AM, Buss C, Rasmussen JM, Rudolph MD, Demeter DV, Gilmore JH, Styner M, Entringer S, Wadhwa PD, Fair DA. Implications of newborn amygdala connectivity for fear and cognitive development at 6-months-of-age. Dev Cogn Neurosci 2016; 18:12-25. [PMID: 26499255 PMCID: PMC4819011 DOI: 10.1016/j.dcn.2015.09.006] [Citation(s) in RCA: 95] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2015] [Revised: 09/16/2015] [Accepted: 09/21/2015] [Indexed: 01/06/2023] Open
Abstract
The first year of life is an important period for emergence of fear in humans. While animal models have revealed developmental changes in amygdala circuitry accompanying emerging fear, human neural systems involved in early fear development remain poorly understood. To increase understanding of the neural foundations of human fear, it is important to consider parallel cognitive development, which may modulate associations between typical development of early fear and subsequent risk for fear-related psychopathology. We, therefore, examined amygdala functional connectivity with rs-fcMRI in 48 neonates (M=3.65 weeks, SD=1.72), and measured fear and cognitive development at 6-months-of-age. Stronger, positive neonatal amygdala connectivity to several regions, including bilateral anterior insula and ventral striatum, was prospectively associated with higher fear at 6-months. Stronger amygdala connectivity to ventral anterior cingulate/anterior medial prefrontal cortex predicted a specific phenotype of higher fear combined with more advanced cognitive development. Overall, findings demonstrate unique profiles of neonatal amygdala functional connectivity related to emerging fear and cognitive development, which may have implications for normative and pathological fear in later years. Consideration of infant fear in the context of cognitive development will likely contribute to a more nuanced understanding of fear, its neural bases, and its implications for future mental health.
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Affiliation(s)
- Alice M Graham
- Department of Behavioral Neuroscience, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd., Portland, OR 97239, United States
| | - Claudia Buss
- Department of Medical Psychology, Charité University of Medicine Berlin, Luisenstrasse 57, 10117 Berlin, Germany; Development, Health and Disease Research Program, University of California, Irvine, 837 Health Sciences Drive, Irvine, CA 92697, United States.
| | - Jerod M Rasmussen
- Development, Health and Disease Research Program, University of California, Irvine, 837 Health Sciences Drive, Irvine, CA 92697, United States
| | - Marc D Rudolph
- Department of Behavioral Neuroscience, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd., Portland, OR 97239, United States
| | - Damion V Demeter
- Department of Behavioral Neuroscience, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd., Portland, OR 97239, United States
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina, 333 South Columbia Street, Chapel Hill, NC 27514, United States
| | - Martin Styner
- Department of Psychiatry, University of North Carolina, 333 South Columbia Street, Chapel Hill, NC 27514, United States
| | - Sonja Entringer
- Department of Medical Psychology, Charité University of Medicine Berlin, Luisenstrasse 57, 10117 Berlin, Germany; Development, Health and Disease Research Program, University of California, Irvine, 837 Health Sciences Drive, Irvine, CA 92697, United States
| | - Pathik D Wadhwa
- Development, Health and Disease Research Program, University of California, Irvine, 837 Health Sciences Drive, Irvine, CA 92697, United States
| | - Damien A Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd., Portland, OR 97239, United States; Department of Psychiatry, Oregon Health & Science University, Portland, OR, United States; Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, United States.
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Mak E, Su L, Williams GB, Watson R, Firbank M, Blamire A, O'Brien J. Differential Atrophy of Hippocampal Subfields: A Comparative Study of Dementia with Lewy Bodies and Alzheimer Disease. Am J Geriatr Psychiatry 2016; 24:136-43. [PMID: 26324541 DOI: 10.1016/j.jagp.2015.06.006] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Revised: 06/16/2015] [Accepted: 06/18/2015] [Indexed: 11/16/2022]
Abstract
OBJECTIVES Dementia with Lewy bodies (DLB) is characterized by relative preservation of the medial temporal lobe compared with Alzheimer disease (AD). The differential involvement of the hippocampal subfields in both diseases has not been clearly established, however. We aim to investigate hippocampal subfield differences in vivo in a clinical cohort of DLB and AD subjects. METHODS 104 participants (35 DLBs, 36 ADs, and 35 healthy comparison [HC] subjects) underwent clinical assessment and 3T T1-weighted imaging. A Bayesian model implemented in Freesurfer was used to automatically segment the hippocampus and its subfields. We also examined associations between hippocampal subfields and tests of memory function. RESULTS Both the AD and DLB groups demonstrated significant atrophy of the total hippocampus relative to HC but the DLB group was characterized by preservation of the cornu ammonis 1 (CA1), fimbria, and fissure. In contrast, all the hippocampal subfields except the fissure were significantly atrophied in AD compared with both DLB and HC groups. Among DLB subjects, CA1 was correlated with the Recent Memory score of the CAMCOG and Delayed Recall subscores of the HVLT. CONCLUSIONS DLB is characterized by milder hippocampal atrophy that was accompanied by preservation of the CA1. The CA1 was also associated with memory function in DLB. Our findings highlight the promising role of hippocampal subfield volumetry, particularly that of the CA1, as a biomarker for the distinction between AD and DLB.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke University of Cambridge, UK
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke University of Cambridge, UK
| | - Guy B Williams
- Wolfson Brain Imaging Centre, University of Cambridge, UK
| | - Rosie Watson
- Department of Aged Care, The Royal Melbourne Hospital, Melbourne, Australia; Institute of Neuroscience, Newcastle University, Newcastle, UK; The Florey Institute of Neuroscience and the Department of Medicine, The University of Melbourne, Parkville, Australia
| | - Michael Firbank
- Institute of Neuroscience, Newcastle University, Newcastle, UK
| | - Andrew Blamire
- Institute of Cellular Medicine and Newcastle Magnetic Resonance Centre, Newcastle, UK
| | - John O'Brien
- Department of Psychiatry, School of Clinical Medicine, Addenbrooke University of Cambridge, UK.
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Ramirez-Carmona R, Garcia-Lazaro HG, Dominguez-Corrales B, Aguilar-Castañeda E, Roldan-Valadez E. Main effects and interactions of cerebral hemispheres, gender, and age in the calculation of volumes and asymmetries of selected structures of episodic memory. FUNCTIONAL NEUROLOGY 2016; 31:257-264. [PMID: 28072386 PMCID: PMC5231888 DOI: 10.11138/fneur/2016.31.4.257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The aim of this study was to clarify the influence of anatomical (cerebral hemisphere) and demographic (age and gender) variables on the gray matter (GM) volumes and volumetric asymmetry indices (VAIs) of selected structures involved in episodic memory. A cross-sectional study was performed in 47 healthy volunteers. Neuropsychological evaluation revealed similar IQs across the sample. Using SPM-based software, brain segmentation, labeling and volume measurements of the hippocampus, amygdala, middle temporal gyrus and parahippocampal gyrus were performed in each cerebral hemisphere. A two-way between-groups multivariate analysis of covariance (MANCOVA) was applied to GM volumes and VAIs. The main effects of gender and cerebral hemisphere on GM volumes were significant (p < .001), while there was no significant interaction effect between gender and cerebral hemisphere. VAI measurements showed a nonsignificant effect of gender, but a significant influence of age (p = .015). The linear model of interactions and main effects explained 33% of the variance influencing the GM volume quantification. While cerebral hemisphere and gender were found to affect the volumes of brain structures involved in episodic memory, the calculation of VAIs was affected only by age. A comprehensive understanding of the main effects and interaction effects of cerebral hemisphere, gender and age on the volumes and asymmetries of structures related to episodic memory might help neurologists, psychiatrists, geriatricians and other neuroscientists in the study of degenerative brain diseases.
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Affiliation(s)
| | | | - Brenda Dominguez-Corrales
- Magnetic Resonance Unit, Medica Sur Clinic & Foundation, Mexico City, Mexico
- Division of Medicine and Health Sciences, University of Sonora, Hermosillo City, Mexico
| | - Erika Aguilar-Castañeda
- Magnetic Resonance Unit, Medica Sur Clinic & Foundation, Mexico City, Mexico
- Neuropsychology Department, National Institute of Neurology and Neurosurgery, Mexico City, Mexico
| | - Ernesto Roldan-Valadez
- Direccion de Investigacion, Hospital General de Mexico “Dr. Eduardo Liceaga”, Mexico City, Mexico
- Universidad Panamericana, Campus Mexico, Escuela de Medicina, Mexico City, Mexico
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Longitudinal analysis of the developing rhesus monkey brain using magnetic resonance imaging: birth to adulthood. Brain Struct Funct 2015; 221:2847-71. [PMID: 26159774 PMCID: PMC4884209 DOI: 10.1007/s00429-015-1076-x] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Accepted: 06/17/2015] [Indexed: 01/21/2023]
Abstract
We have longitudinally assessed normative brain growth patterns in naturalistically reared Macaca mulatta monkeys. Postnatal to early adulthood brain development in two cohorts of rhesus monkeys was analyzed using magnetic resonance imaging. Cohort A consisted of 24 rhesus monkeys (12 male, 12 female) and cohort B of 21 monkeys (11 male, 10 female). All subjects were scanned at 1, 4, 8, 13, 26, 39, and 52 weeks; cohort A had additional scans at 156 weeks (3 years) and 260 weeks (5 years). Age-specific segmentation templates were developed for automated volumetric analyses of the T1-weighted magnetic resonance imaging scans. Trajectories of total brain size as well as cerebral and subcortical subdivisions were evaluated over this period. Total brain volume was about 64 % of adult estimates in the 1-week-old monkey. Brain volume of the male subjects was always, on average, larger than the female subjects. While brain volume generally increased between any two imaging time points, there was a transient plateau of brain growth between 26 and 39 weeks in both cohorts of monkeys. The trajectory of enlargement differed across cortical regions with the occipital cortex demonstrating the most idiosyncratic pattern of maturation and the frontal and temporal lobes showing the greatest and most protracted growth. A variety of allometric measurements were also acquired and body weight gain was most closely associated with the rate of brain growth. These findings provide a valuable baseline for the effects of fetal and early postnatal manipulations on the pattern of abnormal brain growth related to neurodevelopmental disorders.
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MRI characterization of temporal lobe epilepsy using rapidly measurable spatial indices with hemisphere asymmetries and gender features. Neuroradiology 2015; 57:873-86. [PMID: 26032924 DOI: 10.1007/s00234-015-1540-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Accepted: 05/04/2015] [Indexed: 10/23/2022]
Abstract
INTRODUCTION The paucity of morphometric markers for hemispheric asymmetries and gender variations in hippocampi and amygdalae in temporal lobe epilepsy (TLE) calls for better characterization of TLE by finding more useful prognostic MRI parameter(s). METHODS T1-weighted MRI (3 T) morphometry using multiple parameters of hippocampus-parahippocampus (angular and linear measures, volumetry) and amygdalae (volumetry) including their hemispheric asymmetry indices (AI) were evaluated in both genders. The cutoff values of parameters were statistically estimated from measurements of healthy subjects to characterize TLE (57 patients, 55% male) alterations. RESULTS TLE had differential categories with hippocampal atrophy, parahippocampal angle (PHA) acuteness, and several other parametric changes. Bilateral TLE categories were much more prevalent compared to unilateral TLE categories. Female patients were considerably more disposed to bilateral TLE categories than male patients. Male patients displayed diverse categories of unilateral abnormalities. Few patients (both genders) had combined bilateral appearances of hippocampal atrophy, amygdala atrophy, PHA acuteness, and increase in hippocampal angle (HA) where medial distance ratio (MDR) varied among genders. TLE had gender-specific and hemispheric dominant alterations in AI of parameters. Maximum magnitude of parametric changes in TLE includes (a) AI increase in HA of both genders, (b) HA increase (bilateral) in female patients, and (c) increase in ratio of amygdale/hippocampal volume (unilateral, right hemispheric), and AI decrease in MDR, in male patients. CONCLUSION Multiparametric MRI studies of hippocampus and amygdalae, including their hemispheric asymmetry, underscore better characterization of TLE. Rapidly measurable single-slice parameters (HA, PHA, MDR) can readily delineate TLE in a time-constrained clinical setting, which contrasts with customary three-dimensional hippocampal volumetry that requires many slice computation.
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Kang X, Herron TJ, Ettlinger M, Woods DL. Hemispheric asymmetries in cortical and subcortical anatomy. Laterality 2015; 20:658-84. [PMID: 25894493 DOI: 10.1080/1357650x.2015.1032975] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Previous research studies have reported many hemispherical asymmetries in cortical and subcortical anatomy, but only a subset of findings is consistent across studies. Here, we used improved Freesurfer-based automated methods to analyse the properties of the cortex and seven subcortical structures in 138 young adult subjects. Male and female subjects showed similar hemispheric asymmetries in gyral and sulcal structures, with many areas associated with language processing enlarged in the left hemisphere (LH) and a number of areas associated with visuospatial processing enlarged in the right hemisphere (RH). In addition, we found greater (non-directional) cortical asymmetries in subjects with larger brains. Asymmetries in subcortical structures included larger LH volumes of thalamus, putamen and globus pallidus and larger RH volumes of the cerebellum and the amygdala. We also found significant correlations between the subcortical structural volumes, particularly of the thalamus and cerebellum, with cortical area. These results help to resolve some of the inconsistencies in previous studies of hemispheric asymmetries in brain anatomy.
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Affiliation(s)
- Xiaojian Kang
- a Human Cognitive Neurophysiology Lab , VA Research Service 151, VA-NCHCS , Martinez , CA , USA
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Cherel M, Budin F, Prastawa M, Gerig G, Lee K, Buss C, Lyall A, Consing KZ, Styner M. Automatic Tissue Segmentation of Neonate Brain MR Images with Subject-specific Atlases. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2015; 9413. [PMID: 26089584 DOI: 10.1117/12.2082209] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Automatic tissue segmentation of the neonate brain using Magnetic Resonance Images (MRI) is extremely important to study brain development and perform early diagnostics but is challenging due to high variability and inhomogeneity in contrast throughout the image due to incomplete myelination of the white matter tracts. For these reasons, current methods often totally fail or give unsatisfying results. Furthermore, most of the subcortical midbrain structures are misclassified due to a lack of contrast in these regions. We have developed a novel method that creates a probabilistic subject-specific atlas based on a population atlas currently containing a number of manually segmented cases. The generated subject-specific atlas is sharp and adapted to the subject that is being processed. We then segment brain tissue classes using the newly created atlas with a single-atlas expectation maximization based method. Our proposed method leads to a much lower failure rate in our experiments. The overall segmentation results are considerably improved when compared to using a non-subject-specific, population average atlas. Additionally, we have incorporated diffusion information obtained from Diffusion Tensor Images (DTI) to improve the detection of white matter that is not visible at this early age in structural MRI (sMRI) due to a lack of myelination. Although this necessitates the acquisition of an additional sequence, the diffusion information improves the white matter segmentation throughout the brain, especially for the mid-brain structures such as the corpus callosum and the internal capsule.
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Affiliation(s)
- Marie Cherel
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Francois Budin
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Guido Gerig
- School of Computing, University of Utah, Salt Lake City, UT 84112 USA ; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112 USA
| | - Kevin Lee
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Claudia Buss
- Charité University Medicine Berlin, 10117 Berlin, Germany ; Development, Health and Disease Research Program, University of California, Irvine, CA 92697, USA
| | - Amanda Lyall
- Psychiatry Neuroimaging Laboratory, Harvard, Boston, MA 02215 USA
| | | | - Martin Styner
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC 27599, USA ; Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599 USA
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Teng E, Chow N, Hwang KS, Thompson PM, Gylys KH, Cole GM, Jack CR, Shaw LM, Trojanowski JQ, Soares HD, Weiner MW, Apostolova LG. Low plasma ApoE levels are associated with smaller hippocampal size in the Alzheimer's disease neuroimaging initiative cohort. Dement Geriatr Cogn Disord 2014; 39:154-66. [PMID: 25547651 PMCID: PMC4323932 DOI: 10.1159/000368982] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/10/2014] [Indexed: 12/22/2022] Open
Abstract
Apolipoprotein E (APOE) genotype is the strongest known genetic risk factor for sporadic Alzheimer's disease (AD), but the utility of plasma ApoE levels for assessing the severity of underlying neurodegenerative changes remains uncertain. Here, we examined cross-sectional associations between plasma ApoE levels and volumetric magnetic resonance imaging indices of the hippocampus from 541 participants [57 with normal cognition (NC), 375 with mild cognitive impairment (MCI), and 109 with mild AD] who were enrolled in the Alzheimer's Disease Neuroimaging Initiative. Across the NC and MCI groups, lower plasma ApoE levels were significantly correlated with smaller hippocampal size, as measured by either hippocampal volume or hippocampal radial distance. These associations were driven primarily by findings from carriers of an APOE ε4 allele and are consistent with prior reports that lower plasma ApoE levels correlate with greater global cortical Pittsburgh Compound B retention. In this high-risk group, plasma ApoE levels may represent a peripheral marker of underlying AD neuropathology in nondemented elderly individuals.
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Affiliation(s)
- Edmond Teng
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Nicole Chow
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Kristy S. Hwang
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Paul M. Thompson
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine, UCLA, CA, USA
| | | | - Gregory M. Cole
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Veterans Affairs Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Clifford R. Jack
- Department of Diagnostic Radiology, Mayo Clinic, Rochester, MN, USA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | | | - Michael W. Weiner
- Departments of Medicine, Radiology, and Psychiatry, UCSF, San Francisco, CA, USA
- Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Liana G. Apostolova
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Imaging Genetics Center, Laboratory of Neuro Imaging, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
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Maruszak A, Thuret S. Why looking at the whole hippocampus is not enough-a critical role for anteroposterior axis, subfield and activation analyses to enhance predictive value of hippocampal changes for Alzheimer's disease diagnosis. Front Cell Neurosci 2014; 8:95. [PMID: 24744700 PMCID: PMC3978283 DOI: 10.3389/fncel.2014.00095] [Citation(s) in RCA: 106] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2013] [Accepted: 03/13/2014] [Indexed: 01/06/2023] Open
Abstract
The hippocampus is one of the earliest affected brain regions in Alzheimer's disease (AD) and its dysfunction is believed to underlie the core feature of the disease-memory impairment. Given that hippocampal volume is one of the best AD biomarkers, our review focuses on distinct subfields within the hippocampus, pinpointing regions that might enhance the predictive value of current diagnostic methods. Our review presents how changes in hippocampal volume, shape, symmetry and activation are reflected by cognitive impairment and how they are linked with neurogenesis alterations. Moreover, we revisit the functional differentiation along the anteroposterior longitudinal axis of the hippocampus and discuss its relevance for AD diagnosis. Finally, we indicate that apart from hippocampal subfield volumetry, the characteristic pattern of hippocampal hyperactivation associated with seizures and neurogenesis changes is another promising candidate for an early AD biomarker that could become also a target for early interventions.
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Affiliation(s)
- Aleksandra Maruszak
- Centre for the Cellular Basis of Behaviour, Department of Neuroscience, Institute of Psychiatry, King’s College LondonLondon, UK
| | - Sandrine Thuret
- Centre for the Cellular Basis of Behaviour, Department of Neuroscience, Institute of Psychiatry, King’s College LondonLondon, UK
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31
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Hunsaker MR, Amaral DG. A semi-automated pipeline for the segmentation of rhesus macaque hippocampus: validation across a wide age range. PLoS One 2014; 9:e89456. [PMID: 24586791 PMCID: PMC3933562 DOI: 10.1371/journal.pone.0089456] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Accepted: 01/20/2014] [Indexed: 11/18/2022] Open
Abstract
This report outlines a neuroimaging pipeline that allows a robust, high-throughput, semi-automated, template-based protocol for segmenting the hippocampus in rhesus macaque (Macaca mulatta) monkeys ranging from 1 week to 260 weeks of age. The semiautomated component of this approach minimizes user effort while concurrently maximizing the benefit of human expertise by requiring as few as 10 landmarks to be placed on images of each hippocampus to guide registration. Any systematic errors in the normalization process are corrected using a machine-learning algorithm that has been trained by comparing manual and automated segmentations to identify systematic errors. These methods result in high spatial overlap and reliability when compared with the results of manual tracing protocols. They also dramatically reduce the time to acquire data, an important consideration in large-scale neuroradiological studies involving hundreds of MRI scans. Importantly, other than the initial generation of the unbiased template, this approach requires only modest neuroanatomical training. It has been validated for high-throughput studies of rhesus macaque hippocampal anatomy across a broad age range.
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Affiliation(s)
- Michael R. Hunsaker
- Department of Psychiatry and Behavioral Sciences, University of California, Davis Medical Center, Davis, California, United States of America
- UC Davis MIND Institute; University of California, Davis Medical Center, Davis, California, United States of America
- * E-mail:
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, University of California, Davis Medical Center, Davis, California, United States of America
- UC Davis MIND Institute; University of California, Davis Medical Center, Davis, California, United States of America
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Wenger E, Mårtensson J, Noack H, Bodammer NC, Kühn S, Schaefer S, Heinze HJ, Düzel E, Bäckman L, Lindenberger U, Lövdén M. Comparing manual and automatic segmentation of hippocampal volumes: reliability and validity issues in younger and older brains. Hum Brain Mapp 2014; 35:4236-48. [PMID: 24532539 DOI: 10.1002/hbm.22473] [Citation(s) in RCA: 125] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Accepted: 01/14/2014] [Indexed: 11/08/2022] Open
Abstract
We compared hippocampal volume measures obtained by manual tracing to automatic segmentation with FreeSurfer in 44 younger (20-30 years) and 47 older (60-70 years) adults, each measured with magnetic resonance imaging (MRI) over three successive time points, separated by four months. Retest correlations over time were very high for both manual and FreeSurfer segmentations. With FreeSurfer, correlations over time were significantly lower in the older than in the younger age group, which was not the case with manual segmentation. Pearson correlations between manual and FreeSurfer estimates were sufficiently high, numerically even higher in the younger group, whereas intra-class correlation coefficient (ICC) estimates were lower in the younger than in the older group. FreeSurfer yielded higher volume estimates than manual segmentation, particularly in the younger age group. Importantly, FreeSurfer consistently overestimated hippocampal volumes independently of manually assessed volume in the younger age group, but overestimated larger volumes in the older age group to a less extent, introducing a systematic age bias in the data. Age differences in hippocampal volumes were significant with FreeSurfer, but not with manual tracing. Manual tracing resulted in a significant difference between left and right hippocampus (right > left), whereas this asymmetry effect was considerably smaller with FreeSurfer estimates. We conclude that FreeSurfer constitutes a feasible method to assess differences in hippocampal volume in young adults. FreeSurfer estimates in older age groups should, however, be interpreted with care until the automatic segmentation pipeline has been further optimized to increase validity and reliability in this age group.
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Affiliation(s)
- Elisabeth Wenger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Germany
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Mulder ER, de Jong RA, Knol DL, van Schijndel RA, Cover KS, Visser PJ, Barkhof F, Vrenken H. Hippocampal volume change measurement: quantitative assessment of the reproducibility of expert manual outlining and the automated methods FreeSurfer and FIRST. Neuroimage 2014; 92:169-81. [PMID: 24521851 DOI: 10.1016/j.neuroimage.2014.01.058] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2013] [Revised: 01/23/2014] [Accepted: 01/31/2014] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND To measure hippocampal volume change in Alzheimer's disease (AD) or mild cognitive impairment (MCI), expert manual delineation is often used because of its supposed accuracy. It has been suggested that expert outlining yields poorer reproducibility as compared to automated methods, but this has not been investigated. AIM To determine the reproducibilities of expert manual outlining and two common automated methods for measuring hippocampal atrophy rates in healthy aging, MCI and AD. METHODS From the Alzheimer's Disease Neuroimaging Initiative (ADNI), 80 subjects were selected: 20 patients with AD, 40 patients with mild cognitive impairment (MCI) and 20 healthy controls (HCs). Left and right hippocampal volume change between baseline and month-12 visit was assessed by using expert manual delineation, and by the automated software packages FreeSurfer (longitudinal processing stream) and FIRST. To assess reproducibility of the measured hippocampal volume change, both back-to-back (BTB) MPRAGE scans available for each visit were analyzed. Hippocampal volume change was expressed in μL, and as a percentage of baseline volume. Reproducibility of the 1-year hippocampal volume change was estimated from the BTB measurements by using linear mixed model to calculate the limits of agreement (LoA) of each method, reflecting its measurement uncertainty. Using the delta method, approximate p-values were calculated for the pairwise comparisons between methods. Statistical analyses were performed both with inclusion and exclusion of visibly incorrect segmentations. RESULTS Visibly incorrect automated segmentation in either one or both scans of a longitudinal scan pair occurred in 7.5% of the hippocampi for FreeSurfer and in 6.9% of the hippocampi for FIRST. After excluding these failed cases, reproducibility analysis for 1-year percentage volume change yielded LoA of ±7.2% for FreeSurfer, ±9.7% for expert manual delineation, and ±10.0% for FIRST. Methods ranked the same for reproducibility of 1-year μL volume change, with LoA of ±218 μL for FreeSurfer, ±319 μL for expert manual delineation, and ±333 μL for FIRST. Approximate p-values indicated that reproducibility was better for FreeSurfer than for manual or FIRST, and that manual and FIRST did not differ. Inclusion of failed automated segmentations led to worsening of reproducibility of both automated methods for 1-year raw and percentage volume change. CONCLUSION Quantitative reproducibility values of 1-year microliter and percentage hippocampal volume change were roughly similar between expert manual outlining, FIRST and FreeSurfer, but FreeSurfer reproducibility was statistically significantly superior to both manual outlining and FIRST after exclusion of failed segmentations.
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Affiliation(s)
- Emma R Mulder
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Remko A de Jong
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Dirk L Knol
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | - Ronald A van Schijndel
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Information and Communication Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Keith S Cover
- Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Pieter J Visser
- Department of Neurology, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands; Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo Vrenken
- Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands; Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands.
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34
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Brown ES, Hughes CW, McColl R, Peshock R, King KS, Rush AJ. Association of depressive symptoms with hippocampal volume in 1936 adults. Neuropsychopharmacology 2014; 39:770-9. [PMID: 24220026 PMCID: PMC3895255 DOI: 10.1038/npp.2013.271] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 09/04/2013] [Accepted: 09/14/2013] [Indexed: 12/28/2022]
Abstract
Hippocampal atrophy is reported in major depressive disorder (MDD). However, sample sizes were generally modest, and participant characteristics, including age, differed between studies. This study used a community sample to examine relationships between current depressive symptom severity and hippocampal volume across the adult lifespan. A total of 1936 adults with magnetic resonance images of the brain and Quick Inventory of Depressive Symptomatology Self-Report (QIDS-SR) scores were included. Brain volumes were quantified using the FSL program. Multiple linear regressions were performed using left, right, and total hippocampal volume as criterion variables, and predictor variables of QIDS-SR total, total brain volume, age, gender, education, psychotropic medications, alcohol use, and race/ethnicity. Post hoc analyses were conducted in participants with QIDS-SR scores 11 (moderate or greater depressive symptom severity) and <11, and older and younger adults. In the primary analysis (sample as a whole) QIDS-SR was inversely associated with total hippocampal volume (b=-0.044, p=0.032, (CI-0.019 to -0.001)) but not with left or right hippocampal volume evaluated individually. In participants with QIDS-SR scores of <11, hippocampal volumes were not associated with QIDS-SR scores. In those with QIDS-SR scores 11 total, right, and left hippocampal volumes were modestly, but significantly, associated with QIDS-SR scores. The association between QIDS-SR scores and the hippocampal volume was much stronger in older persons. Findings suggest smaller hippocampal volumes among those with greater reported depressive symptom severity-an association that is strongest in people with at least moderate depressive symptom levels.
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Affiliation(s)
- E Sherwood Brown
- Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, TX, USA,Department of Psychiatry, The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd. MC 8849, Dallas, TX 75390-8849, USA, Tel: +1 214 645 6950, Fax: +1 214 645 6951, E-mail:
| | - Carroll W Hughes
- Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Roderick McColl
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ronald Peshock
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Kevin S King
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, TX, USA
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35
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Donix M, Burggren AC, Scharf M, Marschner K, Suthana NA, Siddarth P, Krupa AK, Jones M, Martin-Harris L, Ercoli LM, Miller KJ, Werner A, von Kummer R, Sauer C, Small GW, Holthoff VA, Bookheimer SY. APOE associated hemispheric asymmetry of entorhinal cortical thickness in aging and Alzheimer's disease. Psychiatry Res 2013; 214:212-20. [PMID: 24080518 PMCID: PMC3851589 DOI: 10.1016/j.pscychresns.2013.09.006] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Revised: 09/07/2013] [Accepted: 09/09/2013] [Indexed: 11/26/2022]
Abstract
Across species structural and functional hemispheric asymmetry is a fundamental feature of the brain. Environmental and genetic factors determine this asymmetry during brain development and modulate its interaction with brain disorders. The e4 allele of the apolipoprotein E gene (APOE-4) is a risk factor for Alzheimer's disease, associated with regionally specific effects on brain morphology and function during the life span. Furthermore, entorhinal and hippocampal hemispheric asymmetry could be modified by pathology during Alzheimer's disease development. Using high-resolution magnetic resonance imaging and a cortical unfolding technique we investigated whether carrying the APOE-4 allele influences hemispheric asymmetry in the entorhinal cortex and the hippocampus among patients with Alzheimer's disease as well as in middle-aged and older cognitively healthy individuals. APOE-4 carriers showed a thinner entorhinal cortex in the left hemisphere when compared with the right hemisphere across all participants. Non-carriers of the allele showed this asymmetry only in the patient group. Cortical thickness in the hippocampus did not vary between hemispheres among APOE-4 allele carriers and non-carriers. The APOE-4 allele modulates hemispheric asymmetry in entorhinal cortical thickness. Among Alzheimer's disease patients, this asymmetry might be less dependent on the APOE genotype and a more general marker of incipient disease pathology.
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Affiliation(s)
- Markus Donix
- Department of Psychiatry and Psychotherapy, Division of Old Age Psychiatry and Cognitive Neuropsychiatry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany; DZNE, German Center for Neurodegenerative Diseases, Dresden, Germany.
| | - Alison C. Burggren
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Maria Scharf
- Department of Psychiatry and Psychotherapy, Division of Old Age Psychiatry and Cognitive Neuropsychiatry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany,DZNE, German Center for Neurodegenerative Diseases, Dresden, Germany
| | - Kira Marschner
- Department of Psychiatry and Psychotherapy, Division of Old Age Psychiatry and Cognitive Neuropsychiatry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany,DZNE, German Center for Neurodegenerative Diseases, Dresden, Germany
| | - Nanthia A. Suthana
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Neurosurgery, Los Angeles CA 90095, USA
| | - Prabha Siddarth
- David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Allison K. Krupa
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Michael Jones
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Laurel Martin-Harris
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Linda M. Ercoli
- David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Karen J. Miller
- David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA
| | - Annett Werner
- Department of Neuroradiology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany
| | - Rüdiger von Kummer
- Department of Neuroradiology, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany
| | - Cathrin Sauer
- Department of Psychiatry and Psychotherapy, Division of Old Age Psychiatry and Cognitive Neuropsychiatry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany
| | - Gary W. Small
- David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA,UCLA Longevity Center, CA 90095, USA
| | - Vjera A. Holthoff
- Department of Psychiatry and Psychotherapy, Division of Old Age Psychiatry and Cognitive Neuropsychiatry, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany,DZNE, German Center for Neurodegenerative Diseases, Dresden, Germany
| | - Susan Y. Bookheimer
- David Geffen School of Medicine at UCLA, Center for Cognitive Neurosciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychiatry and Biobehavioral Sciences, Semel Institute, Los Angeles, CA 90095, USA,David Geffen School of Medicine at UCLA, Department of Psychology, Los Angeles, CA 90095, USA
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Guadalupe T, Zwiers MP, Teumer A, Wittfeld K, Vasquez AA, Hoogman M, Hagoort P, Fernandez G, Buitelaar J, Hegenscheid K, Völzke H, Franke B, Fisher SE, Grabe HJ, Francks C. Measurement and genetics of human subcortical and hippocampal asymmetries in large datasets. Hum Brain Mapp 2013; 35:3277-89. [PMID: 24827550 DOI: 10.1002/hbm.22401] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2013] [Revised: 07/29/2013] [Accepted: 08/26/2013] [Indexed: 11/06/2022] Open
Abstract
Functional and anatomical asymmetries are prevalent features of the human brain, linked to gender, handedness, and cognition. However, little is known about the neurodevelopmental processes involved. In zebrafish, asymmetries arise in the diencephalon before extending within the central nervous system. We aimed to identify genes involved in the development of subtle, left-right volumetric asymmetries of human subcortical structures using large datasets. We first tested the feasibility of measuring left-right volume differences in such large-scale samples, as assessed by two automated methods of subcortical segmentation (FSL|FIRST and FreeSurfer), using data from 235 subjects who had undergone MRI twice. We tested the agreement between the first and second scan, and the agreement between the segmentation methods, for measures of bilateral volumes of six subcortical structures and the hippocampus, and their volumetric asymmetries. We also tested whether there were biases introduced by left-right differences in the regional atlases used by the methods, by analyzing left-right flipped images. While many bilateral volumes were measured well (scan-rescan r = 0.6-0.8), most asymmetries, with the exception of the caudate nucleus, showed lower repeatabilites. We meta-analyzed genome-wide association scan results for caudate nucleus asymmetry in a combined sample of 3,028 adult subjects but did not detect associations at genome-wide significance (P < 5 × 10(-8) ). There was no enrichment of genetic association in genes involved in left-right patterning of the viscera. Our results provide important information for researchers who are currently aiming to carry out large-scale genome-wide studies of subcortical and hippocampal volumes, and their asymmetries.
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Affiliation(s)
- Tulio Guadalupe
- Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands; International Max Planck Research School for Language Sciences, Max Planck Insitute for Psycholinguistics, Nijmegen, The Netherlands
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Sterling NW, Du G, Lewis MM, Dimaio C, Kong L, Eslinger PJ, Styner M, Huang X. Striatal shape in Parkinson's disease. Neurobiol Aging 2013; 34:2510-6. [PMID: 23820588 PMCID: PMC3742686 DOI: 10.1016/j.neurobiolaging.2013.05.017] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2013] [Revised: 05/04/2013] [Accepted: 05/23/2013] [Indexed: 12/16/2022]
Abstract
Parkinson's disease (PD) is marked pathologically by nigrostriatal dopaminergic terminal loss. Histopathological and in vivo labeling studies demonstrate that this loss occurs most extensively in the caudal putamen and caudate head. Previous structural studies have suggested reduced striatal volume and atrophy of the caudate head in PD subjects. The spatial distribution of atrophy in the putamen, however, has not been characterized. We aimed to delineate the specific locations of atrophy in both of these striatal structures. T1- and T2-weighted brain MR (3T) images were obtained from 40 PD and 40 control subjects having no dementia and similar age and gender distributions. Shape analysis was performed using doubly segmented regions of interest. Compared to controls, PD subjects had lower putamen (p = 0.0003) and caudate (p = 0.0003) volumes. Surface contraction magnitudes were greatest on the caudal putamen (p ≤ 0.005) and head and dorsal body of the caudate (p ≤ 0.005). This spatial distribution of striatal atrophy is consistent with the known pattern of dopamine depletion in PD and may reflect global consequences of known cellular remodeling phenomena.
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Affiliation(s)
- Nicholas W. Sterling
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Public Health Sciences, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Guangwei Du
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Mechelle M. Lewis
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Christopher Dimaio
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Lan Kong
- Department of Public Health Sciences, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Paul J. Eslinger
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Public Health Sciences, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Radiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
| | - Martin Styner
- Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Xuemei Huang
- Department of Neurology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Pharmacology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Radiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Neurosurgery, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
- Department of Kinesiology, Pennsylvania State University-Milton S. Hershey Medical Center, Hershey PA 17033, USA
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38
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Lucarelli RT, Peshock RM, McColl R, Hulsey K, Ayers C, Whittemore AR, King KS. MR imaging of hippocampal asymmetry at 3T in a multiethnic, population-based sample: results from the Dallas Heart Study. AJNR Am J Neuroradiol 2013; 34:752-7. [PMID: 23139080 DOI: 10.3174/ajnr.a3308] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Asymmetry of the hippocampus is regarded as an important clinical finding, but limited data on hippocampal asymmetry are available for the general population. Here we present hippocampal asymmetry data from the Dallas Heart Study determined by automated methods and its relationship to age, sex, and ethnicity. MATERIALS AND METHODS 3D magnetization-prepared rapid acquisition of gradient echo MR imaging was performed in 2082 DHS-2 participants. The MR images were analyzed by using 2 standard automated brain-segmentation programs, FSL-FIRST and FreeSurfer. Individuals with imaging errors, self-reported stroke, or major structural abnormalities were excluded. Statistical analyses were performed to determine the significance of the findings across age, sex, and ethnicity. RESULTS At the 90th percentile, FSL-FIRST demonstrated hippocampal asymmetry of 9.8% (95% CI, 9.3%-10.5%). The 90th percentile of hippocampal asymmetry, measured by the difference in right and left hippocampi volume and the larger hippocampus, was 17.9% (95% CI, 17.0%-19.1%). Hippocampal asymmetry increases with age (P=.0216), men have greater asymmetry than women as shown by FSL-FIRST (P=.0036), but ethnicity is not significantly correlated with asymmetry. To confirm these findings, we used FreeSurfer. FreeSurfer showed asymmetry of 4.4% (95% CI, 4.3%-4.7%) normalized to total volume and 8.5% (95% CI, 8.3%-9.0%) normalized by difference/larger hippocampus. FreeSurfer also showed that hippocampal asymmetry increases with age (P=.0024) and that men had greater asymmetry than women (P=.03). CONCLUSIONS There is a significant degree of hippocampal asymmetry in the population. The data provided will aid in the research, diagnosis, and treatment of temporal lobe epilepsy and other neurologic disease.
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Affiliation(s)
- R T Lucarelli
- Department of Radiology, Donald W. Reynolds Cardiovascular Clinical Research Center, University of Texas Southwestern Medical Center, Dallas, Texas 75390-8896, USA
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Dickstein DP, Pescosolido MF, Reidy BL, Galvan T, Kim KL, Seymour KE, Laird AR, Di Martino A, Barrett RP. Developmental meta-analysis of the functional neural correlates of autism spectrum disorders. J Am Acad Child Adolesc Psychiatry 2013; 52:279-289.e16. [PMID: 23452684 PMCID: PMC5441228 DOI: 10.1016/j.jaac.2012.12.012] [Citation(s) in RCA: 64] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2012] [Revised: 11/26/2012] [Accepted: 12/18/2012] [Indexed: 10/27/2022]
Abstract
OBJECTIVE There is a pressing need to elucidate the brain-behavior interactions underlying autism spectrum disorders (ASD) given the marked rise in ASD diagnosis over the past decade. Functional magnetic resonance imaging (fMRI) has begun to address this need, but few fMRI studies have evaluated age-related changes in ASD. Therefore, we conducted a developmental analysis of activation likelihood estimation (ALE) meta-analysis to compare child versus adult ASD fMRI studies. We hypothesized that children and adolescents with ASD (<18 years old) would rely less on prefrontal cortex structures than adults (≥18 years old). METHOD PubMed and PsycInfo literature searches were conducted to identify task-dependent fMRI studies of children or adults with ASD. Then recent GingerALE software improvements were leveraged to perform direct comparisons of child (n = 18) versus adult (n = 24) studies. RESULTS ALE meta-analyses of social tasks showed that children and adolescents with ASD versus adults had significantly greater hyperactivation in the left post-central gyrus, and greater hypoactivation in the right hippocampus and right superior temporal gyrus. ALE meta-analyses of nonsocial tasks showed that children with ASD versus adults had significantly greater hyperactivation in the right insula and left cingulate gyrus, and hypoactivation in the right middle frontal gyrus. CONCLUSION Our data suggest that the neural alterations associated with ASD are not static, occurring only in early childhood. Instead, children with ASD have altered neural activity compared to adults during both social and nonsocial tasks, especially in fronto-temporal structures. Longitudinal neuroimaging studies are required to examine these changes prospectively, as potential targets for brain-based treatments for ASD.
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Affiliation(s)
- Daniel P. Dickstein
- Bradley Hospital’s PediMIND Program and the Alpert Medical School of Brown University
| | | | - Brooke L. Reidy
- Bradley Hospital’s PediMIND Program and the Alpert Medical School of Brown University
| | - Thania Galvan
- Bradley Hospital’s PediMIND Program and the Alpert Medical School of Brown University
| | - Kerri L. Kim
- Bradley Hospital’s PediMIND Program and the Alpert Medical School of Brown University
| | - Karen E. Seymour
- Bradley Hospital’s PediMIND Program and the Alpert Medical School of Brown University
| | | | | | - Rowland P. Barrett
- Bradley Hospital’s Center for Autism and Developmental Disabilities and the Alpert Medical School of Brown University
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40
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Rogers BP, Sheffield JM, Luksik AS, Heckers S. Systematic Error in Hippocampal Volume Asymmetry Measurement is Minimal with a Manual Segmentation Protocol. Front Neurosci 2012; 6:179. [PMID: 23248580 PMCID: PMC3521226 DOI: 10.3389/fnins.2012.00179] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2012] [Accepted: 11/26/2012] [Indexed: 11/13/2022] Open
Abstract
Hemispheric asymmetry of hippocampal volume is a common finding that has biological relevance, including associations with dementia and cognitive performance. However, a recent study has reported the possibility of systematic error in measurements of hippocampal asymmetry by magnetic resonance volumetry. We manually traced the volumes of the anterior and posterior hippocampus in 40 healthy people to measure systematic error related to image orientation. We found a bias due to the side of the screen on which the hippocampus was viewed, such that hippocampal volume was larger when traced on the left side of the screen than when traced on the right (p = 0.05). However, this bias was smaller than the anatomical right > left asymmetry of the anterior hippocampus. We found right > left asymmetry of hippocampal volume regardless of image presentation (radiological versus neurological). We conclude that manual segmentation protocols can minimize the effect of image orientation in the study of hippocampal volume asymmetry, but our confirmation that such bias exists suggests strategies to avoid it in future studies.
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Affiliation(s)
- Baxter P Rogers
- Department of Radiology and Radiological Sciences, Vanderbilt University Nashville, TN, USA ; Department of Biomedical Engineering, Vanderbilt University Nashville, TN, USA
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Maltbie E, Bhatt K, Paniagua B, Smith RG, Graves MM, Mosconi MW, Peterson S, White S, Blocher J, El-Sayed M, Hazlett HC, Styner MA. Asymmetric bias in user guided segmentations of brain structures. Neuroimage 2012; 59:1315-23. [PMID: 21889995 PMCID: PMC3230681 DOI: 10.1016/j.neuroimage.2011.08.025] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2011] [Revised: 07/27/2011] [Accepted: 08/11/2011] [Indexed: 10/17/2022] Open
Abstract
Brain morphometric studies often incorporate comparative hemispheric asymmetry analyses of segmented brain structures. In this work, we present evidence that common user guided structural segmentation techniques exhibit strong left-right asymmetric biases and thus fundamentally influence any left-right asymmetry analyses. In this study, MRI scans from ten pediatric subjects were employed for studying segmentations of amygdala, globus pallidus, putamen, caudate, and lateral ventricle. Additionally, two pediatric and three adult scans were used for studying hippocampus segmentation. Segmentations of the sub-cortical structures were performed by skilled raters using standard manual and semi-automated methods. The left-right mirrored versions of each image were included in the data and segmented in a random order to assess potential left-right asymmetric bias. Using shape analysis we further assessed whether the asymmetric bias is consistent across subjects and raters with the focus on the hippocampus. The user guided segmentation techniques on the sub-cortical structures exhibited left-right asymmetric volume bias with the hippocampus displaying the most significant asymmetry values (p<<0.01). The hippocampal shape analysis revealed the bias to be strongest on the lateral side of the body and medial side of the head and tail. The origin of this asymmetric bias is considered to be based in laterality of visual perception; therefore segmentations with any degree of user interaction contain an asymmetric bias. The aim of our study is to raise awareness in the neuroimaging community regarding the presence of the asymmetric bias and its influence on any left-right hemispheric analyses. We also recommend reexamining previous research results in the light of this new finding.
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Affiliation(s)
- Eric Maltbie
- Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA.
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