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Gil N, Tabari A, Lo WC, Clifford B, Lang M, Awan K, Gaudet K, Splitthoff DN, Polak D, Cauley S, Huang SY. Quantitative Evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) MPRAGE for Morphometric Analysis of Brain Tissue in Patients Undergoing Evaluation for Memory Loss. Neuroimage 2024:120865. [PMID: 39349147 DOI: 10.1016/j.neuroimage.2024.120865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2024] [Revised: 09/20/2024] [Accepted: 09/23/2024] [Indexed: 10/02/2024] Open
Abstract
BACKGROUND Three-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings. METHODS We evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia. In part (1), we used a set of 108 MPRAGE reconstructed images derived from 12 healthy volunteers to systematically assess the effectiveness of SAMER in correcting varying degrees of motion corruption, ranging from mild to severe. In part (2), 29 patients who were scheduled for brain MRI with memory loss protocol and had motion corruption on their clinical MPRAGE scans were prospectively enrolled. RESULTS In part (1), SAMER resulted in effective correction of motion-induced cortical volume and thickness reductions. We observed systematic increases in the estimated cortical volume and thickness across all neuroanatomical regions and a relative reduction in percent error values compared to reference standard scans of up to 66% for the cerebral white matter volume. In part (2), SAMER resulted in statistically significant volume increases across anatomical regions, with the most pronounced increases seen in the parietal and temporal lobes, and general reductions in percent error relative to reference standard clinical scans. CONCLUSION SAMER improves the accuracy of morphometry through systematic increases and recovery of the estimated cortical volume and cortical thickness following motion correction, which may affect the evaluation of regional cortical atrophy in patients undergoing evaluation for dementia.
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Affiliation(s)
- Nelson Gil
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | | | - Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Komal Awan
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Kyla Gaudet
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | | | - Stephen Cauley
- Harvard Medical School, Boston, MA, USA; Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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Jung W, Jeong G, Kim S, Hwang I, Choi SH, Jeon YH, Choi KS, Lee JY, Yoo RE, Yun TJ, Kang KM. Reliability of brain volume measures of accelerated 3D T1-weighted images with deep learning-based reconstruction. Neuroradiology 2024:10.1007/s00234-024-03461-5. [PMID: 39316090 DOI: 10.1007/s00234-024-03461-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024]
Abstract
PURPOSE The time-intensive nature of acquiring 3D T1-weighted MRI and analyzing brain volumetry limits quantitative evaluation of brain atrophy. We explore the feasibility and reliability of deep learning-based accelerated MRI scans for brain volumetry. METHODS This retrospective study collected 3D T1-weighted data using 3T from 42 participants for the simulated acceleration dataset and 48 for the validation dataset. The simulated acceleration dataset consists of three sets at different simulated acceleration levels (Simul-Accel) corresponding to level 1 (65% undersampling), 2 (70%), and 3 (75%). These images were then subjected to deep learning-based reconstruction (Simul-Accel-DL). Conventional images (Conv) without acceleration and DL were set as the reference. In the validation dataset, DICOM images were collected from Conv and accelerated scan with DL-based reconstruction (Accel-DL). The image quality of Simul-Accel-DL was evaluated using quantitative error metrics. Volumetric measurements were evaluated using intraclass correlation coefficients (ICCs) and linear regression analysis in both datasets. The volumes were estimated by two software, NeuroQuant and DeepBrain. RESULTS Simul-Accel-DL across all acceleration levels revealed comparable or better error metrics than Simul-Accel. In the simulated acceleration dataset, ICCs between Conv and Simul-Accel-DL in all ROIs exceeded 0.90 for volumes and 0.77 for normative percentiles at all acceleration levels. In the validation dataset, ICCs for volumes > 0.96, ICCs for normative percentiles > 0.89, and R2 > 0.93 at all ROIs except pallidum demonstrated good agreement in both software. CONCLUSION DL-based reconstruction achieves clinical feasibility of 3D T1 brain volumetric MRI by up to 75% acceleration relative to full-sampled acquisition.
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Affiliation(s)
- Woojin Jung
- AIRS Medical, 223, Teheran-ro, Gangnam-gu, Seoul, 06142, Republic of Korea
| | - Geunu Jeong
- AIRS Medical, 223, Teheran-ro, Gangnam-gu, Seoul, 06142, Republic of Korea
| | - Sohyun Kim
- AIRS Medical, 223, Teheran-ro, Gangnam-gu, Seoul, 06142, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Young Hun Jeon
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Ji Ye Lee
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Roh-Eul Yoo
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Tae Jin Yun
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
- Department of Radiology, Seoul National University College of Medicine, 103 Daehak- ro, Jongno-gu, Seoul, 03080, Republic of Korea.
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3
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Jiang Y, Gao Y, Dong D, Sun X, Situ W, Yao S. The amygdala volume moderates the relationship between childhood maltreatment and callous-unemotional traits in adolescents with conduct disorder. Eur Child Adolesc Psychiatry 2024:10.1007/s00787-024-02482-y. [PMID: 38832960 DOI: 10.1007/s00787-024-02482-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 05/21/2024] [Indexed: 06/06/2024]
Abstract
CU traits, characterized by shallow affect, lack of fear, and absence of remorse, have been moderately associated with childhood maltreatment in a recent meta-analysis. However, the potential impact of brain structures remains undetermined. This paper examines the relationship between callous-unemotional (CU) traits, childhood maltreatment, and amygdala volumes. In this study, we used a region-of-interest (ROI) analysis to explore the interaction between the volumes of the amygdala, childhood maltreatment, and the manifestation of CU traits in adolescents diagnosed with conduct disorder (CD, N = 67), along with a comparison group of healthy-control youths (HCs, N = 89). The ROI analysis revealed no significant group differences in the bilateral amygdalar volumes. Significant positive correlation was discovered between all forms of child maltreatment (except for physical neglect) and CU traits across subjects. But the interaction of physical abuse and amygdala volumes was only significant within CD patients. Notably, a sensitivity analysis suggested that gender significantly influences these findings. These results contribute critical insights into the etiology of CU traits, emphasizing the need for customized clinical assessment tools and intervention strategies.
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Affiliation(s)
- Yali Jiang
- Department of Psychology, School of Education Science, Hunan Normal University, Changsha, People's Republic of China.
- Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, People's Republic of China.
- Institute for Interdisciplinary Studies, Hunan Normal University, Changsha, People's Republic of China.
- Research Base for Mental Health Education of Hunan Province, Hunan Normal University, Changsha, People's Republic of China.
- School of Psychology, South China Normal University, Guangzhou, People's Republic of China.
| | - Yidian Gao
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK
| | - Daifeng Dong
- Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Xiaoqiang Sun
- Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Weijun Situ
- Department of Radiology, the Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Shuqiao Yao
- Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
- National Clinical Research Center on Psychiatry and Psychology, Changsha, People's Republic of China
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Jiang Y, Gao Y, Dong D, Sun X, Situ W, Yao S. Brain Anatomy in Boys with Conduct Disorder: Differences Among Aggression Subtypes. Child Psychiatry Hum Dev 2024; 55:3-13. [PMID: 35704134 DOI: 10.1007/s10578-022-01360-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/01/2022] [Indexed: 11/03/2022]
Abstract
Aggression is a core feature of conduct disorder (CD), but the motivation, execution of aggression may vary. A deeper understanding of the neural substrates of aggressive behaviours is critical for effective clinical intervention. Seventy-six Boys with CD (50 with impulsive aggression (I-CD) and 26 with premeditated aggression (P-CD)) and 69 healthy controls (HCs) underwent a structural MRI scan and behavioural assessments. Whole-brain analyses revealed that, compared to HCs, the I-CD group showed significant cortical thinning in the right frontal cortex, while the P-CD group demonstrated significant folding deficits in the bilateral superior parietal cortex. Both types of aggression negatively correlated with the left amygdala volume, albeit in different ways. The present results demonstrated that the complex nature of aggression relies on differentiated anatomical substrates, highlighting the importance of exploring differential circuit-targeted interventions for CD patients.
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Affiliation(s)
- Yali Jiang
- Medical Psychological Center, the Second Xiangya Hospital of Central South University, No. 139, Middle Renmin Road, 410011, Changsha, Hunan, People's Republic of China
- Department of Radiology, the Second Xiangya Hospital, Central South University, 139, Middle Renmin Road, 410011, Changsha, Hunan, People's Republic of China
- Key Laboratory of Brain, Cognition and Education Sciences, South China Normal University, Ministry of Education, Guangzhou, China
- School of Psychology, South China Normal University, Guangzhou, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Yidian Gao
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, China
| | - Daifeng Dong
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Xiaoqiang Sun
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China
| | - Weijun Situ
- Department of Radiology, the Second Xiangya Hospital, Central South University, 139, Middle Renmin Road, 410011, Changsha, Hunan, People's Republic of China.
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
| | - Shuqiao Yao
- Medical Psychological Center, the Second Xiangya Hospital of Central South University, No. 139, Middle Renmin Road, 410011, Changsha, Hunan, People's Republic of China.
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, China.
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, UK.
- Medical Psychological Center, the Second Xiangya Hospital, Central South University, Changsha, China.
- National Clinical Research Center on Psychiatry and Psychology, Changsha, China.
- Medical Psychological Institute of Central South University, Changsha, China.
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Gentreau M, Maller JJ, Meslin C, Cyprien F, Lopez-Castroman J, Artero S. Is Hippocampal Volume a Relevant Early Marker of Dementia? Am J Geriatr Psychiatry 2023; 31:932-942. [PMID: 37394314 DOI: 10.1016/j.jagp.2023.05.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/09/2023] [Accepted: 05/31/2023] [Indexed: 07/04/2023]
Abstract
OBJECTIVE Hippocampal volume (HV) is a key imaging marker to improve Alzheimer's disease risk prediction. However, longitudinal studies are rare, and hippocampus may also be implicated in the subtle aging-related cognitive decline observed in dementia-free individuals. Our aim was to determine whether HV, measured by manual or automatic segmentation, is associated with dementia risk and cognitive decline in participants with and without incident dementia. METHODS At baseline, 510 dementia-free participants from the French longitudinal ESPRIT cohort underwent magnetic resonance imaging. HV was measured by manual and by automatic segmentation (FreeSurfer 6.0). The presence of dementia and cognitive functions were investigated at each follow-up (2, 4, 7, 10, 12, and 15 years). Cox proportional hazards models and linear mixed models were used to assess the association of HV with dementia risk and with cognitive decline, respectively. RESULTS During the 15-years follow-up, 42 participants developed dementia. Reduced HV (regardless of the measurement method) was significantly associated with higher dementia risk and cognitive decline in the whole sample. However, only the automatically measured HV was associated with cognitive decline in dementia-free participants. CONCLUSION These results suggest that HV can be used to predict the long-term risk of dementia but also cognitive decline in a dementia-free population. This raises the question of the relevance of HV measurement as an early marker of dementia in the general population.
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Affiliation(s)
- Mélissa Gentreau
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Jerome J Maller
- Monash Alfred Psychiatry Research Centre (JJM), Melbourne, Victoria, Australia; General Electric Healthcare (JJM), Richmond, Melbourne, Victoria, Australia
| | - Chantal Meslin
- Centre for Mental Health Research (CM), Australian National University, Canberra, Australia
| | - Fabienne Cyprien
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Jorge Lopez-Castroman
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France; Department of Adult Psychiatry (JLC), Nimes University Hospital, Nimes, France; Centro de Investigación Biomédica en Red de Salud Mental (JLC), Madrid, Spain
| | - Sylvaine Artero
- Institute of Functional Genomics (MG, FC, JLC, SA), University of Montpellier, CNRS, INSERM, Montpellier, France.
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Hari E, Kurt E, Ulasoglu-Yildiz C, Bayram A, Bilgic B, Demiralp T, Gurvit H. Morphometric analysis of medial temporal lobe subregions in Alzheimer's disease using high-resolution MRI. Brain Struct Funct 2023; 228:1885-1899. [PMID: 37486408 DOI: 10.1007/s00429-023-02683-2] [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: 01/16/2023] [Accepted: 07/07/2023] [Indexed: 07/25/2023]
Abstract
The spread pattern of progressive degeneration seen in Alzheimer's disease (AD) to small-scale medial temporal lobe subregions is critical for early diagnosis. In this context, it was aimed to examine the morphometric changes of the hippocampal subfields, amygdala nuclei, entorhinal cortex (ERC), and parahippocampal cortex (PHC) using MRI. MRI data of patients diagnosed with 20 Alzheimer's disease dementia (ADD), 30 amnestic mild cognitive impairment (aMCI), and 30 subjective cognitive impairment (SCI) without demographic differences were used. Segmentation and parcellation were performed using FreeSurfer. The segmentation process obtained volume values of 12 hippocampal subfields and 9 amygdala nuclei. Thickness values of ERC and PHC were calculated with the parcellation process. ANCOVA was performed using age, education and gender as covariates to evaluate the intergroup differences. Linear discriminant analysis was used to investigate whether atrophy predicted groups at an early stage. ERC and PHC thickness decreased significantly throughout the disease continuum, while only ERC was affected in the early stage. When the hippocampal and amygdala subfields were compared volumetrically, significant differences were found in the amygdala between the SCI and aMCI groups. In the early period, only volume reduction in the anterior amygdaloid area of the amygdala nuclei exceeded the significance threshold. Research on AD primarily focuses on original hippocampocentric structures and their main function which is episodic memory. Our results emphasized the significance of so far relatively neglected olfactocentric structures and their functions, such as smell and social cognition in the pre-dementia stages of the AD process.
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Affiliation(s)
- Emre Hari
- Graduate School of Health Sciences, Istanbul University, Bozdogan Kemeri Caddesi No:8 Vezneciler Hamami Sokagi, Vezneciler, 34216, Fatih, Istanbul, Turkey.
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey.
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey.
| | - Elif Kurt
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Cigdem Ulasoglu-Yildiz
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Ali Bayram
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Neuroscience, Aziz Sancar Institute of Experimental Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Başar Bilgic
- Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Tamer Demiralp
- Hulusi Behcet Life Sciences Research Laboratory, Neuroimaging Unit, Istanbul University, 34093, Istanbul, Turkey
- Department of Physiology, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
| | - Hakan Gurvit
- Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul Faculty of Medicine, Istanbul University, 34093, Istanbul, Turkey
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Quek YE, Bourgeat P, Fung YL, Vogrin SJ, Collins SJ, Bowden SC. Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease. Psychiatry Res Neuroimaging 2023; 335:111707. [PMID: 37639979 DOI: 10.1016/j.pscychresns.2023.111707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/25/2023] [Accepted: 08/09/2023] [Indexed: 08/31/2023]
Abstract
The current study aimed to validate entorhinal and transentorhinal cortical volumes measured by the automated segmentation tool Automatic Segmentation of Hippocampal Subfields (ASHS-T1). The study sample comprised 34 healthy controls (HCs), 37 individuals with amnestic mild cognitive impairment (aMCI), and 29 individuals with Alzheimer's disease (AD) dementia from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Entorhinal and transentorhinal cortical volumes were assessed using ASHS-T1, manual segmentation, as well as a widely used automated segmentation tool, FreeSurfer v6.0.1. Mean differences, intraclass correlation coefficients, and Bland-Altman plots were computed. ASHS-T1 tended to underestimate entorhinal and transentorhinal cortical volumes relative to manual segmentation and FreeSurfer. There was variable consistency and low agreement between ASHS-T1 and manual segmentation volumes. There was low-to-moderate consistency and low agreement between ASHS-T1 and FreeSurfer volumes. There was a trend toward higher consistency and agreement for the entorhinal cortex in the aMCI and AD groups compared to the HC group. Despite the differences in volume measurements, ASHS-T1 was sensitive to entorhinal and transentorhinal cortical atrophy in both early and late disease stages. Based on the current study, ASHS-T1 appears to be a promising tool for automated entorhinal and transentorhinal cortical volume measurement in individuals with likely underlying AD.
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Affiliation(s)
- Yi-En Quek
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.
| | - Pierrick Bourgeat
- The Australian e-Health Research Centre, CSIRO Health and Biosecurity, Brisbane, Queensland, Australia
| | - Yi Leng Fung
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Simon J Vogrin
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Steven J Collins
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia; Department of Medicine (RMH), The University of Melbourne, Parkville, Victoria, Australia
| | - Stephen C Bowden
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia; Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
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Loong S, Barnes S, Gatto NM, Chowdhury S, Lee GJ. Omega-3 Fatty Acids, Cognition, and Brain Volume in Older Adults. Brain Sci 2023; 13:1278. [PMID: 37759879 PMCID: PMC10526215 DOI: 10.3390/brainsci13091278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 08/19/2023] [Accepted: 08/31/2023] [Indexed: 09/29/2023] Open
Abstract
The elderly population is growing at increased rates and is expected to double in size by 2050 in the United States and worldwide. The consumption of healthy foods and enriched diets have been associated with improved cognition and brain health. The key nutrients common to many healthy foods and diets are the omega-3 polyunsaturated fatty acids (omega-3 FAs), such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). We explored whether omega-3 FA levels are associated with brain volume and cognition. Forty healthy, cognitively normal, Seventh-day Adventist older adults (mean age 76.3 years at MRI scan, 22 females) completed neurocognitive testing, a blood draw, and structural neuroimaging from 2016 to 2018. EPA and an overall omega-3 index were associated with individual measures of delayed recall (RAVLT-DR) and processing speed (Stroop Color) as well as entorhinal cortex thickness. EPA, DHA, and the omega-3 index were significantly correlated with the total white matter volume. The entorhinal cortex, frontal pole, and total white matter were associated with higher scores on delayed memory recall. This exploratory study found that among healthy, cognitively older adults, increased levels of omega-3 FAs are associated with better memory, processing speed, and structural brain measures.
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Affiliation(s)
- Spencer Loong
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92350, USA;
| | - Samuel Barnes
- Department of Radiology, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA; (S.B.)
| | - Nicole M. Gatto
- School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA;
| | - Shilpy Chowdhury
- Department of Radiology, School of Medicine, Loma Linda University, Loma Linda, CA 92350, USA; (S.B.)
| | - Grace J. Lee
- Department of Psychology, School of Behavioral Health, Loma Linda University, Loma Linda, CA 92350, USA;
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Stocks J, Heywood A, Popuri K, Beg MF, Rosen H, Wang L. Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum. J Alzheimers Dis 2023; 92:513-527. [PMID: 36776061 DOI: 10.3233/jad-220975] [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: 02/10/2023]
Abstract
BACKGROUND The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear. OBJECTIVE To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points. METHODS We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up. RESULTS In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12. CONCLUSION These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ashley Heywood
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Canada.,Memorial University of Newfoundland, Department of Computer Science, St. John's, NL, Canada
| | | | - Howie Rosen
- School of Medicine, University of California, San Francisco, CA, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA
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10
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Jiang Y, Gao Y, Dong D, Sun X, Situ W, Yao S. Structural abnormalities in adolescents with conduct disorder and high versus low callous unemotional traits. Eur Child Adolesc Psychiatry 2023; 32:193-203. [PMID: 34635947 DOI: 10.1007/s00787-021-01890-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 10/01/2021] [Indexed: 10/20/2022]
Abstract
There may be distinct conduct disorder (CD) etiologies and neural morphologies in adolescents with high callous unemotional (CU) traits versus low CU traits. Here, we employed surface-based morphometry methods to investigate morphological differences in adolescents diagnosed with CD [42 with high CU traits (CD-HCU) and 40 with low CU traits (CD-LCU)] and healthy controls (HCs, N = 115) in China. Whole-brain analyses revealed significantly increased cortical surface area (SA) in the left inferior temporal cortex and the right precuneus, but decreased SA in the left superior temporal cortex in the CD-LCU group, compared with the HC group. There were no significant cortical SA differences between the CD-HCU and the HC groups. Compared to the CD-HCU group, the CD-LCU group had a greater cortical thickness (CT) in the left rostral middle frontal cortex. Region-of-interest analyses revealed significant group differences in the right hippocampus, with CD-HCU group having lower right hippocampal volumes than HCs. We did not detect significant group differences in the amygdalar volume, however, the right amygdalar volume was found to be a significant moderator of the correlation between CU traits and the proactive aggression in CD patients. The present results suggested that the manifestations of CD differ between those with high CU traits versus low CU traits, and underscore the importance of sample characteristics in understanding the neural substrates of CD.
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Affiliation(s)
- Yali Jiang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, South China Normal University, Guangzhou, People's Republic of China
- School of Psychology, South China Normal University, Guangzhou, People's Republic of China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou, People's Republic of China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, People's Republic of China
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Yidian Gao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Daifeng Dong
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Xiaoqiang Sun
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Weijun Situ
- Department of Radiology, the Second Xiangya Hospital, Central South University, Changsha, People's Republic of China
| | - Shuqiao Yao
- Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, People's Republic of China.
- National Clinical Research Center on Psychiatry and Psychology, Changsha, People's Republic of China.
- Medical Psychological Institute of Central South University, Changsha, People's Republic of China.
- National Clinical Research Center for Mental Disorders, Changsha, People's Republic of China.
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11
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Lidén S, Farahmand D, Laurell K. Ventricular volume in relation to lumbar CSF levels of amyloid-β 1–42, tau and phosphorylated tau in iNPH, is there a dilution effect? Fluids Barriers CNS 2022; 19:59. [PMID: 35843939 PMCID: PMC9288679 DOI: 10.1186/s12987-022-00353-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/23/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Levels of the biomarkers amyloid-β 1–42 (Aβ42), tau and phosphorylated tau (p-tau) are decreased in the cerebrospinal fluid (CSF) of patients with idiopathic normal pressure hydrocephalus (iNPH). The mechanism behind this is unknown, but one potential explanation is dilution by excessive CSF volumes. The aim of this study was to investigate the presence of a dilution effect, by studying the relationship between ventricular volume (VV) and the levels of the CSF biomarkers.
Methods
In this cross-sectional observational study, preoperative magnetic resonance imaging (MRI) and lumbar CSF was acquired from 136 patients with a median age of 76 years, 89 men and 47 females, selected for surgical treatment for iNPH. The CSF volume of the lateral and third ventricles was segmented on MRI and related to preoperative concentrations of Aβ42, tau and p-tau.
Results
In the total sample VV (Median 140.7 mL) correlated weakly (rs = − 0.17) with Aβ42 (Median 534 pg/mL), but not with tau (Median 216 pg/mL) nor p-tau (Median 31 pg/mL). In a subgroup analysis, the correlation between VV and Aβ42 was only present in the male group (rs = − 0.22, p = 0.038). Further, Aβ42 correlated positively with tau (rs = 0.30, p = 0.004) and p-tau (rs = 0.26, p = 0.012) in males but not in females.
Conclusions
The findings did not support a major dilution effect in iNPH, at least not in females. The only result in favor for dilution was a weak negative correlation between VV and Aβ42 but not with the other lumbar CSF biomarkers. The different results between males and females suggest that future investigations of the CSF pattern in iNPH would gain from sex-based subgroup analysis.
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12
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Ferraro PM, Gualco L, Costagli M, Schiavi S, Ponzano M, Signori A, Massa F, Pardini M, Castellan L, Levrero F, Zacà D, Piredda GF, Hilbert T, Kober T, Roccatagliata L. Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A comparison of derived brain volume measurements. Phys Med 2022; 103:166-174. [DOI: 10.1016/j.ejmp.2022.10.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/16/2022] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
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13
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de Mélo Silva Júnior ML, Diniz PRB, de Souza Vilanova MV, Basto GPT, Valença MM. Brain ventricles, CSF and cognition: a narrative review. Psychogeriatrics 2022; 22:544-552. [PMID: 35488797 DOI: 10.1111/psyg.12839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 03/07/2022] [Accepted: 04/12/2022] [Indexed: 11/29/2022]
Abstract
The brain ventricles are structures that have been related to cognition since antiquity. They are essential components in the development and maintenance of brain functions. The aging process runs with the enlargement of ventricles and is related to a less selective blood-cerebrospinal fluid barrier and then a more toxic cerebrospinal fluid environment. The study of brain ventricles as a biological marker of aging is promissing because they are structures easily identified in neuroimaging studies, present good inter-rater reliability, and measures of them can identify brain atrophy earlier than cortical structures. The ventricular system also plays roles in the development of dementia, since dysfunction in the clearance of beta-amyloid protein is a key mechanism in sporadic Alzheimer's disease. The morphometric and volumetric studies of the brain ventricles can help to distinguish between healthy elderly and persons with mild cognitive impairment (MCI) and dementia. Brain ventricle data may contribute to the appropriate allocation of individuals in groups at higher risk for MCI-dementia progression in clinical trials and to measuring therapeutic responses in these studies, as well as providing differential diagnosis, such as normal pressure hydrocephalus. Here, we reviewed the pathophysiology of healthy aging and cognitive decline, focusing on the role of the choroid plexus and brain ventricles in this process.
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Affiliation(s)
- Mário Luciano de Mélo Silva Júnior
- Medical School, Universidade Federal de Pernambuco, Recife, Brazil.,Medical School, Centro Universitário Maurício de Nassau, Recife, Brazil.,Neurology Unit, Hospital da Restauração, Recife, Brazil
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14
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Seo SY, Kim SJ, Oh JS, Chung J, Kim SY, Oh SJ, Joo S, Kim JS. Unified Deep Learning-Based Mouse Brain MR Segmentation: Template-Based Individual Brain Positron Emission Tomography Volumes-of-Interest Generation Without Spatial Normalization in Mouse Alzheimer Model. Front Aging Neurosci 2022; 14:807903. [PMID: 35309883 PMCID: PMC8931825 DOI: 10.3389/fnagi.2022.807903] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/17/2022] [Indexed: 02/03/2023] Open
Abstract
Although skull-stripping and brain region segmentation are essential for precise quantitative analysis of positron emission tomography (PET) of mouse brains, deep learning (DL)-based unified solutions, particularly for spatial normalization (SN), have posed a challenging problem in DL-based image processing. In this study, we propose an approach based on DL to resolve these issues. We generated both skull-stripping masks and individual brain-specific volumes-of-interest (VOIs—cortex, hippocampus, striatum, thalamus, and cerebellum) based on inverse spatial normalization (iSN) and deep convolutional neural network (deep CNN) models. We applied the proposed methods to mutated amyloid precursor protein and presenilin-1 mouse model of Alzheimer’s disease. Eighteen mice underwent T2-weighted MRI and 18F FDG PET scans two times, before and after the administration of human immunoglobulin or antibody-based treatments. For training the CNN, manually traced brain masks and iSN-based target VOIs were used as the label. We compared our CNN-based VOIs with conventional (template-based) VOIs in terms of the correlation of standardized uptake value ratio (SUVR) by both methods and two-sample t-tests of SUVR % changes in target VOIs before and after treatment. Our deep CNN-based method successfully generated brain parenchyma mask and target VOIs, which shows no significant difference from conventional VOI methods in SUVR correlation analysis, thus establishing methods of template-based VOI without SN.
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Affiliation(s)
- Seung Yeon Seo
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- Department of Biomedical Engineering, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
| | - Soo-Jong Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- Department of Biomedical Engineering, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Songpa-gu, South Korea
- Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon-si, South Korea
| | - Jungsu S. Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- *Correspondence: Jungsu S. Oh, ;
| | - Jinwha Chung
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
| | - Seog-Young Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
- Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
| | - Seung Jun Oh
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
| | - Segyeong Joo
- Department of Biomedical Engineering, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
| | - Jae Seung Kim
- Department of Nuclear Medicine, Asan Medical Center, University of Ulsan College of Medicine, Songpa-gu, South Korea
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15
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Hedges EP, Dimitrov M, Zahid U, Brito Vega B, Si S, Dickson H, McGuire P, Williams S, Barker GJ, Kempton MJ. Reliability of structural MRI measurements: The effects of scan session, head tilt, inter-scan interval, acquisition sequence, FreeSurfer version and processing stream. Neuroimage 2022; 246:118751. [PMID: 34848299 PMCID: PMC8784825 DOI: 10.1016/j.neuroimage.2021.118751] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 11/18/2021] [Accepted: 11/20/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Large-scale longitudinal and multi-centre studies are used to explore neuroimaging markers of normal ageing, and neurodegenerative and mental health disorders. Longitudinal changes in brain structure are typically small, therefore the reliability of automated techniques is crucial. Determining the effects of different factors on reliability allows investigators to control those adversely affecting reliability, calculate statistical power, or even avoid particular brain measures with low reliability. This study examined the impact of several image acquisition and processing factors and documented the test-retest reliability of structural MRI measurements. METHODS In Phase I, 20 healthy adults (11 females; aged 20-30 years) were scanned on two occasions three weeks apart on the same scanner using the ADNI-3 protocol. On each occasion, individuals were scanned twice (repetition), after re-entering the scanner (reposition) and after tilting their head forward. At one year follow-up, nine returning individuals and 11 new volunteers were recruited for Phase II (11 females; aged 22-31 years). Scans were acquired on two different scanners using the ADNI-2 and ADNI-3 protocols. Structural images were processed using FreeSurfer (v5.3.0, 6.0.0 and 7.1.0) to provide subcortical and cortical volume, cortical surface area and thickness measurements. Intra-class correlation coefficients (ICC) were calculated to estimate test-retest reliability. We examined the effect of repetition, reposition, head tilt, time between scans, MRI sequence and scanner on reliability of structural brain measurements. Mean percentage differences were also calculated in supplementary analyses. RESULTS Using the FreeSurfer v7.1.0 longitudinal pipeline, we observed high reliability for subcortical and cortical volumes, and cortical surface areas at repetition, reposition, three weeks and one year (mean ICCs>0.97). Cortical thickness reliability was lower (mean ICCs>0.82). Head tilt had the greatest adverse impact on ICC estimates, for example reducing mean right cortical thickness to ICC=0.74. In contrast, changes in ADNI sequence or MRI scanner had a minimal effect. We observed an increase in reliability for updated FreeSurfer versions, with the longitudinal pipeline consistently having a higher reliability than the cross-sectional pipeline. DISCUSSION Longitudinal studies should monitor or control head tilt to maximise reliability. We provided the ICC estimates and mean percentage differences for all FreeSurfer brain regions, which may inform power analyses for clinical studies and have implications for the design of future longitudinal studies.
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Affiliation(s)
- Emily P Hedges
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom.
| | - Mihail Dimitrov
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - Uzma Zahid
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom
| | - Barbara Brito Vega
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom
| | - Shuqing Si
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom
| | - Hannah Dickson
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - Philip McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom
| | - Steven Williams
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - Gareth J Barker
- Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London SE5 8AF, United Kingdom
| | - Matthew J Kempton
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London SE5 8AF, United Kingdom
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16
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Lee B, Yao X, Shen L. Genome-Wide association study of quantitative biomarkers identifies a novel locus for alzheimer's disease at 12p12.1. BMC Genomics 2022; 23:85. [PMID: 35086473 PMCID: PMC8796646 DOI: 10.1186/s12864-021-08269-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Accepted: 12/14/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genetic study of quantitative biomarkers in Alzheimer's Disease (AD) is a promising method to identify novel genetic factors and relevant endophenotypes, which provides valuable information to deconvolute mechanistic complexity and better understand disease subtypes. RESULTS Using the data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we performed a genome-wide association study (GWAS) between 565,373 single nucleotide polymorphisms (SNPs) and 16 key AD biomarkers from 1,576 subjects at four visits. We identified a novel locus rs5011804 at 12p12.1 significantly associated with several AD biomarkers, including three cognitive traits (CDRSB, FAQ, ADAS13) and one imaging trait (fusiform volume). Additional mediation and interaction analyses investigated the relationships among this SNP, relevant biomarkers, and clinical diagnosis, confirming and further elaborating the genetic effects seen in the GWAS. CONCLUSION Our GWAS not only affirms key AD genes but also suggests the promising role of the SNP rs5011804 due to its associations with several AD cognitive and imaging outcomes. The SNP rs5011804 has a reported association with adult asthma and slightly affects intracranial volume but has not been associated with AD before. Our novel findings contribute to a more comprehensive view of the molecular mechanism behind AD.
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Affiliation(s)
- Brian Lee
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Xiaohui Yao
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
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17
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Quek YE, Fung YL, Cheung MWL, Vogrin SJ, Collins SJ, Bowden SC. Agreement Between Automated and Manual MRI Volumetry in Alzheimer's Disease: A Systematic Review and Meta-Analysis. J Magn Reson Imaging 2021; 56:490-507. [PMID: 34964531 DOI: 10.1002/jmri.28037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Automated magnetic resonance imaging (MRI) volumetry is a promising tool to evaluate regional brain volumes in dementia and especially Alzheimer's disease (AD). PURPOSE To compare automated methods and the gold standard manual segmentation in measuring regional brain volumes on MRI across healthy controls, patients with mild cognitive impairment, and patients with dementia due to AD. STUDY TYPE Systematic review and meta-analysis. DATA SOURCES MEDLINE, Embase, and PsycINFO were searched through October 2021. FIELD STRENGTH 1.0 T, 1.5 T, or 3.0 T. ASSESSMENT Two review authors independently identified studies for inclusion and extracted data. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). STATISTICAL TESTS Standardized mean differences (SMD; Hedges' g) were pooled using random-effects meta-analysis with robust variance estimation. Subgroup analyses were undertaken to explore potential sources of heterogeneity. Sensitivity analyses were conducted to examine the impact of the within-study correlation between effect estimates on the meta-analysis results. RESULTS Seventeen studies provided sufficient data to evaluate the hippocampus, lateral ventricles, and parahippocampal gyrus. The pooled SMD for the hippocampus, lateral ventricles, and parahippocampal gyrus were 0.22 (95% CI -0.50 to 0.93), 0.12 (95% CI -0.13 to 0.37), and -0.48 (95% CI -1.37 to 0.41), respectively. For the hippocampal data, subgroup analyses suggested that the pooled SMD was invariant across clinical diagnosis and field strength. Subgroup analyses could not be conducted on the lateral ventricles data and the parahippocampal gyrus data due to insufficient data. The results were robust to the selected within-study correlation value. DATA CONCLUSION While automated methods are generally comparable to manual segmentation for measuring hippocampal, lateral ventricle, and parahippocampal gyrus volumes, wide 95% CIs and large heterogeneity suggest that there is substantial uncontrolled variance. Thus, automated methods may be used to measure these regions in patients with AD but should be used with caution. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Yi-En Quek
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Yi Leng Fung
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia
| | - Mike W-L Cheung
- Department of Psychology, Faculty of Arts and Social Sciences, National University of Singapore, Singapore
| | - Simon J Vogrin
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Steven J Collins
- Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Stephen C Bowden
- Melbourne School of Psychological Sciences, The University of Melbourne, Parkville, Victoria, Australia.,Department of Clinical Neurosciences, St Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
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18
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Du J, Liang P, He H, Tong Q, Gong T, Qian T, Sun Y, Zhong J, Li K. Reproducibility of volume and asymmetry measurements of hippocampus, amygdala, and entorhinal cortex on traveling volunteers: a multisite MP2RAGE prospective study. Acta Radiol 2021; 62:1381-1390. [PMID: 33121264 DOI: 10.1177/0284185120963919] [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: 11/17/2022]
Abstract
BACKGROUND Multisite studies can considerably increase the pool of normally aging individuals with neurodegenerative disorders and thereby expedite the associated research. Understanding the reproducibility of the parameters of related brain structures-including the hippocampus, amygdala, and entorhinal cortex-in multisite studies is crucial in determining the impact of healthy aging or neurodegenerative diseases. PURPOSE To estimate the reproducibility of the fascinating structures by automatic (FreeSurfer) and manual segmentation methods in a well-controlled multisite dataset. MATERIAL AND METHODS Three traveling individuals were scanned at 10 sites, which were equipped with the same equipment (3T Prisma Siemens). They used the same scan protocol (two inversion-contrast magnetization-prepared rapid gradient echo sequences) and operators. Validity coefficients (intraclass correlations coefficient [ICC]) and spatial overlap measures (Dice Similarity Coefficient [DSC]) were used to estimate the reproducibility of multisite data. RESULTS ICC and DSC values varied substantially among structures and segmentation methods, and values of manual tracing were relatively higher than the automated method. ICC and DSC values of structural parameters were greater than 0.80 and 0.60 across sites, as determined by manual tracing. Low reproducibility was observed in the amygdala parameters by automatic segmentation method (ICC = 0.349-0.529, DSC = 0.380-0.873). However, ICC and DSC scores of the hippocampus were higher than 0.60 and 0.65 by two segmentation methods. CONCLUSION This study suggests that a well-controlled multisite study could provide a reliable MRI dataset. Manual tracing of volume assessments is recommended for low reproducibility structures that require high levels of precision in multisite studies.
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Affiliation(s)
- Jiachen Du
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, PR China
| | - Peipeng Liang
- School of Psychology, Capital Normal University, Beijing, PR China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, PR China
| | - Qiqi Tong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, PR China
| | - Ting Gong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, PR China
| | - Tianyi Qian
- MR Collaboration NE Asia, Siemens Healthcare, Beijing, PR China
| | - Yi Sun
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, PR China
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou, Zhejiang, PR China
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, PR China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, PR China
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19
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Bocchetta M, Malpetti M, Todd EG, Rowe JB, Rohrer JD. Looking beneath the surface: the importance of subcortical structures in frontotemporal dementia. Brain Commun 2021; 3:fcab158. [PMID: 34458729 PMCID: PMC8390477 DOI: 10.1093/braincomms/fcab158] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/21/2021] [Indexed: 12/15/2022] Open
Abstract
Whilst initial anatomical studies of frontotemporal dementia focussed on cortical involvement, the relevance of subcortical structures to the pathophysiology of frontotemporal dementia has been increasingly recognized over recent years. Key structures affected include the caudate, putamen, nucleus accumbens, and globus pallidus within the basal ganglia, the hippocampus and amygdala within the medial temporal lobe, the basal forebrain, and the diencephalon structures of the thalamus, hypothalamus and habenula. At the most posterior aspect of the brain, focal involvement of brainstem and cerebellum has recently also been shown in certain subtypes of frontotemporal dementia. Many of the neuroimaging studies on subcortical structures in frontotemporal dementia have been performed in clinically defined sporadic cases. However, investigations of genetically- and pathologically-confirmed forms of frontotemporal dementia are increasingly common and provide molecular specificity to the changes observed. Furthermore, detailed analyses of sub-nuclei and subregions within each subcortical structure are being added to the literature, allowing refinement of the patterns of subcortical involvement. This review focuses on the existing literature on structural imaging and neuropathological studies of subcortical anatomy across the spectrum of frontotemporal dementia, along with investigations of brain–behaviour correlates that examine the cognitive sequelae of specific subcortical involvement: it aims to ‘look beneath the surface’ and summarize the patterns of subcortical involvement have been described in frontotemporal dementia.
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Affiliation(s)
- Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Maura Malpetti
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Emily G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK.,Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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20
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Combination of automated brain volumetry on MRI and quantitative tau deposition on THK-5351 PET to support diagnosis of Alzheimer's disease. Sci Rep 2021; 11:10343. [PMID: 33990649 PMCID: PMC8121780 DOI: 10.1038/s41598-021-89797-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 04/27/2021] [Indexed: 01/18/2023] Open
Abstract
Imaging biomarkers support the diagnosis of Alzheimer’s disease (AD). We aimed to determine whether combining automated brain volumetry on MRI and quantitative measurement of tau deposition on [18F] THK-5351 PET can aid discrimination of AD spectrum. From a prospective database in an IRB-approved multicenter study (NCT02656498), 113 subjects (32 healthy control, 55 mild cognitive impairment, and 26 Alzheimer disease) with baseline structural MRI and [18F] THK-5351 PET were included. Cortical volumes were quantified from FDA-approved software for automated volumetric MRI analysis (NeuroQuant). Standardized uptake value ratio (SUVR) was calculated from tau PET images for 6 composite FreeSurfer-derived regions-of-interests approximating in vivo Braak stage (Braak ROIs). On volumetric MRI analysis, stepwise logistic regression analyses identified the cingulate isthmus and inferior parietal lobule as significant regions in discriminating AD from HC and MCI. The combined model incorporating automated volumes of selected brain regions on MRI (cingulate isthmus, inferior parietal lobule, hippocampus) and SUVRs of Braak ROIs on [18F] THK-5351 PET showed higher performance than SUVRs of Braak ROIs on [18F] THK-5351 PET in discriminating AD from HC (0.98 vs 0.88, P = 0.033) but not in discriminating AD from MCI (0.85 vs 0.79, P = 0.178). The combined model showed comparable performance to automated volumes of selected brain regions on MRI in discriminating AD from HC (0.98 vs 0.94, P = 0.094) and MCI (0.85 vs 0.78; P = 0.065).
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21
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Raman F, Grandhi S, Murchison CF, Kennedy RE, Landau S, Roberson ED, McConathy J. Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER) Methodology for Research and Clinical Brain PET Applications. J Alzheimers Dis 2020; 70:1241-1257. [PMID: 31322571 DOI: 10.3233/jad-190329] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Tools for efficient evaluation of amyloid- and tau-PET images are needed in both clinical and research settings. OBJECTIVE This study was designed to validate a semi-automated image analysis methodology, called Biomarker Localization, Analysis, Visualization, Extraction, and Registration (BLAzER). We tested BLAzER using two different segmentation platforms, FreeSurfer (FS) and Neuroreader (NR), for regional brain PET quantification in participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. METHODS 127 amyloid-PET and 55 tau-PET studies with volumetric MRIs were obtained from ADNI. The BLAzER methodology utilizes segmentation of MR images by FS or NR, then visualizes and quantifies regional brain PET data using FDA-cleared software (MIM), enabling quality control to ensure optimal registration and to detect segmentation errors. RESULTS BLAzER analysis required ∼5 min plus segmentation time. BLAzER using FS segmentation showed strong agreement with ADNI for global amyloid-PET standardized uptake value ratios (SUVRs) (r = 0.9922, p < 0.001) and regional tau-PET SUVRs across all Braak staging regions (r > 0.97, p < 0.001) with high inter-operator reproducibility (ICC > 0.97) and nearly identical dichotomization as amyloid-positive or -negative (2 discrepant cases out of 127). Comparing FS versus NR segmentation with BLAzER, global SUVRs were strongly correlated for amyloid-PET (r = 0.9841, p < 0.001), but were systematically higher (4% on average) with NR, likely due to more inclusion of white matter with NR-defined regions. CONCLUSIONS BLAzER provides an efficient methodology for regional brain PET quantification. FDA-cleared components and visualization of registration reduce barriers between research and clinical applications.
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Affiliation(s)
- Fabio Raman
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.,Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Sameera Grandhi
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Charles F Murchison
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Richard E Kennedy
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA, USA
| | - Erik D Roberson
- Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA.,Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA.,Center for Neurodegeneration and Experimental Therapeutics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jonathan McConathy
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, University of Alabama at Birmingham, Birmingham, AL, USA
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22
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Biffen SC, Warton CMR, Dodge NC, Molteno CD, Jacobson JL, Jacobson SW, Meintjes EM. Validity of automated FreeSurfer segmentation compared to manual tracing in detecting prenatal alcohol exposure-related subcortical and corpus callosal alterations in 9- to 11-year-old children. Neuroimage Clin 2020; 28:102368. [PMID: 32791491 PMCID: PMC7424233 DOI: 10.1016/j.nicl.2020.102368] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 07/07/2020] [Accepted: 07/29/2020] [Indexed: 12/12/2022]
Abstract
In recent years a number of semi-automated and automated segmentation tools and brain atlases have been developed to facilitate morphometric analyses of large MRI datasets. These tools are much faster than manual tracing and demonstrate excellent test-retest reliabilities. Reliabilities of automated segmentations relative to "gold standard" manual tracings have, however, been shown to vary by brain region and in different cohorts. It remains uncertain to what extent smaller brain volumes and potential changes in grey/white matter contrasts in paediatric brains impact on the performance of automated methods, and how pathology may influence performance. This study examined whether using data from automated FreeSurfer segmentation would alter our ability, compared to manual segmentation, to detect prenatal alcohol exposure (PAE)-related volume changes in subcortical regions and the corpus callosum (CC) in pre-adolescent children. High-resolution T1-weighted images were acquired, using a sequence optimized for morphometric neuroanatomical analysis, on a Siemens 3T Allegra MRI scanner in 71 right-handed, 9- to 11-year-old children (27 fetal alcohol syndrome (FAS) and partial FAS (PFAS), 25 non-syndromal heavily exposed (HE) and 19 non-exposed controls) from a high-risk community in Cape Town, South Africa. Data from timeline follow-back interviews administered to the mothers prospectively during pregnancy were used to quantify the amount of alcohol (in ounces absolute alcohol per day, AA/day) that the children had been exposed to prenatally. Volumes of corpus callosum (CC) and bilateral caudate nuclei, hippocampi and nucleus accumbens (NA) were obtained by manual tracing and automated segmentation using both FreeSurfer versions 5.1 and 6.0. Reliability across methods was assessed using intraclass correlation (ICC) estimates for consistency and absolute agreement, and Cronbach's α. Ability to detect regions showing PAE effects was assessed separately for each segmentation method using ANOVA and linear regression of regional volumes with AA/day. Our results support findings from other studies showing excellent reliability across methods for easy-to-segment structures, such as the CC and caudate nucleus. Volumes from FreeSurfer 6.0 were smaller than those from version 5.1 in all regions except the right caudate, for which they were similar, and right hippocampus and CC, for which they were larger. Despite poor absolute agreement between methods in the NA and hippocampus, all three segmentation methods detected dose-dependent volume reductions in regions for which reliabilities on ICC consistency across methods reached at least 0.70, namely the CC, and bilateral caudate nuclei and hippocampi. PAE-related changes in the NA for which ICC consistency did not reach this minimum were inconsistent across methods and should be interpreted with caution. This is the first study to demonstrate in a pre-adolescent cohort the ability of automated segmentation with FreeSurfer to detect regional volume changes associated with pathology similar to those found using manual tracing.
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Affiliation(s)
- Stevie C Biffen
- Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Christopher M R Warton
- Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Neil C Dodge
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, USA
| | - Christopher D Molteno
- Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Joseph L Jacobson
- Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, USA; Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Sandra W Jacobson
- Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, USA; Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Ernesta M Meintjes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Neurosciences Institute, University of Cape Town, South Africa; Cape Universities Body Imaging Centre, University of Cape Town, South Africa.
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23
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Longo MGF, Conklin J, Cauley SF, Setsompop K, Tian Q, Polak D, Polackal M, Splitthoff D, Liu W, González RG, Schaefer PW, Kirsch JE, Rapalino O, Huang SY. Evaluation of Ultrafast Wave-CAIPI MPRAGE for Visual Grading and Automated Measurement of Brain Tissue Volume. AJNR Am J Neuroradiol 2020; 41:1388-1396. [PMID: 32732274 DOI: 10.3174/ajnr.a6703] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Accepted: 05/18/2020] [Indexed: 01/23/2023]
Abstract
BACKGROUND AND PURPOSE Volumetric brain MR imaging typically has long acquisition times. We sought to evaluate an ultrafast MPRAGE sequence based on Wave-CAIPI (Wave-MPRAGE) compared with standard MPRAGE for evaluation of regional brain tissue volumes. MATERIALS AND METHODS We performed scan-rescan experiments in 10 healthy volunteers to evaluate the intraindividual variability of the brain volumes measured using the standard and Wave-MPRAGE sequences. We then evaluated 43 consecutive patients undergoing brain MR imaging. Patients underwent 3T brain MR imaging, including a standard MPRAGE sequence (acceleration factor [R] = 2, acquisition time [TA] = 5.2 minutes) and an ultrafast Wave-MPRAGE sequence (R = 9, TA = 1.15 minutes for the 32-channel coil; R = 6, TA = 1.75 minutes for the 20-channel coil). Automated segmentation of regional brain volume was performed. Two radiologists evaluated regional brain atrophy using semiquantitative visual rating scales. RESULTS The mean absolute symmetrized percent change in the healthy volunteers participating in the scan-rescan experiments was not statistically different in any brain region for both the standard and Wave-MPRAGE sequences. In the patients undergoing evaluation for neurodegenerative disease, the Dice coefficient of similarity between volumetric measurements obtained from standard and Wave-MPRAGE ranged from 0.86 to 0.95. Similarly, for all regions, the absolute symmetrized percent change for brain volume and cortical thickness showed <6% difference between the 2 sequences. In the semiquantitative visual comparison, the differences between the 2 radiologists' scores were not clinically or statistically significant. CONCLUSIONS Brain volumes estimated using ultrafast Wave-MPRAGE show low intraindividual variability and are comparable with those estimated using standard MPRAGE in patients undergoing clinical evaluation for suspected neurodegenerative disease.
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Affiliation(s)
- M G F Longo
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.)
| | - J Conklin
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.).,Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts
| | - S F Cauley
- Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts
| | - K Setsompop
- Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
| | - Q Tian
- Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts
| | - D Polak
- Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Department of Physics and Astronomy (D.P.), Heidelberg University, Heidelberg, Germany.,Siemens (D.P., D.S., W.L.), Erlangen, Germany
| | - M Polackal
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.)
| | | | - W Liu
- Siemens (D.P., D.S., W.L.), Erlangen, Germany
| | - R G González
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.).,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts
| | - P W Schaefer
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.).,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts
| | - J E Kirsch
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.)
| | - O Rapalino
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.)
| | - S Y Huang
- From the Departments of Radiology (M.G.F.L., J.C., M.P., R.G.G., P.W.S., J.E.K., O.R., S.Y.H.).,Radiology, Athinoula A. Martinos Center for Biomedical Imaging, (J.C., S.F.C., K.S., Q.T., D.P., S.Y.H.), Massachusetts General Hospital, Boston, Massachusetts.,Harvard Medical School (J.C., S.F.C., K.S., R.G.G., P.W.S., S.Y.H.), Boston, Massachusetts.,Harvard-MIT Division of Health Sciences and Technology (K.S., S.Y.H.), Massachusetts Institute of Technology, Cambridge, Massachusetts
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24
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Aljondi R, Szoeke C, Steward C, Lui E, Alghamdi S, Desmond P. The impact of hippocampal segmentation methods on correlations with clinical data. Acta Radiol 2020; 61:953-963. [PMID: 31718255 DOI: 10.1177/0284185119885120] [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: 11/15/2022]
Abstract
BACKGROUND In vivo measurement of hippocampal volume with magnetic resonance imaging (MRI) has become an important element in neuroimaging research. However, hippocampal volumetric findings and their relationship with cardiovascular risk factors and memory performance are still controversial and inconsistent for non-demented adults. PURPOSE To compare total and regional hippocampal volumes from manual tracing and automated Freesurfer segmentation methods and their relationship with mid-life clinical data and late-life verbal episodic memory performance in older women. MATERIAL AND METHODS This study used structural MRI datasets from 161 women who were scanned in 2012 and underwent neuropsychological assessments. Of these participants, 135 women had completed baseline measures of cardiovascular risk factors in 1992. RESULTS Our results showed a significant correlation between manual tracing and automated Freesurfer output segmentations of total (r = 0.71), anterior (r = 0.65), and posterior (r = 0.38) hippocampal volumes. Mid-life Framingham Cardiovascular Risk Profile score is not associated with late-life hippocampal volumes, adjusted for intracranial volume, age, education, and apolipoprotein E gene ε4 status. Anterior hippocampal volume segmented either with manual tracing or automated Freesurfer software is sensitive to changes in mid-life high-density lipoprotein (HDL) cholesterol level, while posterior hippocampal volume is linked with verbal episodic memory performance in elderly women. CONCLUSION These findings support the use of Freesurfer automated segmentation measures for large datasets as being highly correlated with the manual tracing method. In addition, our results suggest intervention strategies that target mid-life HDL cholesterol level in women.
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Affiliation(s)
- Rowa Aljondi
- University of Jeddah, College of Applied Medical Sciences, Department of Medical Imaging and Radiation Sciences, Jeddah, Saudi Arabia
| | - Cassandra Szoeke
- Department of Medicine (Royal Melbourne Hospital), The University of Melbourne, Parkville, VIC, Australia
| | - Chris Steward
- Department of Radiology, The University of Melbourne, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Elaine Lui
- Department of Radiology, The University of Melbourne, Royal Melbourne Hospital, Parkville, VIC, Australia
| | - Salem Alghamdi
- University of Jeddah, College of Applied Medical Sciences, Department of Medical Imaging and Radiation Sciences, Jeddah, Saudi Arabia
| | - Patricia Desmond
- Department of Radiology, The University of Melbourne, Royal Melbourne Hospital, Parkville, VIC, Australia
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25
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Fung YL, Ng KET, Vogrin SJ, Meade C, Ngo M, Collins SJ, Bowden SC. Comparative Utility of Manual versus Automated Segmentation of Hippocampus and Entorhinal Cortex Volumes in a Memory Clinic Sample. J Alzheimers Dis 2020; 68:159-171. [PMID: 30814357 DOI: 10.3233/jad-181172] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Structural neuroimaging is a useful non-invasive biomarker commonly employed to evaluate the integrity of mesial temporal lobe structures that are typically compromised in Alzheimer's disease. Advances in quantitative neuroimaging have permitted the development of automated segmentation protocols (e.g., FreeSurfer) with significantly increased efficiency compared to earlier manual techniques. While these protocols have been found to be suitable for large-scale, multi-site research studies, we were interested in assessing the practical utility and reliability of automated FreeSurfer protocols compared to manual volumetry on routinely acquired clinical scans. Independent validation studies with newer automated segmentation protocols are scarce. Two FreeSurfer protocols for each of two regions of interest-the hippocampus and entorhinal cortex-were compared against manual volumetry. High reliability and agreement was found between FreeSurfer and manual hippocampal protocols, however, there was lower reliability and agreement between FreeSurfer and manual entorhinal protocols. Although based on a the relatively small sample of subjects drawn from a memory clinic (n = 27), our study findings suggest further refinements to improve measurement error and most accurately depict true regional brain volumes using automated segmentation protocols are required, especially for non-hippocampal mesial temporal structures, to achieve maximal utility for routine clinical evaluations.
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Affiliation(s)
- Yi Leng Fung
- School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Kelly E T Ng
- School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia
| | - Simon J Vogrin
- Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia
| | - Catherine Meade
- Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia
| | - Michael Ngo
- Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia
| | - Steven J Collins
- Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia.,Department of Medicine (RMH), The University of Melbourne, Parkville, Victoria, Australia
| | - Stephen C Bowden
- School of Psychological Sciences, University of Melbourne, Parkville, Victoria, Australia.,Centre for Clinical Neuroscience and Neurological Research, St Vincent's Hospital, Fitzroy, Victoria, Australia
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26
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Chapleau M, Bedetti C, Devenyi GA, Sheldon S, Rosen HJ, Miller BL, Gorno-Tempini ML, Chakravarty MM, Brambati SM. Deformation-based shape analysis of the hippocampus in the semantic variant of primary progressive aphasia and Alzheimer's disease. Neuroimage Clin 2020; 27:102305. [PMID: 32544853 PMCID: PMC7298722 DOI: 10.1016/j.nicl.2020.102305] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 05/30/2020] [Accepted: 06/01/2020] [Indexed: 01/18/2023]
Abstract
BACKGROUND Increasing evidence shows that the semantic variant of primary progressive aphasia (svPPA) is characterized by hippocampal atrophy. However, less is known about disease-related morphological hippocampal changes. The goal of the present study is to conduct a detailed characterization of the impact of svPPA on global hippocampus volume and morphology compared with control subjects and patients with Alzheimer's disease (AD). METHODS We measured hippocampal volume and deformation-based shape differences in 22 patients with svPPA compared with 99 patients with AD and 92 controls. Multiple Automatically Generated Templates Brain Segmentation Algorithm (MAGeT-Brain) was used on MRI images obtained at the diagnostic visit. RESULTS Comparable left and right hippocampal atrophy were observed in svPPA and AD. Deformation-based shape analysis showed a common pattern of morphological deformation in svPPA and AD compared with controls. More specifically, both svPPA and AD showed inward deformations in the dorsal surface of the hippocampus, from head to tail on the left side, and more limited to the anterior portion of the body in the right hemisphere. These results also pointed out that both diseases are characterized by a lateral displacement of the central part (body) of the hippocampus. DISCUSSION Our study provides critical new evidence of hippocampal morphological changes in svPPA, similar to those found in AD. These findings highlight the importance of considering morphological hippocampal changes as part of the anatomical profile of patients with svPPA.
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Affiliation(s)
- Marianne Chapleau
- Department of Psychology, University of Montreal, Quebec, Canada; Research Center of l'Institut Universitaire de Gériatrie de Montréal, Quebec, Canada
| | - Christophe Bedetti
- Department of Psychology, University of Montreal, Quebec, Canada; Research Center of l'Institut Universitaire de Gériatrie de Montréal, Quebec, Canada
| | - Gabriel A Devenyi
- Computational Brain Anatomy Lab, Cerebral Imaging Center, Douglas Mental Health University Institute, Quebec, Canada; Department of Psychiatry, McGill University, Quebec, Canada
| | - Signy Sheldon
- Department of Psychology, McGill University, Quebec, Canada
| | - Howie J Rosen
- Memory and Aging Center, University of California in San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California in San Francisco, CA, USA
| | | | - Mallar M Chakravarty
- Computational Brain Anatomy Lab, Cerebral Imaging Center, Douglas Mental Health University Institute, Quebec, Canada; Department of Psychiatry, McGill University, Quebec, Canada; Department of Biological and Biomedical Engineering, McGill University, Quebec, Canada
| | - Simona M Brambati
- Department of Psychology, University of Montreal, Quebec, Canada; Research Center of l'Institut Universitaire de Gériatrie de Montréal, Quebec, Canada.
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27
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Yaakub SN, Heckemann RA, Keller SS, McGinnity CJ, Weber B, Hammers A. On brain atlas choice and automatic segmentation methods: a comparison of MAPER & FreeSurfer using three atlas databases. Sci Rep 2020; 10:2837. [PMID: 32071355 PMCID: PMC7028906 DOI: 10.1038/s41598-020-57951-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Accepted: 11/27/2019] [Indexed: 11/09/2022] Open
Abstract
Several automatic image segmentation methods and few atlas databases exist for analysing structural T1-weighted magnetic resonance brain images. The impact of choosing a combination has not hitherto been described but may bias comparisons across studies. We evaluated two segmentation methods (MAPER and FreeSurfer), using three publicly available atlas databases (Hammers_mith, Desikan-Killiany-Tourville, and MICCAI 2012 Grand Challenge). For each combination of atlas and method, we conducted a leave-one-out cross-comparison to estimate the segmentation accuracy of FreeSurfer and MAPER. We also used each possible combination to segment two datasets of patients with known structural abnormalities (Alzheimer's disease (AD) and mesial temporal lobe epilepsy with hippocampal sclerosis (HS)) and their matched healthy controls. MAPER was better than FreeSurfer at modelling manual segmentations in the healthy control leave-one-out analyses in two of the three atlas databases, and the Hammers_mith atlas database transferred to new datasets best regardless of segmentation method. Both segmentation methods reliably identified known abnormalities in each patient group. Better separation was seen for FreeSurfer in the AD and left-HS datasets, and for MAPER in the right-HS dataset. We provide detailed quantitative comparisons for multiple anatomical regions, thus enabling researchers to make evidence-based decisions on their choice of atlas and segmentation method.
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Affiliation(s)
- Siti Nurbaya Yaakub
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Rolf A Heckemann
- MedTech West at Sahlgrenska University Hospital Gothenburg, Gothenburg, Sweden
- Department of Radiation Physics, Institute of Clinical Sciences, Gothenburg University, Gothenburg, Sweden
- Division of Brain Sciences, Imperial College London, London, United Kingdom
| | - Simon S Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Colm J McGinnity
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom
| | - Bernd Weber
- Center for Economics and Neuroscience, University of Bonn, Bonn, Germany
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Alexander Hammers
- King's College London & Guy's and St Thomas' PET Centre, School of Biomedical Engineering & Imaging Sciences, King's College London, London, United Kingdom.
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28
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Xie L, Wisse LEM, Pluta J, de Flores R, Piskin V, Manjón JV, Wang H, Das SR, Ding S, Wolk DA, Yushkevich PA. Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease. Hum Brain Mapp 2019; 40:3431-3451. [PMID: 31034738 PMCID: PMC6697377 DOI: 10.1002/hbm.24607] [Citation(s) in RCA: 63] [Impact Index Per Article: 12.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2019] [Accepted: 04/15/2019] [Indexed: 12/14/2022] Open
Abstract
Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Laura E. M. Wisse
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - John Pluta
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Robin de Flores
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Virgine Piskin
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Jose V. Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA)Universidad Politécnica de ValenciaValenciaSpain
| | | | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Song‐Lin Ding
- Allen Institute for Brain ScienceSeattleWashington
- Institute of Neuroscience, School of Basic Medical SciencesGuangzhou Medical UniversityGuangzhouPeople's Republic of China
| | - David A. Wolk
- Penn Memory CenterUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvania
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Auday ES, Pérez-Edgar KE. Limbic and prefrontal neural volume modulate social anxiety in children at temperamental risk. Depress Anxiety 2019; 36:690-700. [PMID: 31373755 PMCID: PMC6684311 DOI: 10.1002/da.22941] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 05/22/2019] [Accepted: 06/05/2019] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Clinical levels of a social anxiety disorder (SAD) often appear during childhood and rise to a peak during late adolescence. The temperament trait behavioral inhibition (BI), evident early in childhood, has been linked to increased risk for SAD. Functional and structural variations in brain regions associated with the identification of, and response to, fear may support the BI-SAD relation. Whereas relevant functional studies are emerging, the few extant structural studies have focused on adult samples with mixed findings. METHODS A moderated-mediation model was used to examine the relations between BI, SAD symptoms, and brain-volume individual differences in a sample of children at risk for anxiety (ages 9-12; N = 130, 52 BI). RESULTS Our findings indicate that at higher levels of BI, children with smaller anterior insula volumes showed stronger correlations between BI and SAD. In addition, larger ventrolateral prefrontal cortex (vlPFC) volumes were associated with fewer SAD symptoms. CONCLUSIONS These findings support previous reports linking SAD levels with variations in volume and reactivity in both limbic (insula) and prefrontal (vlPFC) regions. These findings set the foundation for further examination of networks of neural structures that influence the transition from BI to SAD across development, helping further clarify mechanisms of risk and resilience.
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Affiliation(s)
- Eran S. Auday
- The Pennsylvania State University,Geisinger Health System
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Pagnozzi AM, Fripp J, Rose SE. Quantifying deep grey matter atrophy using automated segmentation approaches: A systematic review of structural MRI studies. Neuroimage 2019; 201:116018. [PMID: 31319182 DOI: 10.1016/j.neuroimage.2019.116018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 07/01/2019] [Accepted: 07/12/2019] [Indexed: 12/13/2022] Open
Abstract
The deep grey matter (DGM) nuclei of the brain play a crucial role in learning, behaviour, cognition, movement and memory. Although automated segmentation strategies can provide insight into the impact of multiple neurological conditions affecting these structures, such as Multiple Sclerosis (MS), Huntington's disease (HD), Alzheimer's disease (AD), Parkinson's disease (PD) and Cerebral Palsy (CP), there are a number of technical challenges limiting an accurate automated segmentation of the DGM. Namely, the insufficient contrast of T1 sequences to completely identify the boundaries of these structures, as well as the presence of iso-intense white matter lesions or extensive tissue loss caused by brain injury. Therefore in this systematic review, 269 eligible studies were analysed and compared to determine the optimal approaches for addressing these technical challenges. The automated approaches used among the reviewed studies fall into three broad categories, atlas-based approaches focusing on the accurate alignment of atlas priors, algorithmic approaches which utilise intensity information to a greater extent, and learning-based approaches that require an annotated training set. Studies that utilise freely available software packages such as FIRST, FreeSurfer and LesionTOADS were also eligible, and their performance compared. Overall, deep learning approaches achieved the best overall performance, however these strategies are currently hampered by the lack of large-scale annotated data. Improving model generalisability to new datasets could be achieved in future studies with data augmentation and transfer learning. Multi-atlas approaches provided the second-best performance overall, and may be utilised to construct a "silver standard" annotated training set for deep learning. To address the technical challenges, providing robustness to injury can be improved by using multiple channels, highly elastic diffeomorphic transformations such as LDDMM, and by following atlas-based approaches with an intensity driven refinement of the segmentation, which has been done with the Expectation Maximisation (EM) and level sets methods. Accounting for potential lesions should be achieved with a separate lesion segmentation approach, as in LesionTOADS. Finally, to address the issue of limited contrast, R2*, T2* and QSM sequences could be used to better highlight the DGM due to its higher iron content. Future studies could look to additionally acquire these sequences by retaining the phase information from standard structural scans, or alternatively acquiring these sequences for only a training set, allowing models to learn the "improved" segmentation from T1-sequences alone.
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Affiliation(s)
- Alex M Pagnozzi
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia.
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
| | - Stephen E Rose
- CSIRO Health and Biosecurity, The Australian e-Health Research Centre, Brisbane, Australia
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Abstract
OBJECTIVES With an increasing aging population, it is important to understand biological markers of aging. Subcortical volume is known to differ with age; additionally considering shape-related characteristics may provide a better index of age-related differences. Fractal dimensionality is more sensitive to age-related differences, but is borne out of mathematical principles, rather than neurobiological relevance. We considered four distinct measures of shape and how they relate to aging and fractal dimensionality: surface-to-volume ratio, sphericity, long-axis curvature, and surface texture. METHODS Structural MRIs from a combined sample of over 600 healthy adults were used to measure age-related differences in the structure of the thalamus, putamen, caudate, and hippocampus. For each, volume and fractal dimensionality were calculated, as well as four distinct shape measures. These measures were examined for their utility in explaining age-related variability in brain structure. RESULTS The four shape measures were able to account for 80%-90% of the variance in fractal dimensionality. Of the distinct shape measures, surface-to-volume ratio was the most sensitive biomarker. CONCLUSION Though volume is often used to characterize inter-individual differences in subcortical structures, our results demonstrate that additional measures can be useful complements. Our results indicate that shape characteristics are useful biological markers of aging.
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Affiliation(s)
- Christopher R Madan
- a School of Psychology , University of Nottingham , Nottingham , UK.,b Department of Psychology , Boston College , Chestnut Hill , MA , USA
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Bartos A, Gregus D, Ibrahim I, Tintěra J. Brain volumes and their ratios in Alzheimer´s disease on magnetic resonance imaging segmented using Freesurfer 6.0. Psychiatry Res Neuroimaging 2019; 287:70-74. [PMID: 31003044 DOI: 10.1016/j.pscychresns.2019.01.014] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 12/21/2018] [Accepted: 01/21/2019] [Indexed: 11/17/2022]
Abstract
Ratios between opposing volumes from brain magnetic resonance imaging (MRI) can provide additional information to volumes in Alzheimer's disease (AD). Brain three-dimensional MPRAGE MRI at 3T were segmented into 44 regions using FreeSurfer v6 in 75 participants. The region's size in absolute volumes and relative proportions to the whole brain volume were compared between 39 AD patients and 36 age-, education- and sex-matched normal controls (NC). Volumes of the most atrophied parts were related to the opposing volumes of the most enlarged parts as ratios. The most atrophic structures in AD were both hippocampi. By contrast, the greatest enlargements in AD were inferior parts of both lateral ventricles. The best ratio for each side was the hippocampo-horn proportion calculated as ratio: the hippocampus / (the hippocampus + inferior lateral ventricle). Its optimal cut-off of 74% yielded sensitivity of 74% and specificity of 78% on the left and sensitivity of 74% and specificity of 78% on the right. The hippocampo-horn proportion is another measure to evaluate the degree of hippocampal atrophy on brain MRI in percentages. It has a potential to be simplified into a comparison of two-dimensional corresponding areas or a visual assessment.
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Affiliation(s)
- Ales Bartos
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Charles University, Third Faculty of Medicine, University Hospital Královské Vinohrady, Department of Neurology, AD Center, Šrobárova 50, 100 34 Prague 10, Czechia.
| | - David Gregus
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Charles University, Third Faculty of Medicine, University Hospital Královské Vinohrady, Department of Neurology, AD Center, Šrobárova 50, 100 34 Prague 10, Czechia
| | | | - Jaroslav Tintěra
- National Institute of Mental Health, Topolová 748, Klecany 250 67, Czechia; Institute of Clinical and Experimental Medicine, Czechia
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Bocchetta M, Iglesias JE, Russell LL, Greaves CV, Marshall CR, Scelsi MA, Cash DM, Ourselin S, Warren JD, Rohrer JD. Segmentation of medial temporal subregions reveals early right-sided involvement in semantic variant PPA. ALZHEIMERS RESEARCH & THERAPY 2019; 11:41. [PMID: 31077248 PMCID: PMC6511178 DOI: 10.1186/s13195-019-0489-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 04/02/2019] [Indexed: 12/03/2022]
Abstract
Background Semantic variant of primary progressive aphasia (svPPA) is a subtype of frontotemporal dementia characterized by asymmetric temporal atrophy. Methods We investigated the pattern of medial temporal lobe atrophy in 24 svPPA patients compared to 72 controls using novel approaches to segment the hippocampal and amygdalar subregions on MRIs. Based on semantic knowledge scores, we split the svPPA group into 3 subgroups of early, middle and late disease stage. Results Early stage: all left amygdalar and hippocampal subregions (except the tail) were affected in svPPA (21–35% smaller than controls), together with the following amygdalar nuclei in the right hemisphere: lateral, accessory basal and superficial (15–23%). On the right, only the temporal pole was affected among the cortical regions. Middle stage: the left hippocampal tail became affected (28%), together with the other amygdalar nuclei (22–26%), and CA4 (15%) on the right, with orbitofrontal cortex and subcortical structures involvement on the left, and more posterior temporal lobe on the right. Late stage: the remaining right hippocampal regions (except the tail) (19–24%) became affected, with more posterior left cortical and right extra-temporal anterior cortical involvement. Conclusions With advanced subregions segmentation, it is possible to detect early involvement of the right medial temporal lobe in svPPA that is not detectable by measuring the amygdala or hippocampus as a whole. Electronic supplementary material The online version of this article (10.1186/s13195-019-0489-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Caroline V Greaves
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Charles R Marshall
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK.,Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK.
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Bartel F, Vrenken H, van Herk M, de Ruiter M, Belderbos J, Hulshof J, de Munck JC. FAst Segmentation Through SURface Fairing (FASTSURF): A novel semi-automatic hippocampus segmentation method. PLoS One 2019; 14:e0210641. [PMID: 30657776 PMCID: PMC6338359 DOI: 10.1371/journal.pone.0210641] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 12/26/2018] [Indexed: 11/18/2022] Open
Abstract
Objective The objective is to present a proof-of-concept of a semi-automatic method to reduce hippocampus segmentation time on magnetic resonance images (MRI). Materials and methods FAst Segmentation Through SURface Fairing (FASTSURF) is based on a surface fairing technique which reconstructs the hippocampus from sparse delineations. To validate FASTSURF, simulations were performed in which sparse delineations extracted from full manual segmentations served as input. On three different datasets with different diagnostic groups, FASTSURF hippocampi were compared to the original segmentations using Jaccard overlap indices and percentage volume differences (PVD). In one data set for which back-to-back scans were available, unbiased estimates of overlap and PVD were obtained. Using longitudinal scans, we compared hippocampal atrophy rates measured by manual, FASTSURF and two automatic segmentations (FreeSurfer and FSL-FIRST). Results With only seven input contours, FASTSURF yielded mean Jaccard indices ranging from 72(±4.3)% to 83(±2.6)% and PVDs ranging from 0.02(±2.40)% to 3.2(±3.40)% across the three datasets. Slightly poorer results were obtained for the unbiased analysis, but the performance was still considerably better than both tested automatic methods with only five contours. Conclusions FASTSURF segmentations have high accuracy and require only a fraction of the delineation effort of fully manual segmentation. Atrophy rate quantification based on completely manual segmentation is well reproduced by FASTSURF. Therefore, FASTSURF is a promising tool to be implemented in clinical workflow, provided a future prospective validation confirms our findings.
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Affiliation(s)
- Fabian Bartel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
- * E-mail:
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Marcel van Herk
- Manchester Cancer Research Centre, Division of Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Sciences Centre, Manchester, United Kingdom
| | - Michiel de Ruiter
- Division of Psychosocial Research and Epidemiology, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jose Belderbos
- Department of Radiotherapy, Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Joost Hulshof
- Department of Mathematics, VU University Amsterdam, Amsterdam, The Netherlands
| | - Jan C. de Munck
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
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Klasson N, Olsson E, Eckerström C, Malmgren H, Wallin A. Estimated intracranial volume from FreeSurfer is biased by total brain volume. Eur Radiol Exp 2018. [PMCID: PMC6143491 DOI: 10.1186/s41747-018-0055-4] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Background Estimated intracranial volume (eTIV) from FreeSurfer is not segmentation-based but calculated from the alignment of the input magnetic resonance (MR) images to the MNI305 brain atlas, an approach that could lead to a bias by total brain volume. If eTIV is unbiased, variance beyond that explained by intracranial volume should be random. Our null hypothesis was that no correlation would remain between eTIV and total brain volume when controlling for intracranial volume. Methods eTIV and total brain volume for 62 participants were calculated on 1.5-T, T1-weighted MR images using FreeSurfer (version 6.0.0). Manual delineations of the intracranial volume were also made for the same images. To evaluate the null hypothesis, the partial correlation between eTIV and total brain volume was calculated when controlling for intracranial volume. Results The partial correlation between eTIV and total brain volume when controlling for intracranial volume was 0.355 (p = 0.026). The null hypothesis was rejected. Conclusion eTIV from FreeSurfer is biased by total brain volume. Electronic supplementary material The online version of this article (10.1186/s41747-018-0055-4) contains supplementary material, which is available to authorized users.
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Bensassi I, Lopez-Castroman J, Maller JJ, Meslin C, Wyart M, Ritchie K, Courtet P, Artero S, Calati R. Smaller hippocampal volume in current but not in past depression in comparison to healthy controls: Minor evidence from an older adults sample. J Psychiatr Res 2018; 102:159-167. [PMID: 29665490 DOI: 10.1016/j.jpsychires.2018.04.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Revised: 04/05/2018] [Accepted: 04/06/2018] [Indexed: 11/25/2022]
Abstract
BACKGROUND Structural neuroimaging studies revealed a consistent pattern of volumetric reductions in both hippocampus (HC) and anterior cingulate cortex (ACC) of individuals with major depressive episode(s) (MDE). This study investigated HC and ACC volume differences in currently depressed individuals (n = 150), individuals with a past lifetime MDE history (n = 79) and healthy controls (n = 287). METHODS Non-demented individuals were recruited from a cohort of community-dwelling older adults (ESPRIT study). T1-weighted magnetic resonance images and FreeSurfer Software (automated method) were used. Concerning HC, a manual method of measurement dividing HC into head, body, and tail was also used. General Linear Model was applied adjusting for covariates. RESULTS Current depression was associated with lower left posterior HC volume, using manual measurement, in comparison to healthy status. However, when we slightly changed sub-group inclusion criteria, results did not survive to correction for multiple comparisons. CONCLUSIONS The finding of lower left posterior HC volume in currently depressed individuals but not in those with a past MDE compared to healthy controls could be related to brain neuroplasticity. Additionally, our results may suggest manual measures to be more sensitive than automated methods.
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Affiliation(s)
- Ismaïl Bensassi
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France; Department of Adult Psychiatry, CHRU Nimes, Nimes, France
| | - Jorge Lopez-Castroman
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France; Department of Adult Psychiatry, CHRU Nimes, Nimes, France
| | - Jerome J Maller
- Monash Alfred Psychiatry Research Centre, The Alfred & Monash University Central Clinical School, Melbourne, Victoria, Australia; General Electric Healthcare, Victoria, Australia
| | - Chantal Meslin
- Centre for Mental Health Research, Australian National University, Canberra, Australia
| | - Marilyn Wyart
- Department of Adult Psychiatry, CHRU Nimes, Nimes, France
| | - Karen Ritchie
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France; Centre for Clinical Brain Sciences, Faculty of Medicine, University of Edinburgh, United Kingdom
| | - Philippe Courtet
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France; Department of Psychiatric Emergency & Acute Care, Lapeyronie Hospital, CHU Montpellier, Montpellier, France; FondaMental Foundation, Créteil, France
| | - Sylvaine Artero
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France
| | - Raffaella Calati
- INSERM, University of Montpellier, Neuropsychiatry: Epidemiological and Clinical Research, Montpellier, France; FondaMental Foundation, Créteil, France.
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Edsbagge M, Andreasson U, Ambarki K, Wikkelsø C, Eklund A, Blennow K, Zetterberg H, Tullberg M. Alzheimer's Disease-Associated Cerebrospinal Fluid (CSF) Biomarkers do not Correlate with CSF Volumes or CSF Production Rate. J Alzheimers Dis 2018; 58:821-828. [PMID: 28505972 DOI: 10.3233/jad-161257] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Neuropathologically, Alzheimer's disease (AD) is characterized by accumulation of a 42 amino acid peptide called amyloid-β (Aβ42) in extracellular senile plaques together with intraneuronal inclusions of hyperphosphorylated tau protein in neurofibrillary tangles and neuronal degeneration. These changes are reflected in the cerebrospinal fluid (CSF), the volumes and production rates of which vary considerably between individuals, by reduced concentration of Aβ42, increased concentration of phosphorylated tau (P-tau) protein, and increased concentration of total tau (T-tau) protein, respectively. OBJECTIVE To examine the outstanding question if CSF concentrations of AD associated biomarkers are influenced by variations in CSF volumes, CSF production rate, and intracranial pressure in healthy individuals. METHODS CSF concentrations of Aβ42, P-tau, and T-tau, as well as a number of other AD-related CSF biomarkers were analyzed together with intracranial subarachnoid, ventricular, and spinal CSF volumes, as assessed by magnetic resonance imaging volumetric measurements, and CSF production rate in 19 cognitively normal healthy subjects (mean age 70.6, SD 3.6 years). RESULTS Negative correlations were seen between the concentrations of three CSF biomarkers (albumin ratio, Aβ38, and Aβ40), and ventricular CSF volume, but apart from this finding, no significant correlations were observed. CONCLUSION These results speak against inter-individual variations in CSF volume and production rate as important confounds in the AD biomarker research field.
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Affiliation(s)
- Mikael Edsbagge
- Department of Clinical Neuroscience, Hydrocephalus Research Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, Clinical Neurochemistry Laboratory,Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Khalid Ambarki
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Carsten Wikkelsø
- Department of Clinical Neuroscience, Hydrocephalus Research Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders Eklund
- Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Clinical Neurochemistry Laboratory,Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Clinical Neurochemistry Laboratory,Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,UCL Institute of Neurology, Queen Square, London, UK
| | - Mats Tullberg
- Department of Clinical Neuroscience, Hydrocephalus Research Unit, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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Malpas CB, Saling MM, Velakoulis D, Desmond P, Hicks RJ, Zetterberg H, Blennow K, O’Brien TJ. Cerebrospinal Fluid Biomarkers are Differentially Related to Structural and Functional Changes in Dementia of the Alzheimer’s Type. J Alzheimers Dis 2018; 62:417-427. [DOI: 10.3233/jad-170250] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Charles B. Malpas
- Department of Medicine, Royal Melbourne Hospital, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC, Australia
| | - Michael M. Saling
- Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia
| | | | - Patricia Desmond
- Department of Radiology, University of Melbourne, VIC, Australia
| | - Rodney J. Hicks
- Department of Radiology, University of Melbourne, VIC, Australia
- Centre for Molecular Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Terence J. O’Brien
- Department of Medicine, Royal Melbourne Hospital, VIC, Australia
- Departments of Neuroscience and Neurology, The Central Clinical School and The Alfred Hospital, Monash University, Melbourne, VIC, Australia
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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: 32] [Impact Index Per Article: 4.6] [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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Madan CR, Kensinger EA. Test-retest reliability of brain morphology estimates. Brain Inform 2017; 4:107-121. [PMID: 28054317 PMCID: PMC5413592 DOI: 10.1007/s40708-016-0060-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Accepted: 12/26/2016] [Indexed: 12/17/2022] Open
Abstract
Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.
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Affiliation(s)
- Christopher R Madan
- Department of Psychology, Boston College, McGuinn 300, 140 Commonwealth Ave., Chestnut Hill, MA, 02467, USA.
| | - Elizabeth A Kensinger
- Department of Psychology, Boston College, McGuinn 300, 140 Commonwealth Ave., Chestnut Hill, MA, 02467, USA
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Comparison of accuracy between FSL's FIRST and Freesurfer for caudate nucleus and putamen segmentation. Sci Rep 2017; 7:2418. [PMID: 28546533 PMCID: PMC5445091 DOI: 10.1038/s41598-017-02584-5] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 04/12/2017] [Indexed: 11/08/2022] Open
Abstract
Although several methods have been developed to automatically delineate subcortical gray matter structures from MR images, the accuracy of these algorithms has not been comprehensively examined. Most of earlier studies focused primarily on the hippocampus. Here, we assessed the accuracy of two widely used non-commercial programs (FSL-FIRST and Freesurfer) for segmenting the caudate and putamen. T1-weighted 1 mm3 isotropic resolution MR images were acquired for thirty healthy subjects (15 females). Caudate nucleus and putamen were segmented manually by two independent observers and automatically by FIRST and Freesurfer (v4.5 and v5.3). Utilizing manual labels as reference standard the following measures were studied: Dice coefficient (D), percentage volume difference (PVD), absolute volume difference as well as intraclass correlation coefficient (ICC) for consistency and absolute agreement. For putamen segmentation, FIRST achieved higher D, lower PVD and higher ICC for absolute agreement with manual tracing than either version of Freesurfer. Freesurfer overestimated the putamen, while FIRST was not statistically different from manual tracing. The ICC for consistency with manual tracing was similar between the two methods. For caudate segmentation, FIRST and Freesurfer performed more similarly. In conclusion, Freesurfer and FIRST are not equivalent when comparing to manual tracing. FIRST was superior for putaminal segmentation.
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Bartel F, Vrenken H, Bijma F, Barkhof F, van Herk M, de Munck JC. Regional analysis of volumes and reproducibilities of automatic and manual hippocampal segmentations. PLoS One 2017; 12:e0166785. [PMID: 28182655 PMCID: PMC5300281 DOI: 10.1371/journal.pone.0166785] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Accepted: 11/03/2016] [Indexed: 01/08/2023] Open
Abstract
PURPOSE Precise and reproducible hippocampus outlining is important to quantify hippocampal atrophy caused by neurodegenerative diseases and to spare the hippocampus in whole brain radiation therapy when performing prophylactic cranial irradiation or treating brain metastases. This study aimed to quantify systematic differences between methods by comparing regional volume and outline reproducibility of manual, FSL-FIRST and FreeSurfer hippocampus segmentations. MATERIALS AND METHODS This study used a dataset from ADNI (Alzheimer's Disease Neuroimaging Initiative), including 20 healthy controls, 40 patients with mild cognitive impairment (MCI), and 20 patients with Alzheimer's disease (AD). For each subject back-to-back (BTB) T1-weighted 3D MPRAGE images were acquired at time-point baseline (BL) and 12 months later (M12). Hippocampi segmentations of all methods were converted into triangulated meshes, regional volumes were extracted and regional Jaccard indices were computed between the hippocampi meshes of paired BTB scans to evaluate reproducibility. Regional volumes and Jaccard indices were modelled as a function of group (G), method (M), hemisphere (H), time-point (T), region (R) and interactions. RESULTS For the volume data the model selection procedure yielded the following significant main effects G, M, H, T and R and interaction effects G-R and M-R. The same model was found for the BTB scans. For all methods volumes reduces with the severity of disease. Significant fixed effects for the regional Jaccard index data were M, R and the interaction M-R. For all methods the middle region was most reproducible, independent of diagnostic group. FSL-FIRST was most and FreeSurfer least reproducible. DISCUSSION/CONCLUSION A novel method to perform detailed analysis of subtle differences in hippocampus segmentation is proposed. The method showed that hippocampal segmentation reproducibility was best for FSL-FIRST and worst for Freesurfer. We also found systematic regional differences in hippocampal segmentation between different methods reinforcing the need of adopting harmonized protocols.
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Affiliation(s)
- Fabian Bartel
- Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
| | - Hugo Vrenken
- Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
- Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
| | - Fetsje Bijma
- Department of Mathematics, VU University Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology, VU University Medical Center, Amsterdam, The Netherlands
- Image Analysis Center, VU University Medical Center, Amsterdam, The Netherlands
| | - Marcel van Herk
- Department of Radiotherapy Physics, University of Manchester, Manchester, United Kingdom
| | - Jan C. de Munck
- Department of Physics and Medical Technology, VU University Medical Center, Amsterdam, The Netherlands
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43
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Age-related differences in the structural complexity of subcortical and ventricular structures. Neurobiol Aging 2016; 50:87-95. [PMID: 27939959 DOI: 10.1016/j.neurobiolaging.2016.10.023] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2016] [Revised: 10/19/2016] [Accepted: 10/20/2016] [Indexed: 02/05/2023]
Abstract
It has been well established that the volume of several subcortical structures decreases in relation to age. Different metrics of cortical structure (e.g., volume, thickness, surface area, and gyrification) have been shown to index distinct characteristics of interindividual differences; thus, it is important to consider the relation of age to multiple structural measures. Here, we compare age-related differences in subcortical and ventricular volume to those differences revealed with a measure of structural complexity, quantified as fractal dimensionality. Across 3 large data sets, totaling nearly 900 individuals across the adult lifespan (aged 18-94 years), we found greater age-related differences in complexity than volume for the subcortical structures, particularly in the caudate and thalamus. The structural complexity of ventricular structures was not more strongly related to age than volume. These results demonstrate that considering shape-related characteristics improves sensitivity to detect age-related differences in subcortical structures.
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Chapleau M, Aldebert J, Montembeault M, Brambati SM. Atrophy in Alzheimer’s Disease and Semantic Dementia: An ALE Meta-Analysis of Voxel-Based Morphometry Studies. J Alzheimers Dis 2016; 54:941-955. [DOI: 10.3233/jad-160382] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- Marianne Chapleau
- Département de Psychologie, Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montréal, Québec, Canada
| | - Joséphine Aldebert
- Département de Psychologie, Université de Montréal, Montréal, Québec, Canada
| | - Maxime Montembeault
- Département de Psychologie, Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montréal, Québec, Canada
| | - Simona M. Brambati
- Département de Psychologie, Université de Montréal, Montréal, Québec, Canada
- Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, Montréal, Québec, Canada
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Lyden H, Gimbel SI, Del Piero L, Tsai AB, Sachs ME, Kaplan JT, Margolin G, Saxbe D. Associations between Family Adversity and Brain Volume in Adolescence: Manual vs. Automated Brain Segmentation Yields Different Results. Front Neurosci 2016; 10:398. [PMID: 27656121 PMCID: PMC5011142 DOI: 10.3389/fnins.2016.00398] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Accepted: 08/12/2016] [Indexed: 12/03/2022] Open
Abstract
Associations between brain structure and early adversity have been inconsistent in the literature. These inconsistencies may be partially due to methodological differences. Different methods of brain segmentation may produce different results, obscuring the relationship between early adversity and brain volume. Moreover, adolescence is a time of significant brain growth and certain brain areas have distinct rates of development, which may compromise the accuracy of automated segmentation approaches. In the current study, 23 adolescents participated in two waves of a longitudinal study. Family aggression was measured when the youths were 12 years old, and structural scans were acquired an average of 4 years later. Bilateral amygdalae and hippocampi were segmented using three different methods (manual tracing, FSL, and NeuroQuant). The segmentation estimates were compared, and linear regressions were run to assess the relationship between early family aggression exposure and all three volume segmentation estimates. Manual tracing results showed a positive relationship between family aggression and right amygdala volume, whereas FSL segmentation showed negative relationships between family aggression and both the left and right hippocampi. However, results indicate poor overlap between methods, and different associations were found between early family aggression exposure and brain volume depending on the segmentation method used.
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Affiliation(s)
- Hannah Lyden
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Sarah I Gimbel
- Department of Psychology, Brain and Creativity Institute, University of Southern California Los Angeles, CA, USA
| | - Larissa Del Piero
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - A Bryna Tsai
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Matthew E Sachs
- Department of Psychology, Brain and Creativity Institute, University of Southern California Los Angeles, CA, USA
| | - Jonas T Kaplan
- Department of Psychology, University of Southern CaliforniaLos Angeles, CA, USA; Department of Psychology, Brain and Creativity Institute, University of Southern CaliforniaLos Angeles, CA, USA
| | - Gayla Margolin
- Department of Psychology, University of Southern California Los Angeles, CA, USA
| | - Darby Saxbe
- Department of Psychology, University of Southern California Los Angeles, CA, USA
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Mühle C, Kreczi J, Rhein C, Richter-Schmidinger T, Alexopoulos P, Doerfler A, Lenz B, Kornhuber J. Additive sex-specific influence of common non-synonymous DISC1 variants on amygdala, basal ganglia, and white cortical surface area in healthy young adults. Brain Struct Funct 2016; 222:881-894. [PMID: 27369464 DOI: 10.1007/s00429-016-1253-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2014] [Accepted: 06/16/2016] [Indexed: 01/30/2023]
Abstract
The disrupted-in-schizophrenia-1 (DISC1) gene is known for its role in the development of mental disorders. It is also involved in neurodevelopment, cognition, and memory. To investigate the association between DISC1 variants and brain morphology, we analyzed the influence of the three common non-synonymous polymorphisms in DISC1 on specific brain structures in healthy young adults. The volumes of brain regions were determined in 145 subjects by magnetic resonance imaging and automated analysis using FreeSurfer. Genotyping was performed by high resolution melting of amplified products. In an additive genetic model, rs6675281 (Leu607Phe), rs3738401 (Arg264Gln), and rs821616 (Ser704Cys) significantly explained the volume variance of the amygdala (p = 0.007) and the pallidum (p = 0.004). A higher cumulative portion of minor alleles was associated with larger volumes of the amygdala (p = 0.005), the pallidum (p = 0.001), the caudate (p = 0.024), and the putamen (p = 0.007). Sex-stratified analysis revealed a strong genetic effect of rs6675281 on putamen and pallidum in females but not in males and an opposite influence of rs3738401 on the white cortical surface in females compared to males. The strongest single association was found for rs821616 and the amygdala volume in male subjects (p < 0.001). No effect was detected for the nucleus accumbens. We report-to our knowledge-for the first time a significant and sex-specific influence of common DISC1 variants on volumes of the basal ganglia, the amygdala and on the cortical surface area. Our results demonstrate that the additive model of all three polymorphisms outperforms their single analysis.
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Affiliation(s)
- Christiane Mühle
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany.
| | - Jakob Kreczi
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Cosima Rhein
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Tanja Richter-Schmidinger
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Panagiotis Alexopoulos
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany.,Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar of the Technical University Munich, Munich, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Bernd Lenz
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University Erlangen-Nürnberg, Schwabachanlage 6, 91054, Erlangen, Germany
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Cover KS, van Schijndel RA, Versteeg A, Leung KK, Mulder ER, Jong RA, Visser PJ, Redolfi A, Revillard J, Grenier B, Manset D, Damangir S, Bosco P, Vrenken H, van Dijk BW, Frisoni GB, Barkhof F. Reproducibility of hippocampal atrophy rates measured with manual, FreeSurfer, AdaBoost, FSL/FIRST and the MAPS-HBSI methods in Alzheimer's disease. Psychiatry Res Neuroimaging 2016; 252:26-35. [PMID: 27179313 DOI: 10.1016/j.pscychresns.2016.04.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Revised: 02/16/2016] [Accepted: 04/08/2016] [Indexed: 11/23/2022]
Abstract
The purpose of this study is to assess the reproducibility of hippocampal atrophy rate measurements of commonly used fully-automated algorithms in Alzheimer disease (AD). The reproducibility of hippocampal atrophy rate for FSL/FIRST, AdaBoost, FreeSurfer, MAPS independently and MAPS combined with the boundary shift integral (MAPS-HBSI) were calculated. Back-to-back (BTB) 3D T1-weighted MPRAGE MRI from the Alzheimer's Disease Neuroimaging Initiative (ADNI1) study at baseline and year one were used. Analysis on 3 groups of subjects was performed - 562 subjects at 1.5T, a 75 subject group that also had manual segmentation and 111 subjects at 3T. A simple and novel statistical test based on the binomial distribution was used that handled outlying data points robustly. Median hippocampal atrophy rates were -1.1%/year for healthy controls, -3.0%/year for mildly cognitively impaired and -5.1%/year for AD subjects. The best reproducibility was observed for MAPS-HBSI (1.3%), while the other methods tested had reproducibilities at least 50% higher at 1.5T and 3T which was statistically significant. For a clinical trial, MAPS-HBSI should require less than half the subjects of the other methods tested. All methods had good accuracy versus manual segmentation. The MAPS-HBSI method has substantially better reproducibility than the other methods considered.
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Affiliation(s)
- Keith S Cover
- VU University Medical Center, Amsterdam, Netherlands.
| | | | | | | | - Emma R Mulder
- VU University Medical Center, Amsterdam, Netherlands
| | - Remko A Jong
- VU University Medical Center, Amsterdam, Netherlands
| | | | | | | | | | | | | | - Paolo Bosco
- IRCCS San Giovanni di Dio Fatebenefratelli, Italy
| | - Hugo Vrenken
- VU University Medical Center, Amsterdam, Netherlands
| | | | - Giovanni B Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Italy; University Hospitals and University of Geneva, Switzerland
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Claassen DO, Dobolyi DG, Isaacs DA, Roman OC, Herb J, Wylie SA, Neimat JS, Donahue MJ, Hedera P, Zald DH, Landman BA, Bowman AB, Dawant BM, Rane S. Linear and Curvilinear Trajectories of Cortical Loss with Advancing Age and Disease Duration in Parkinson's Disease. Aging Dis 2016; 7:220-9. [PMID: 27330836 PMCID: PMC4898918 DOI: 10.14336/ad.2015.1110] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2015] [Accepted: 11/10/2015] [Indexed: 11/20/2022] Open
Abstract
Advancing age and disease duration both contribute to cortical thinning in Parkinson’s disease (PD), but the pathological interactions between them are poorly described. This study aims to distinguish patterns of cortical decline determined by advancing age and disease duration in PD. A convenience cohort of 177 consecutive PD patients, identified at the Vanderbilt University Movement Disorders Clinic as part of a clinical evaluation for Deep Brain Stimulation (age: M= 62.0, SD 9.3), completed a standardized clinical assessment, along with structural brain Magnetic Resonance Imaging scan. Age and gender matched controls (n=53) were obtained from the Alzheimer Disease Neuroimaging Initiative and Progressive Parkinson’s Marker Initiative (age: M= 63.4, SD 12.2). Estimated changes in cortical thickness were modeled with advancing age, disease duration, and their interaction. The best-fitting model, linear or curvilinear (2nd, or 3rd order natural spline), was defined using the minimum Akaike Information Criterion, and illustrated on a 3-dimensional brain. Three curvilinear patterns of cortical thinning were identified: early decline, late decline, and early-stable-late. In contrast to healthy controls, the best-fit model for age related changes in PD is curvilinear (early decline), particularly in frontal and precuneus regions. With advancing disease duration, a curvilinear model depicts accelerating decline in the occipital cortex. A significant interaction between advancing age and disease duration is evident in frontal, motor, and posterior parietal areas. Study results support the hypothesis that advancing age and disease duration differentially affect regional cortical thickness and display regional dependent linear and curvilinear patterns of thinning.
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Affiliation(s)
- Daniel O Claassen
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - David G Dobolyi
- 2McIntire School of Commerce, University of Virginia, Charlottesville, VA 22904, USA
| | - David A Isaacs
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - Olivia C Roman
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - Joshua Herb
- 3Department of Medicine, University of Virginia, Charlottesville, VA 22904, USA
| | - Scott A Wylie
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - Joseph S Neimat
- 4Department of Neurosurgery, Vanderbilt University, Nashville, TN 37235, USA
| | - Manus J Donahue
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA; 5Department of Radiology, Vanderbilt University, Nashville, TN 37235, USA
| | - Peter Hedera
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - David H Zald
- 6Department of Psychology, Vanderbilt University, Nashville, TN 37235, USA
| | - Bennett A Landman
- 5Department of Radiology, Vanderbilt University, Nashville, TN 37235, USA; 7Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Aaron B Bowman
- 1Department of Neurology, Vanderbilt University, Nashville, TN 37235, USA
| | - Benoit M Dawant
- 7Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Swati Rane
- 5Department of Radiology, Vanderbilt University, Nashville, TN 37235, USA
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49
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Huo Y, Plassard AJ, Carass A, Resnick SM, Pham DL, Prince JL, Landman BA. Consistent cortical reconstruction and multi-atlas brain segmentation. Neuroimage 2016; 138:197-210. [PMID: 27184203 DOI: 10.1016/j.neuroimage.2016.05.030] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 05/10/2016] [Indexed: 01/14/2023] Open
Abstract
Whole brain segmentation and cortical surface reconstruction are two essential techniques for investigating the human brain. Spatial inconsistences, which can hinder further integrated analyses of brain structure, can result due to these two tasks typically being conducted independently of each other. FreeSurfer obtains self-consistent whole brain segmentations and cortical surfaces. It starts with subcortical segmentation, then carries out cortical surface reconstruction, and ends with cortical segmentation and labeling. However, this "segmentation to surface to parcellation" strategy has shown limitations in various cohorts such as older populations with large ventricles. In this work, we propose a novel "multi-atlas segmentation to surface" method called Multi-atlas CRUISE (MaCRUISE), which achieves self-consistent whole brain segmentations and cortical surfaces by combining multi-atlas segmentation with the cortical reconstruction method CRUISE. A modification called MaCRUISE(+) is designed to perform well when white matter lesions are present. Comparing to the benchmarks CRUISE and FreeSurfer, the surface accuracy of MaCRUISE and MaCRUISE(+) is validated using two independent datasets with expertly placed cortical landmarks. A third independent dataset with expertly delineated volumetric labels is employed to compare segmentation performance. Finally, 200MR volumetric images from an older adult sample are used to assess the robustness of MaCRUISE and FreeSurfer. The advantages of MaCRUISE are: (1) MaCRUISE constructs self-consistent voxelwise segmentations and cortical surfaces, while MaCRUISE(+) is robust to white matter pathology. (2) MaCRUISE achieves more accurate whole brain segmentations than independently conducting the multi-atlas segmentation. (3) MaCRUISE is comparable in accuracy to FreeSurfer (when FreeSurfer does not exhibit global failures) while achieving greater robustness across an older adult population. MaCRUISE has been made freely available in open source.
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Affiliation(s)
- Yuankai Huo
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA.
| | | | - Aaron Carass
- Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Dzung L Pham
- Center for Neuroscience and Regenerative Medicine, Henry Jackson Foundation, Bethesda, MD, USA
| | - Jerry L Prince
- Image Analysis and Communications Laboratory, Johns Hopkins University, Baltimore, MD, USA
| | - Bennett A Landman
- Electrical Engineering, Vanderbilt University, Nashville, TN, USA; Computer Science, Vanderbilt University, Nashville, TN, USA; Institute of Imaging Science, Vanderbilt University, Nashville, TN, USA; Radiology and Radiological Sciences, Vanderbilt University, Nashville, TN, USA
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50
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Menéndez González M, Suárez-Sanmartin E, García C, Martínez-Camblor P, Westman E, Simmons A. Manual Planimetry of the Medial Temporal Lobe Versus Automated Volumetry of the Hippocampus in the Diagnosis of Alzheimer's Disease. Cureus 2016; 8:e544. [PMID: 27433401 PMCID: PMC4934791 DOI: 10.7759/cureus.544] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Introduction: Though a disproportionate rate of atrophy in the medial temporal lobe (MTA) represents a reliable marker of Alzheimer’s disease (AD) pathology, measurement of the MTA is not currently widely used in daily clinical practice. This is mainly because the methods available to date are sophisticated and difficult to implement in clinical practice (volumetric methods), are poorly explored (linear and planimetric methods), or lack objectivity (visual rating). Here, we aimed to compare the results of a manual planimetric measure (the yearly rate of absolute atrophy of the medial temporal lobe, 2D-yrA-MTL) with the results of an automated volumetric measure (the yearly rate of atrophy of the hippocampus, 3D-yrA-H). Methods: A series of 1.5T MRI studies on 290 subjects in the age range of 65–85 years, including patients with AD (n = 100), mild cognitive impairment (MCI) (n = 100), and matched controls (n = 90) from the AddNeuroMed study, were examined by two independent subgroups of researchers: one in charge of volumetric measures and the other in charge of planimetric measures. Results: The means of both methods were significantly different between AD and the other two diagnostic groups. In the differential diagnosis of AD against controls, 3D-yrA-H performed significantly better than 2D-yrA-MTL while differences were not statistically significant in the differential diagnosis of AD against MCI. Conclusion: Automated volumetry of the hippocampus is superior to manual planimetry of the MTL in the diagnosis of AD. Nevertheless, the 2D-yrAMTL is a simpler method that could be easily implemented in clinical practice when volumetry is not available.
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Affiliation(s)
- Manuel Menéndez González
- Neurology, Hospital Universitario Central de Asturias ; Morphology and Cellular Biology, Universidad de Oviedo ; Facultad de Ciencias de la Salud, Universidad Autónoma de Chile
| | | | - Ciara García
- Neurology, Hospital Universitario Central de Asturias
| | | | - Eric Westman
- Department of Neurobiology, Care Sciences and Society, Karolinska Institutet
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