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Gajawelli N, Paulli A, Deoni S, Paquette N, Darakjian D, Salazar C, Dean D, O'Muircheartaigh J, Nelson MD, Wang Y, Lepore N. Surface-based morphometry of the corpus callosum in young children of ages 1-5. Hum Brain Mapp 2024; 45:e26693. [PMID: 38924235 PMCID: PMC11199824 DOI: 10.1002/hbm.26693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 02/05/2024] [Accepted: 04/05/2024] [Indexed: 06/28/2024] Open
Abstract
The corpus callosum (CC) is a large white matter fiber bundle in the brain and is involved in various cognitive, sensory, and motor processes. While implicated in various developmental and psychiatric disorders, much is yet to be uncovered about the normal development of this structure, especially in young children. Additionally, while sexual dimorphism has been reported in prior literature, observations have not necessarily been consistent. In this study, we use morphometric measures including surface tensor-based morphometry (TBM) to investigate local changes in the shape of the CC in children between the ages of 12 and 60 months, in intervals of 12 months. We also analyze sex differences in each of these age groups. We observed larger significant clusters in the earlier ages between 12 v 24 m and between 48 v 60 m and localized differences in the anterior region of the body of the CC. Sex differences were most pronounced in the 12 m group. This study adds to the growing literature of work aiming to understand the developing brain and emphasizes the utility of surface TBM as a useful tool for analyzing regional differences in neuroanatomical morphometry.
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Affiliation(s)
- Niharika Gajawelli
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Athelia Paulli
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Sean Deoni
- Department of PediatricsWarren Alpert Medical School at Brown UniversityProvidenceRhode IslandUSA
- Bill & Melinda Gates FoundationSeattleWashingtonUSA
| | - Natacha Paquette
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
- Department of PsychologyCHU Sainte‐JustineMontrealQuebecCanada
| | - Danielle Darakjian
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
- College of MedicineCalifornia Northstate UniversityElk GroveCaliforniaUSA
| | - Carlos Salazar
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Douglas Dean
- Waisman Laboratory for Brain Imaging and BehaviorUniversity of Wisconsin MadisonMadisonWisconsinUSA
| | | | - Marvin D. Nelson
- Department of PediatricsUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
| | - Yalin Wang
- Department of Computer ScienceArizona State UniversityTempeArizonaUSA
| | - Natasha Lepore
- CIBORG Lab, Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
- Department of Biomedical EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of PediatricsUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of RadiologyChildren's Hospital Los AngelesLos AngelesCaliforniaUSA
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Zheng W, Liu H, Li Z, Li K, Wang Y, Hu B, Dong Q, Wang Z. Classification of Alzheimer's disease based on hippocampal multivariate morphometry statistics. CNS Neurosci Ther 2023; 29:2457-2468. [PMID: 37002795 PMCID: PMC10401169 DOI: 10.1111/cns.14189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/07/2023] [Accepted: 03/13/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive cognitive decline, and mild cognitive impairment (MCI) is associated with a high risk of developing AD. Hippocampal morphometry analysis is believed to be the most robust magnetic resonance imaging (MRI) markers for AD and MCI. Multivariate morphometry statistics (MMS), a quantitative method of surface deformations analysis, is confirmed to have strong statistical power for evaluating hippocampus. AIMS We aimed to test whether surface deformation features in hippocampus can be employed for early classification of AD, MCI, and healthy controls (HC). METHODS We first explored the differences in hippocampus surface deformation among these three groups by using MMS analysis. Additionally, the hippocampal MMS features of selective patches and support vector machine (SVM) were used for the binary classification and triple classification. RESULTS By the results, we identified significant hippocampal deformation among the three groups, especially in hippocampal CA1. In addition, the binary classification of AD/HC, MCI/HC, AD/MCI showed good performances, and area under curve (AUC) of triple-classification model achieved 0.85. Finally, positive correlations were found between the hippocampus MMS features and cognitive performances. CONCLUSIONS The study revealed significant hippocampal deformation among AD, MCI, and HC. Additionally, we confirmed that hippocampal MMS can be used as a sensitive imaging biomarker for the early diagnosis of AD at the individual level.
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Affiliation(s)
- Weimin Zheng
- Department of Radiology, Aerospace Center Hospital, Beijing, China
| | - Honghong Liu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Zhigang Li
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Kuncheng Li
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, USA
| | - Bin Hu
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Qunxi Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, China
| | - Zhiqun Wang
- Department of Radiology, Aerospace Center Hospital, Beijing, China
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Xu X, Sun C, Sun J, Shi W, Shen Y, Zhao R, Luo W, Li M, Wang G, Wu D. Spatiotemporal Atlas of the Fetal Brain Depicts Cortical Developmental Gradient. J Neurosci 2022; 42:9435-9449. [PMID: 36323525 PMCID: PMC9794379 DOI: 10.1523/jneurosci.1285-22.2022] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/17/2022] [Accepted: 10/25/2022] [Indexed: 11/12/2022] Open
Abstract
The fetal brains experience rapid and complex development in utero during the second and third trimesters. In utero MRI of the fetal brain in this period enables us to quantify normal fetal brain development in the spatiotemporal domain. In this study, we established a high-quality spatiotemporal atlas between 23 and 38 weeks gestational age (GA) from 90 healthy Chinese human fetuses of both sexes using a pairwise and groupwise registration pipeline. We quantified the fetal cortical morphology indices and characterized their spatiotemporal developmental pattern. The cortical thickness exhibited a biphasic pattern that first increased and then decreased; the curvature fitted well into the Gompertz growth model; sulcal depth increased linearly, while surface area expanded exponentially. The cortical thickness and curvature trajectories consistently pointed to a characteristic time point around GA of 31 weeks. The characteristic GA and growth rate obtained from individual cortical regions suggested a central-to-peripheral developmental gradient, with the earliest development in the parietal lobe, and we also observed a superior-to-inferior gradient within the temporal lobe. These findings may be linked to biophysical events, such as dendritic arborization and thalamocortical fibers ingrowth. The proposed atlas was also compared with an existing fetal atlas from a white/mixed population. Finally, we examined the structural asymmetry of the fetal brains and found extensive asymmetry that dynamically changed with development. The current study depicted a comprehensive profile of fetal cortical development, and the established atlas could be used as a normative reference for neurodevelopmental and diagnostic purposes, especially in the Chinese population.SIGNIFICANCE STATEMENT We generated a high-quality 4D spatiotemporal atlas of the normal fetal brain development from 23 to 38 gestational weeks in a Chinese population and characterized the spatiotemporal developmental pattern of cortical morphology. According to the cortical development trajectories, the fetal cerebral cortex development follows a central-to-peripheral developmental gradient that may be related to the underlying cellular events. The majority of cortical regions already exhibit significant asymmetry during the fetal period.
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Affiliation(s)
- Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Cong Sun
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, P. R. China
| | - Jiwei Sun
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Wen Shi
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland 21287
| | - Yao Shen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Ruoke Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Wanrong Luo
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Mingyang Li
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, 250021, P. R. China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027, P. R. China
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Lao Y, Cao M, Yang Y, Kishan AU, Yang W, Wang Y, Sheng K. Bladder surface dose modeling in prostate cancer radiotherapy: An analysis of motion-induced variations and the cumulative dose across the treatment. Med Phys 2021; 48:8024-8036. [PMID: 34734414 DOI: 10.1002/mp.15326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 09/15/2021] [Accepted: 10/21/2021] [Indexed: 01/04/2023] Open
Abstract
PURPOSE To introduce a novel surface-based dose mapping method to improve quantitative bladder dosimetric assessment in prostate cancer (PC) radiotherapy. METHODS Based on the planning and daily pre and postfraction MRIs of 12 PC patients, bladder surface models (SMs) were generated on manually delineated contours and regionally aligned via surface-based registration. Subsequently, bladder surface dose models (SDMs) were created using face-wise dose sampling. To determine the bladder intrafractional and interfractional motion and dose variation, we performed a pose analysis between pre and postfraction bladder SMs, as well as surface mapping for fractional SMs. Discrepancies between the received dose, accumulated from daily SDMs, and the planned dose were then assessed on the corresponding SDMs. Complementary to the surface dose mapping, dose surface histogram (DSH)-based comparisons were also performed. RESULTS The intrafraction pose analysis revealed a significant (p < 0.05) bladder expansion, as well as an anterior/superior drift during the treatment. The intrafraction motion substantially altered dose to mid-bladder body, but not the bladder surface areas distal to or contiguous with the target. A similar pattern of dose variations was also detected by interfraction comparisons. With surface registration to the common SM, the cumulative bladder dose significantly differs from the planned dose. The discrepancy is evident in the mid-posterior range that corresponds to a mid- to high-dose region. The received DSH significantly differs from the planned DSH after permutation correction (p = 0.0122), while the overall surface-based comparison after multiple comparison correction is nonsignificant (p = 0.0800). CONCLUSIONS We developed a novel surface-based intra and interdose mapping framework applied to a unique daily MR dataset for image-guided radiotherapy. The framework identified significant intrafraction bladder positional changes, localized the intra and interfraction variations, and quantified planned versus received dose differences on the bladder surface. The result indicates the importance of adopting the motion-integrated bladder SDM for bladder dose management.
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Affiliation(s)
- Yi Lao
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Minsong Cao
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Amar U Kishan
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
| | - Wensha Yang
- Department of Radiation Oncology, University of Southern California, Los Angeles, California, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona, USA
| | - Ke Sheng
- Department of Radiation Oncology, University of California, Los Angeles, California, USA
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5
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Giudice JS, Alshareef A, Wu T, Gancayco CA, Reynier KA, Tustison NJ, Druzgal TJ, Panzer MB. An Image Registration-Based Morphing Technique for Generating Subject-Specific Brain Finite Element Models. Ann Biomed Eng 2020; 48:2412-2424. [PMID: 32725547 DOI: 10.1007/s10439-020-02584-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Accepted: 07/22/2020] [Indexed: 01/10/2023]
Abstract
Finite element (FE) models of the brain are crucial for investigating the mechanisms of traumatic brain injury (TBI). However, FE brain models are often limited to a single neuroanatomy because the manual development of subject-specific models is time consuming. The objective of this study was to develop a pipeline to automatically generate subject-specific FE brain models using previously developed nonlinear image registration techniques, preserving both external and internal neuroanatomical characteristics. To verify the morphing-induced mesh distortions did not influence the brain deformation response, strain distributions predicted using the morphed model were compared to those from manually created voxel models of the same subject. Morphed and voxel models were generated for 44 subjects ranging in age, and simulated using head kinematics from a football concussion case. For each subject, brain strain distributions predicted by each model type were consistent, and differences in strain prediction was less than 4% between model type. This automated technique, taking approximately 2 h to generate a subject-specific model, will facilitate interdisciplinary research between the biomechanics and neuroimaging fields and could enable future use of biomechanical models in the clinical setting as a tool for improving diagnosis.
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Affiliation(s)
- J Sebastian Giudice
- Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia, 4040 Lewis and Clark Dr., Charlottesville, VA, 229011, USA
| | - Ahmed Alshareef
- Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia, 4040 Lewis and Clark Dr., Charlottesville, VA, 229011, USA
| | - Taotao Wu
- Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia, 4040 Lewis and Clark Dr., Charlottesville, VA, 229011, USA
| | | | - Kristen A Reynier
- Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia, 4040 Lewis and Clark Dr., Charlottesville, VA, 229011, USA
| | - Nicholas J Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - T Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Matthew B Panzer
- Department of Mechanical and Aerospace Engineering, Center for Applied Biomechanics, University of Virginia, 4040 Lewis and Clark Dr., Charlottesville, VA, 229011, USA. .,Brain Injury and Sports Concussion Center, University of Virginia, Charlottesville, VA, USA.
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6
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Dong Q, Zhang W, Stonnington CM, Wu J, Gutman BA, Chen K, Su Y, Baxter LC, Thompson PM, Reiman EM, Caselli RJ, Wang Y. Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline. NEUROIMAGE-CLINICAL 2020; 27:102338. [PMID: 32683323 PMCID: PMC7371915 DOI: 10.1016/j.nicl.2020.102338] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 06/15/2020] [Accepted: 07/02/2020] [Indexed: 12/31/2022]
Abstract
A completely automated surface-based ventricular morphometry system. Generate a whole connected 3D ventricular shape model. Test-retest the system in two independent CU subject cohorts. Subregional ventricular abnormalities prior to clinically memory decline.
Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage.
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Affiliation(s)
- Qunxi Dong
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Wen Zhang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | | | - Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Boris A Gutman
- Armour College of Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Leslie C Baxter
- Human Brain Imaging Laboratory, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Paul M Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
| | | | | | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
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Popov M, Molsberry SA, Lecci F, Junker B, Kingsley LA, Levine A, Martin E, Miller E, Munro CA, Ragin A, Seaberg E, Sacktor N, Becker JT. Brain structural correlates of trajectories to cognitive impairment in men with and without HIV disease. Brain Imaging Behav 2020; 14:821-829. [PMID: 30623289 PMCID: PMC6616021 DOI: 10.1007/s11682-018-0026-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
There are distinct trajectories to cognitive impairment among participants in the Multicenter AIDS Cohort Study (MACS). Here we analyzed the relationship between regional brain volumes and the individual trajectories to impairment in a subsample (n = 302) of the cohort. 302 (167 HIV-infected; mean age = 55.7 yrs.; mean education: 16.2 yrs.) of the men enrolled in the MACS MRI study contributed data to this analysis. We used voxel-based morphometry (VBM) to segment the brain images to analyze gray and white matter volume at the voxel-level. A Mixed Membership Trajectory Model had previously identified three distinct profiles, and each study participant had a membership weight for each of these three trajectories. We estimated VBM model parameters for 100 imputations, manually performed the post-hoc contrasts, and pooled the results. We examined the associations between brain volume at the voxel level and the MMTM membership weights for two profiles: one considered "unhealthy" and the other considered "Premature aging." The unhealthy profile was linked to the volume of the posterior cingulate gyrus/precuneus, the inferior frontal cortex, and the insula, whereas the premature aging profile was independently associated with the integrity of a portion of the precuneus. Trajectories to cognitive impairment are the result, in part, of atrophy in cortical regions linked to normal and pathological aging. These data suggest the possibility of predicting cognitive morbidity based on patterns of CNS atrophy.
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Affiliation(s)
- Mikhail Popov
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA
- Wikimedia Foundation, San Francisco, CA, USA
| | - Samantha A Molsberry
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA
- Population Health Sciences, Harvard University, Cambridge, MA, USA
| | - Fabrizio Lecci
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA
- Uber, New York, NY, USA
| | - Brian Junker
- Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lawrence A Kingsley
- Department of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew Levine
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, USA
| | - Eileen Martin
- Department of Psychiatry, Rush Medical School, Chicago, IL, USA
| | - Eric Miller
- Department of Psychiatry, University of California Los Angeles, Los Angeles, CA, USA
| | - Cynthia A Munro
- Department of Psychiatry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ann Ragin
- Department of Radiology, Northwestern University, Evanston, IL, USA
| | - Eric Seaberg
- Department of Epidemiology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ned Sacktor
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - James T Becker
- Department of Psychiatry, University of Pittsburgh, Suite 830, 3501 Forbes Avenue, Pittsburgh, PA, 15213, USA.
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.
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Yao Z, Fu Y, Wu J, Zhang W, Yu Y, Zhang Z, Wu X, Wang Y, Hu B. Morphological changes in subregions of hippocampus and amygdala in major depressive disorder patients. Brain Imaging Behav 2020; 14:653-667. [PMID: 30519998 PMCID: PMC6551316 DOI: 10.1007/s11682-018-0003-1] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Despite many neuroimaging studies in the past years, the neuroanatomical substrates of major depressive disorder (MDD) subcortical structures are still not well understood. Since hippocampus and amygdala are the two vital subcortical structures that most susceptible to MDD, finding the evidence of morphological changes in their subregions may bring some new insights for MDD research. Combining structural magnetic resonance imaging (MRI) with novel morphometry analysis methods, we recruited 25 MDD patients and 28 healthy controls (HC), and investigated their volume and morphological differences in hippocampus and amygdala. Relative to volumetric method, our methods detected more significant global morphological atrophies (p<0.05). More precisely, subiculum and cornu ammonis (CA) 1 subregions of bilateral hippocampus, lateral (LA) and basolateral ventromedial (BLVM) of left amygdala and LA, BLVM, central (CE), amygdalostriatal transition area (ASTR), anterior cortical (ACO) and anterior amygdaloid area (AAA) of right amygdala were demonstrated prone to atrophy. Correlation analyses between each subject's surface eigenvalues and Hamilton Depression Scale (HAMD) were then performed. Correlation results showed that atrophy areas in hippocampus and amygdala have slight tendencies of expanding into other subregions with the development of MDD. Finally, we performed group morphometric analysis and drew the atrophy and expansion areas between MDD-Medicated group (only 19 medicated subjects in MDD group were included) and HC group, found some preliminary evidence about subregional morphological resilience of hippocampus and amygdala. These findings revealed new pathophysiologic patterns in the subregions of hippocampus and amygdala, which can help with subsequent smaller-scale MDD research.
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Affiliation(s)
- Zhijun Yao
- School of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China
| | - Yu Fu
- School of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China
| | - Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, P.O. Box 878809, Tempe, AZ, 85287, USA
| | - Wenwen Zhang
- Department of Radiology, Gansu Provincial Hospital, Lanzhou, China
| | - Yue Yu
- School of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China
| | - Zicheng Zhang
- School of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China
| | - Xia Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
- College of Information Science and Technology, Beijing Normal University, P.O. Box 100000, Beijing, China.
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, P.O. Box 878809, Tempe, AZ, 85287, USA.
| | - Bin Hu
- School of Information Science and Engineering, Lanzhou University, P.O. Box 730000, Lanzhou, China.
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9
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Dong Q, Zhang W, Wu J, Li B, Schron EH, McMahon T, Shi J, Gutman BA, Chen K, Baxter LC, Thompson PM, Reiman EM, Caselli RJ, Wang Y. Applying surface-based hippocampal morphometry to study APOE-E4 allele dose effects in cognitively unimpaired subjects. NEUROIMAGE-CLINICAL 2019; 22:101744. [PMID: 30852398 PMCID: PMC6411498 DOI: 10.1016/j.nicl.2019.101744] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/07/2018] [Revised: 02/02/2019] [Accepted: 03/02/2019] [Indexed: 11/30/2022]
Abstract
Apolipoprotein E (APOE) e4 is the major genetic risk factor for late-onset Alzheimer's disease (AD). The dose-dependent impact of this allele on hippocampal volumes has been documented, but its influence on general hippocampal morphology in cognitively unimpaired individuals is still elusive. Capitalizing on the study of a large number of cognitively unimpaired late middle aged and older adults with two, one and no APOE-e4 alleles, the current study aims to characterize the ability of our automated surface-based hippocampal morphometry algorithm to distinguish between these three levels of genetic risk for AD and demonstrate its superiority to a commonly used hippocampal volume measurement. We examined the APOE-e4 dose effect on cross-sectional hippocampal morphology analysis in a magnetic resonance imaging (MRI) database of 117 cognitively unimpaired subjects aged between 50 and 85 years (mean = 57.4, SD = 6.3), including 36 heterozygotes (e3/e4), 37 homozygotes (e4/e4) and 44 non-carriers (e3/e3). The proposed automated framework includes hippocampal surface segmentation and reconstruction, higher-order hippocampal surface correspondence computation, and hippocampal surface deformation analysis with multivariate statistics. In our experiments, the surface-based method identified APOE-e4 dose effects on the left hippocampal morphology. Compared to the widely-used hippocampal volume measure, our hippocampal morphometry statistics showed greater statistical power by distinguishing cognitively unimpaired subjects with two, one, and no APOE-e4 alleles. Our findings mirrored previous studies showing that APOE-e4 has a dose effect on the acceleration of brain structure deformities. The results indicated that the proposed surface-based hippocampal morphometry measure is a potential preclinical AD imaging biomarker for cognitively unimpaired individuals. Applied surface-based hippocampal morphometry on cognitively unimpaired subjects. Our study identified APOE-e4 dose effects on cognitively unimpaired subjects. Surface-based hippocampal morphometry outperformed the hippocampal volume measure. Surface-based hippocampal morphometry may be a potential preclinical AD biomarker.
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Affiliation(s)
- Qunxi Dong
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Wen Zhang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Bolun Li
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | | | - Travis McMahon
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Boris A Gutman
- Armour College of Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Leslie C Baxter
- Human Brain Imaging Laboratory, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Paul M Thompson
- Imaging Genetics Center, Institute for Neuroimaging and Informatics, University of Southern California, Los Angeles, CA, USA
| | | | | | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
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10
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Abstract
Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data.
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Affiliation(s)
- Erdem Varol
- Section for Biomedical Image Analysis, Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Aristeidis Sotiras
- Section for Biomedical Image Analysis, Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Christos Davatzikos
- Section for Biomedical Image Analysis, Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA, 19104, USA
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11
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Abstract
Human immunodeficiency virus (HIV) enters the brain early after infecting humans and may remain in the central nervous system despite successful antiretroviral treatment. Many neuroimaging techniques were used to study HIV+ patients with or without opportunistic infections. These techniques assessed abnormalities in brain structures (using computed tomography, structural magnetic resonance imaging (MRI), diffusion MRI) and function (using functional MRI at rest or during a task, and perfusion MRI with or without a contrast agent). In addition, single-photon emission computed tomography with various tracers (e.g., thallium-201, Tc99-HMPAO) and positron emission tomography with various agents (e.g., [18F]-dexoyglucose, [11C]-PiB, and [11C]-TSPO tracers), were applied to study opportunistic infections or HIV-associated neurocognitive disorders. Neuroimaging provides diagnoses and biomarkers to quantitate the severity of brain injury or to monitor treatment effects, and may yield insights into the pathophysiology of HIV infection. As the majority of antiretroviral-stable HIV+ patients are living longer, age-related comorbid disorders (e.g., additional neuroinflammation, cerebrovascular disorders, or other dementias) will need to be considered. Other highly prevalent conditions, such as substance use disorders, psychiatric illnesses, and the long-term effects of combined antiretroviral therapy, all may lead to additional brain injury. Neuroimaging studies could provide knowledge regarding how these comorbid conditions impact the HIV-infected brain. Lastly, specific molecular imaging agents may be needed to assess the central nervous system viral reservoir.
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Affiliation(s)
- Linda Chang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States; Department of Medicine and Department of Neurology, John A. Burns School of Medicine, University of Hawaii, Manoa, United States.
| | - Dinesh K Shukla
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
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12
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Chandran V, Reyes M, Zysset P. A novel registration-based methodology for prediction of trabecular bone fabric from clinical QCT: A comprehensive analysis. PLoS One 2017; 12:e0187874. [PMID: 29176881 PMCID: PMC5703488 DOI: 10.1371/journal.pone.0187874] [Citation(s) in RCA: 7] [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: 01/10/2017] [Accepted: 10/29/2017] [Indexed: 11/23/2022] Open
Abstract
Osteoporosis leads to hip fractures in aging populations and is diagnosed by modern medical imaging techniques such as quantitative computed tomography (QCT). Hip fracture sites involve trabecular bone, whose strength is determined by volume fraction and orientation, known as fabric. However, bone fabric cannot be reliably assessed in clinical QCT images of proximal femur. Accordingly, we propose a novel registration-based estimation of bone fabric designed to preserve tensor properties of bone fabric and to map bone fabric by a global and local decomposition of the gradient of a non-rigid image registration transformation. Furthermore, no comprehensive analysis on the critical components of this methodology has been previously conducted. Hence, the aim of this work was to identify the best registration-based strategy to assign bone fabric to the QCT image of a patient’s proximal femur. The normalized correlation coefficient and curvature-based regularization were used for image-based registration and the Frobenius norm of the stretch tensor of the local gradient was selected to quantify the distance among the proximal femora in the population. Based on this distance, closest, farthest and mean femora with a distinction of sex were chosen as alternative atlases to evaluate their influence on bone fabric prediction. Second, we analyzed different tensor mapping schemes for bone fabric prediction: identity, rotation-only, rotation and stretch tensor. Third, we investigated the use of a population average fabric atlas. A leave one out (LOO) evaluation study was performed with a dual QCT and HR-pQCT database of 36 pairs of human femora. The quality of the fabric prediction was assessed with three metrics, the tensor norm (TN) error, the degree of anisotropy (DA) error and the angular deviation of the principal tensor direction (PTD). The closest femur atlas (CTP) with a full rotation (CR) for fabric mapping delivered the best results with a TN error of 7.3 ± 0.9%, a DA error of 6.6 ± 1.3% and a PTD error of 25 ± 2°. The closest to the population mean femur atlas (MTP) using the same mapping scheme yielded only slightly higher errors than CTP for substantially less computing efforts. The population average fabric atlas yielded substantially higher errors than the MTP with the CR mapping scheme. Accounting for sex did not bring any significant improvements. The identified fabric mapping methodology will be exploited in patient-specific QCT-based finite element analysis of the proximal femur to improve the prediction of hip fracture risk.
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Affiliation(s)
- Vimal Chandran
- Institute of Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
- * E-mail:
| | - Mauricio Reyes
- Institute of Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
| | - Philippe Zysset
- Institute of Surgical Technology and Biomechanics, University of Bern, Bern, Switzerland
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13
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Vlasova R, Dirks H, Dean D, O'Muircheartaigh J, Gonzalez S, Nelson MD, Deoni S, Lepore N. Contribution to speech development of the right anterior putamen revealed with multivariate tensor-based morphometry. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2017; 2017:3085-3087. [PMID: 29060550 DOI: 10.1109/embc.2017.8037509] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
In our previous study1, we suggested that the difference between tensor-based metrics in the anterior part of the right putamen between 21 and 18 months age groups associated with speech development during this ages. Here we used a correlational analysis between verbal scores and determinant of the Jacobian matrix to confirm our hypothesis. Significant correlations in anterior part of the right putamen between verbal scores and surface metric were revealed in the 18 and 21 age groups.
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14
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Tsao S, Gajawelli N, Zhou J, Shi J, Ye J, Wang Y, Leporé N. Feature selective temporal prediction of Alzheimer's disease progression using hippocampus surface morphometry. Brain Behav 2017; 7:e00733. [PMID: 28729939 PMCID: PMC5516607 DOI: 10.1002/brb3.733] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2016] [Revised: 04/10/2017] [Accepted: 04/14/2017] [Indexed: 12/14/2022] Open
Abstract
INTRODUCTION Prediction of Alzheimer's disease (AD) progression based on baseline measures allows us to understand disease progression and has implications in decisions concerning treatment strategy. To this end, we combine a predictive multi-task machine learning method (cFSGL) with a novel MR-based multivariate morphometric surface map of the hippocampus (mTBM) to predict future cognitive scores of patients. METHODS Previous work has shown that a multi-task learning framework that performs prediction of all future time points simultaneously (cFSGL) can be used to encode both sparsity as well as temporal smoothness. The authors showed that this method is able to predict cognitive outcomes of ADNI subjects using FreeSurfer-based baseline MRI features, MMSE score demographic information and ApoE status. Whilst volumetric information may hold generalized information on brain status, we hypothesized that hippocampus specific information may be more useful in predictive modeling of AD. To this end, we applied a multivariate tensor-based parametric surface analysis method (mTBM) to extract features from the hippocampal surfaces. RESULTS We combined mTBM features with traditional surface features such as middle axis distance, the Jacobian determinant as well as 2 of the Jacobian principal eigenvalues to yield 7 normalized hippocampal surface maps of 300 points each. By combining these 7 × 300 = 2100 features together with the previous ~350 features, we illustrate how this type of sparsifying method can be applied to an entire surface map of the hippocampus that yields a feature space that is 2 orders of magnitude larger than what was previously attempted. CONCLUSIONS By combining the power of the cFSGL multi-task machine learning framework with the addition of AD sensitive mTBM feature maps of the hippocampus surface, we are able to improve the predictive performance of ADAS cognitive scores 6, 12, 24, 36 and 48 months from baseline.
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Affiliation(s)
- Sinchai Tsao
- CIBORG Children's Hospital Los Angeles and University of Southern California Los Angeles CA USA
| | - Niharika Gajawelli
- CIBORG Children's Hospital Los Angeles and University of Southern California Los Angeles CA USA
| | - Jiayu Zhou
- Department of Computer Science and Engineering Michigan State University East Lansing MI USA
| | - Jie Shi
- School of Computing, Informatics and Decision Systems Engineering Arizona State University Phoenix AZ USA
| | - Jieping Ye
- Department of Computational Medicine and Bioinformatics & Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA
| | - Yalin Wang
- School of Computing, Informatics and Decision Systems Engineering Arizona State University Phoenix AZ USA
| | - Natasha Leporé
- CIBORG Children's Hospital Los Angeles and University of Southern California Los Angeles CA USA
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15
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Kim HJ, Adluru N, Suri H, Vemuri BC, Johnson SC, Singh V. Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging. PROCEEDINGS. IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION 2017; 2017:5777-5786. [PMID: 29430166 PMCID: PMC5805155 DOI: 10.1109/cvpr.2017.612] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Statistical machine learning models that operate on manifold-valued data are being extensively studied in vision, motivated by applications in activity recognition, feature tracking and medical imaging. While non-parametric methods have been relatively well studied in the literature, efficient formulations for parametric models (which may offer benefits in small sample size regimes) have only emerged recently. So far, manifold-valued regression models (such as geodesic regression) are restricted to the analysis of cross-sectional data, i.e., the so-called "fixed effects" in statistics. But in most "longitudinal analysis" (e.g., when a participant provides multiple measurements, over time) the application of fixed effects models is problematic. In an effort to answer this need, this paper generalizes non-linear mixed effects model to the regime where the response variable is manifold-valued, i.e., f : Rd → ℳ. We derive the underlying model and estimation schemes and demonstrate the immediate benefits such a model can provide - both for group level and individual level analysis - on longitudinal brain imaging data. The direct consequence of our results is that longitudinal analysis of manifold-valued measurements (especially, the symmetric positive definite manifold) can be conducted in a computationally tractable manner.
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16
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Topographies of Cortical and Subcortical Volume Loss in HIV and Aging in the cART Era. J Acquir Immune Defic Syndr 2017; 73:374-383. [PMID: 27454251 DOI: 10.1097/qai.0000000000001111] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
OBJECTIVES Studies of HIV-associated brain atrophy often focus on a priori brain regions of interest, which can introduce bias. A data-driven, minimally biased approach was used to analyze changes in brain volumetrics associated with HIV and their relationship to aging, viral factors, combination antiretroviral therapy (cART), and gender, and smoking. DESIGN A cross-sectional study of 51 HIV-uninfected (HIV-) and 146 HIV-infected (HIV+) participants. METHODS Structural MRI of participants was analyzed using principal component analysis (PCA) to reduce dimensionality and determine topographies of volumetric changes. Neuropsychological (NP) assessment was examined using global and domain-specific scores. The effects of HIV disease factors (eg, viral load, CD4, etc.) on brain volumes and neuropsychological were investigated using penalized regression (LASSO). RESULTS Two components of interest were visualized using principal component analysis. An aging effect predominated for both components. The first component, a cortically weighted topography, accounted for a majority of variance across participants (43.5% of variance) and showed independent effects of HIV and smoking. A secondary, subcortically weighted topography (4.6%) showed HIV-status accentuated age-related volume loss. In HIV+ patients, the cortical topography correlated with global neuropsychological scores and nadir CD4, whereas subcortical volume loss was associated with recent viral load. CONCLUSIONS Cortical regions showed the most prominent volumetric changes because of aging and HIV. Within HIV+ participants, cortical volumes were associated with immune history, whereas subcortical changes correlated with current immune function. Cognitive function was primarily associated with cortical volume changes. Observed volumetric changes in chronic HIV+ patients may reflect both past infection history and current viral status.
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17
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Paquette N, Shi J, Wang Y, Lao Y, Ceschin R, Nelson MD, Panigrahy A, Lepore N. Ventricular shape and relative position abnormalities in preterm neonates. NEUROIMAGE-CLINICAL 2017. [PMID: 28649491 PMCID: PMC5470570 DOI: 10.1016/j.nicl.2017.05.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Recent neuroimaging findings have highlighted the impact of premature birth on subcortical development and morphological changes in the deep grey nuclei and ventricular system. To help characterize subcortical microstructural changes in preterm neonates, we recently implemented a multivariate tensor-based method (mTBM). This method allows to precisely measure local surface deformation of brain structures in infants. Here, we investigated ventricular abnormalities and their spatial relationships with surrounding subcortical structures in preterm neonates. We performed regional group comparisons on the surface morphometry and relative position of the lateral ventricles between 19 full-term and 17 preterm born neonates at term-equivalent age. Furthermore, a relative pose analysis was used to detect individual differences in translation, rotation, and scale of a given brain structure with respect to an average. Our mTBM results revealed broad areas of alterations on the frontal horn and body of the left ventricle, and narrower areas of differences on the temporal horn of the right ventricle. A significant shift in the rotation of the left ventricle was also found in preterm neonates. Furthermore, we located significant correlations between morphology and pose parameters of the lateral ventricles and that of the putamen and thalamus. These results show that regional abnormalities on the surface and pose of the ventricles are also associated with alterations on the putamen and thalamus. The complementarity of the information provided by the surface and pose analysis may help to identify abnormal white and grey matter growth, hinting toward a pattern of neural and cellular dysmaturation.
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Affiliation(s)
- N Paquette
- Department of Radiology, University of Southern California and Children's Hospital of Los Angeles, CA, USA
| | - J Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Y Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Y Lao
- Department of Radiology, University of Southern California and Children's Hospital of Los Angeles, CA, USA
| | - R Ceschin
- Department of Radiology, Children's Hospital of Pittsburgh UPMC, Pittsburgh, PA, USA
| | - M D Nelson
- Department of Radiology, University of Southern California and Children's Hospital of Los Angeles, CA, USA
| | - A Panigrahy
- Department of Radiology, Children's Hospital of Pittsburgh UPMC, Pittsburgh, PA, USA
| | - N Lepore
- Department of Radiology, University of Southern California and Children's Hospital of Los Angeles, CA, USA.
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18
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Complement C5aR1 Signaling Promotes Polarization and Proliferation of Embryonic Neural Progenitor Cells through PKCζ. J Neurosci 2017; 37:5395-5407. [PMID: 28455369 DOI: 10.1523/jneurosci.0525-17.2017] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2017] [Revised: 04/03/2017] [Accepted: 04/13/2017] [Indexed: 01/14/2023] Open
Abstract
The complement system, typically associated with innate immunity, is emerging as a key controller of nonimmune systems including in development, with recent studies linking complement mutations with neurodevelopmental disease. A key effector of the complement response is the activation fragment C5a, which, through its receptor C5aR1, is a potent driver of inflammation. Surprisingly, C5aR1 is also expressed during early mammalian embryogenesis; however, no clearly defined function is ascribed to C5aR1 in development. Here we demonstrate polarized expression of C5aR1 on the apical surface of mouse embryonic neural progenitor cells in vivo and on human embryonic stem cell-derived neural progenitors. We also show that signaling of endogenous C5a during mouse embryogenesis drives proliferation of neural progenitor cells within the ventricular zone and is required for normal brain histogenesis. C5aR1 signaling in neural progenitors was dependent on atypical protein kinase C ζ, a mediator of stem cell polarity, with C5aR1 inhibition reducing proliferation and symmetric division of apical neural progenitors in human and mouse models. C5aR1 signaling was shown to promote the maintenance of cell polarity, with exogenous C5a increasing the retention of polarized rosette architecture in human neural progenitors after physical or chemical disruption. Transient inhibition of C5aR1 during neurogenesis in developing mice led to behavioral abnormalities in both sexes and MRI-detected brain microstructural alterations, in studied males, demonstrating a requirement of C5aR1 signaling for appropriate brain development. This study thus identifies a functional role for C5a-C5aR1 signaling in mammalian neurogenesis and provides mechanistic insight into recently identified complement gene mutations and brain disorders.SIGNIFICANCE STATEMENT The complement system, traditionally known as a controller of innate immunity, now stands as a multifaceted signaling family with a broad range of physiological actions. These include roles in the brain, where complement activation is associated with diseases, including epilepsy and schizophrenia. This study has explored complement regulation of neurogenesis, identifying a novel relationship between the complement activation peptide C5a and the neural progenitor proliferation underpinning formation of the mammalian brain. C5a was identified as a regulator of cell polarity, with inhibition of C5a receptors during embryogenesis leading to abnormal brain development and behavioral deficits. This work demonstrates mechanisms through which dysregulation of complement causes developmental disease and highlights the potential risk of complement inhibition for therapeutic purposes in pregnancy.
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19
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Lao Y, Dion LA, Gilbert G, Bouchard MF, Rocha G, Wang Y, Leporé N, Saint-Amour D. Mapping the basal ganglia alterations in children chronically exposed to manganese. Sci Rep 2017; 7:41804. [PMID: 28155922 PMCID: PMC5290534 DOI: 10.1038/srep41804] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 12/30/2016] [Indexed: 01/24/2023] Open
Abstract
Chronic manganese (Mn) exposure is associated with neuromotor and neurocognitive deficits, but the exact mechanism of Mn neurotoxicity is still unclear. With the advent of magnetic resonance imaging (MRI), in-vivo analysis of brain structures has become possible. Among different sub-cortical structures, the basal ganglia (BG) has been investigated as a putative anatomical biomarker in MR-based studies of Mn toxicity. However, previous investigations have yielded inconsistent results in terms of regional MR signal intensity changes. These discrepancies may be due to the subtlety of brain alterations caused by Mn toxicity, coupled to analysis techniques that lack the requisite detection power. Here, based on brain MRI, we apply a 3D surface-based morphometry method on 3 bilateral basal ganglia structures in school-age children chronically exposed to Mn through drinking water to investigate the effect of Mn exposure on brain anatomy. Our method successfully pinpointed significant enlargement of many areas of the basal ganglia structures, preferentially affecting the putamen. Moreover, these areas showed significant correlations with fine motor performance, indicating a possible link between altered basal ganglia neurodevelopment and declined motor performance in high Mn exposed children.
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Affiliation(s)
- Yi Lao
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, Los Angeles CA, USA.,Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Laurie-Anne Dion
- Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada
| | - Guillaume Gilbert
- Department of radiology, Université de Montréal, Montréal, QC, Canada.,MR Clinical Science, Philips Healthcare, Montreal, Quebec, Canada
| | - Maryse F Bouchard
- Sainte-Justine Hospital Research Centre and Department of Occupational and Environmental Health, Université de Montréal, Montréal, QC, Canada
| | - Gabriel Rocha
- Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Yalin Wang
- School of Computing, Informatics, Decision Systems and Engineering, Arizona State University, Tempe, Arizona, USA
| | - Natasha Leporé
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, Los Angeles CA, USA.,Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Dave Saint-Amour
- Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada
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20
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Yadav SK, Gupta RK, Garg RK, Venkatesh V, Gupta PK, Singh AK, Hashem S, Al-Sulaiti A, Kaura D, Wang E, Marincola FM, Haris M. Altered structural brain changes and neurocognitive performance in pediatric HIV. NEUROIMAGE-CLINICAL 2017; 14:316-322. [PMID: 28224079 PMCID: PMC5304232 DOI: 10.1016/j.nicl.2017.01.032] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Revised: 01/11/2017] [Accepted: 01/29/2017] [Indexed: 11/23/2022]
Abstract
Pediatric HIV patients often suffer with neurodevelopmental delay and subsequently cognitive impairment. While tissue injury in cortical and subcortical regions in the brain of adult HIV patients has been well reported there is sparse knowledge about these changes in perinatally HIV infected pediatric patients. We analyzed cortical thickness, subcortical volume, structural connectivity, and neurocognitive functions in pediatric HIV patients and compared with those of pediatric healthy controls. With informed consent, 34 perinatally infected pediatric HIV patients and 32 age and gender matched pediatric healthy controls underwent neurocognitive assessment and brain magnetic resonance imaging (MRI) on a 3 T clinical scanner. Altered cortical thickness, subcortical volumes, and abnormal neuropsychological test scores were observed in pediatric HIV patients. The structural network connectivity analysis depicted lower connection strengths, lower clustering coefficients, and higher path length in pediatric HIV patients than healthy controls. The network betweenness and network hubs in cortico-limbic regions were distorted in pediatric HIV patients. The findings suggest that altered cortical and subcortical structures and regional brain connectivity in pediatric HIV patients may contribute to deficits in their neurocognitive functions. Further, longitudinal studies are required for better understanding of the effect of HIV pathogenesis on brain structural changes throughout the brain development process under standard ART treatment. Structural brain MRI and cognitive assessments were performed in pediatric HIV. Pediatric HIV showed altered cortical thickness and subcortical volumes. Disrupted structural connectivity was observed in pediatric HIV. Altered brain structures and connectivity contribute to deficits in neurocognition.
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Key Words
- AIDS, acquired immunodeficiency syndrome
- C, clustering coefficient
- Cortical thickness
- ELISA, enzyme-linked immunosorbent assay
- FA, flip angel
- FLAIR, fluid attenuation inversion recovery
- FOV, field of view
- FSPGR, fast spoiled gradient echo
- GAT, graph-theoretical analysis toolbox
- HIV, human immunodeficiency virus
- Human immunodeficiency virus
- L, characteristic path length
- MRI, magnetic resonance imaging
- Magnetic resonance imaging
- Neurocognitive functions
- RAKIT, revised Amsterdamse kinder intelligence
- ROIs, regions of interest
- SW, small-world index
- Structural connectivity
- Subcortical volume
- TBM, tensor based morphometry
- TE, echo time
- TR, repetition time
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Affiliation(s)
- Santosh K Yadav
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
| | - Rakesh K Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, Delhi, India
| | - Ravindra K Garg
- Department of Neurology, King George Medical University, Lucknow, India
| | - Vimala Venkatesh
- Department of Microbiology, King George Medical University, Lucknow, India
| | - Pradeep K Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, Delhi, India
| | - Alok K Singh
- Department of Neurology, King George Medical University, Lucknow, India
| | - Sheema Hashem
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
| | - Asma Al-Sulaiti
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
| | - Deepak Kaura
- Department of Radiology, Sidra Medical and Research Center, Doha, Qatar
| | - Ena Wang
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
| | - Francesco M Marincola
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
| | - Mohammad Haris
- Division of Translational Medicine, Research Branch, Sidra Medical and Research Center, Doha, Qatar
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21
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Lao Y, Nguyen B, Tsao S, Gajawelli N, Law M, Chui H, Weiner M, Wang Y, Leporé N. A T1 and DTI fused 3D corpus callosum analysis in MCI subjects with high and low cardiovascular risk profile. Neuroimage Clin 2016; 14:298-307. [PMID: 28210541 PMCID: PMC5299209 DOI: 10.1016/j.nicl.2016.12.027] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Revised: 12/13/2016] [Accepted: 12/20/2016] [Indexed: 01/08/2023]
Abstract
Understanding the extent to which vascular disease and its risk factors are associated with prodromal dementia, notably Alzheimer's disease (AD), may enhance predictive accuracy as well as guide early interventions. One promising avenue to determine this relationship consists of looking for reliable and sensitive in-vivo imaging methods capable of characterizing the subtle brain alterations before the clinical manifestations. However, little is known from the imaging perspective about how risk factors such as vascular disease influence AD progression. Here, for the first time, we apply an innovative T1 and DTI fusion analysis of 3D corpus callosum (CC) on mild cognitive impairment (MCI) populations with different levels of vascular profile, aiming to de-couple the vascular factor in the prodromal AD stage. Our new fusion method successfully increases the detection power for differentiating MCI subjects with high from low vascular risk profiles, as well as from healthy controls. MCI subjects with high and low vascular risk profiles showed differed alteration patterns in the anterior CC, which may help to elucidate the inter-wired relationship between MCI and vascular risk factors.
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Affiliation(s)
- Yi Lao
- CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA
- Department of Biomedical Engineering, University of Southern California, USA
| | - Binh Nguyen
- CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA
| | - Sinchai Tsao
- CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA
| | - Niharika Gajawelli
- CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA
- Department of Biomedical Engineering, University of Southern California, USA
| | - Meng Law
- Department of Biomedical Engineering, University of Southern California, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, USA
| | - Helena Chui
- Department of Biomedical Engineering, University of Southern California, USA
- Department of Radiology, Keck School of Medicine, University of Southern California, USA
| | - Michael Weiner
- Department of Radiology, University of California, San Francisco, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, USA
| | - Natasha Leporé
- CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, USA
- Department of Biomedical Engineering, University of Southern California, USA
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Biomechanical Analysis of Normal Brain Development during the First Year of Life Using Finite Strain Theory. Sci Rep 2016; 6:37666. [PMID: 27910866 PMCID: PMC5133553 DOI: 10.1038/srep37666] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Accepted: 10/26/2016] [Indexed: 11/15/2022] Open
Abstract
The first year of life is the most critical time period for structural and functional development of the human brain. Combining longitudinal MR imaging and finite strain theory, this study aimed to provide new insights into normal brain development through a biomechanical framework. Thirty-three normal infants were longitudinally imaged using MRI from 2 weeks to 1 year of age. Voxel-wise Jacobian determinant was estimated to elucidate volumetric changes while Lagrange strains (both normal and shear strains) were measured to reveal directional growth information every 3 months during the first year of life. Directional normal strain maps revealed that, during the first 6 months, the growth pattern of gray matter is anisotropic and spatially inhomogeneous with higher left-right stretch around the temporal lobe and interhemispheric fissure, anterior-posterior stretch in the frontal and occipital lobes, and superior-inferior stretch in right inferior occipital and right inferior temporal gyri. In contrast, anterior lateral ventricles and insula showed an isotropic stretch pattern. Volumetric and directional growth rates were linearly decreased with age for most of the cortical regions. Our results revealed anisotropic and inhomogeneous brain growth patterns of the human brain during the first year of life using longitudinal MRI and a biomechanical framework.
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23
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Chai Y, Lao Y, Li Y, Ji C, O'Neil S, Wang Y, Lepore N, Wood J. Multivariate surface-based analysis of corpus callosum in patients with sickle cell disease. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2016; 10160:101600A. [PMID: 31178616 PMCID: PMC6554202 DOI: 10.1117/12.2257399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Sickle cell disease (SCD) is a genetic hematological disease in which the hemoglobin molecule in red blood cells is abnormal. It is closely associated with many symptoms, including pain, anemia, chest syndrome and neurocognitive impairment. One of the most debilitating symptoms is elevated risk for cerebro-vascular accidents. The corpus callosum (CC), as the largest and most prominent white matter (WM) structure in the brain, can reflect the chronic cerebrovascular damage resulting from silent strokes or infarctions in asymptomatic SCD patients. While a lot of studies have reported WM alterations in this cohort, little is known about the shape deformation of the CC. Here we perform the first surface morphometry analysis of the CC in SCD patients using four different shape metrics on T1-weighted magnetic resonance images. We detect regional surface morphological differences in the CC between 11 patients and 10 healthy control subjects. Differences are located in the genu, posterior midbody and splenium, potentially casting light on the anatomical substrates underlying neuropsychological test differences between the SCD and control groups.
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Affiliation(s)
- Yaqiong Chai
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA
- Department of Radiology, University of Southern California, CA, USA
- Department of Biomedical Engineering, University of Southern California, CA, USA
| | - Yi Lao
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA
- Department of Radiology, University of Southern California, CA, USA
- Department of Biomedical Engineering, University of Southern California, CA, USA
| | - Yicen Li
- Department of Electrical Engineering, University of Southern California, CA, USA
| | - Chaoran Ji
- Department of Electrical Engineering, University of Southern California, CA, USA
| | - Sharon O'Neil
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA
- Department of Radiology, University of Southern California, CA, USA
- Department of Biomedical Engineering, University of Southern California, CA, USA
- Department of Electrical Engineering, University of Southern California, CA, USA
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
- Division of Cardiology, Children's Hospital Los Angeles, CA, USA
| | - Yalin Wang
- School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Natasha Lepore
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA
- Department of Radiology, University of Southern California, CA, USA
- Department of Biomedical Engineering, University of Southern California, CA, USA
| | - John Wood
- Division of Cardiology, Children's Hospital Los Angeles, CA, USA
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24
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Schwartzman A. Lognormal Distributions and Geometric Averages of Symmetric Positive Definite Matrices. Int Stat Rev 2016; 84:456-486. [PMID: 28082762 PMCID: PMC5222531 DOI: 10.1111/insr.12113] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Accepted: 06/29/2015] [Indexed: 11/28/2022]
Abstract
This article gives a formal definition of a lognormal family of probability distributions on the set of symmetric positive definite (SPD) matrices, seen as a matrix-variate extension of the univariate lognormal family of distributions. Two forms of this distribution are obtained as the large sample limiting distribution via the central limit theorem of two types of geometric averages of i.i.d. SPD matrices: the log-Euclidean average and the canonical geometric average. These averages correspond to two different geometries imposed on the set of SPD matrices. The limiting distributions of these averages are used to provide large-sample confidence regions and two-sample tests for the corresponding population means. The methods are illustrated on a voxelwise analysis of diffusion tensor imaging data, permitting a comparison between the various average types from the point of view of their sampling variability.
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25
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Vlasova R, Gajawelli N, Wang Y, Dirks H, Dean D, O'Muircheartaigh J, Lao Y, Yoon J, Nelson MD, Deoni S, Lepore N. Putamen Development in Children 12 to 21 Months Old. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2016; 10160. [PMID: 31178618 DOI: 10.1117/12.2257278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
We studied the developmental trajectory of the putamen in 13-21 months old children using multivariate surface tensor-based morphometry. Our results indicate surface changes between 12 and 15 months' age groups in the middle superior part the left putamen. The growth of the left putamen at earlier ages slows down after 15 months. The most important surface changes were detected in the right putamen between 18 and 21 months and were located in the anterior part of the structure. Our results demonstrate the heterochronic growth of the right and left putamen related to different functional subregions within putamen. Our results are compatible with previous studies devoted to total putamen volume changes during normal development.
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Affiliation(s)
- Roza Vlasova
- CIBORG Lab, Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Niharika Gajawelli
- CIBORG Lab, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, CA, USA
| | - Yalin Wang
- Department of Computer Science, Arizona State University, AZ, USA
| | - Holly Dirks
- Department of Biomedical Engineering, Brown University, RI, USA
| | - Douglas Dean
- Department of Biomedical Engineering, Brown University, RI, USA
| | | | - Yi Lao
- CIBORG Lab, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, CA, USA
| | - James Yoon
- CIBORG Lab, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biological Sciences, University of Southern California, CA, USA
| | - Marvin D Nelson
- Department of Radiology, University of Southern California, CA, USA.,Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Sean Deoni
- Department of Pediatric Radiology Research, Children's Hospital Colorado, CO, USA.,Department of Biomedical Engineering, Brown University, RI, USA
| | - Natasha Lepore
- CIBORG Lab, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, CA, USA.,Department of Radiology, University of Southern California, CA, USA
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26
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Influence of APOE Genotype on Hippocampal Atrophy over Time - An N=1925 Surface-Based ADNI Study. PLoS One 2016; 11:e0152901. [PMID: 27065111 PMCID: PMC4827849 DOI: 10.1371/journal.pone.0152901] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 03/21/2016] [Indexed: 11/25/2022] Open
Abstract
The apolipoprotein E (APOE) e4 genotype is a powerful risk factor for late-onset Alzheimer’s disease (AD). In the Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohort, we previously reported significant baseline structural differences in APOE e4 carriers relative to non-carriers, involving the left hippocampus more than the right—a difference more pronounced in e4 homozygotes than heterozygotes. We now examine the longitudinal effects of APOE genotype on hippocampal morphometry at 6-, 12- and 24-months, in the ADNI cohort. We employed a new automated surface registration system based on conformal geometry and tensor-based morphometry. Among different hippocampal surfaces, we computed high-order correspondences, using a novel inverse-consistent surface-based fluid registration method and multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance. At each time point, using Hotelling’s T2 test, we found significant morphological deformation in APOE e4 carriers relative to non-carriers in the full cohort as well as in the non-demented (pooled MCI and control) subjects at each follow-up interval. In the complete ADNI cohort, we found greater atrophy of the left hippocampus than the right, and this asymmetry was more pronounced in e4 homozygotes than heterozygotes. These findings, combined with our earlier investigations, demonstrate an e4 dose effect on accelerated hippocampal atrophy, and support the enrichment of prevention trial cohorts with e4 carriers.
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27
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Pai A, Sporring J, Darkner S, Dam EB, Lillholm M, Jørgensen D, Oh J, Chen G, Suhy J, Sørensen L, Nielsen M. Deformation-based atrophy computation by surface propagation and its application to Alzheimer's disease. J Med Imaging (Bellingham) 2016; 3:014005. [PMID: 27014717 DOI: 10.1117/1.jmi.3.1.014005] [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: 08/10/2015] [Accepted: 02/19/2016] [Indexed: 11/14/2022] Open
Abstract
Obtaining regional volume changes from a deformation field is more precise when using simplex counting (SC) compared with Jacobian integration (JI) due to the numerics involved in the latter. Although SC has been proposed before, numerical properties underpinning the method and a thorough evaluation of the method against JI is missing in the literature. The contributions of this paper are: (a) we propose surface propagation (SP)-a simplification to SC that significantly reduces its computational complexity; (b) we will derive the orders of approximation of SP which can also be extended to SC. In the experiments, we will begin by empirically showing that SP is indeed nearly identical to SC, and that both methods are more stable than JI in presence of moderate to large deformation noise. Since SC and SP are identical, we consider SP as a representative of both the methods for a practical evaluation against JI. In a real application on Alzheimer's disease neuroimaging initiative data, we show the following: (a) SP produces whole brain and medial temporal lobe atrophy numbers that are significantly better than JI at separating between normal controls and Alzheimer's disease patients; (b) SP produces disease group atrophy differences comparable to or better than those obtained using FreeSurfer, demonstrating the validity of the obtained clinical results. Finally, in a reproducibility study, we show that the voxel-wise application of SP yields significantly lower variance when compared to JI.
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Affiliation(s)
- Akshay Pai
- University of Copenhagen , Department of Computer Science, DIKU, Sigursgade 41, Copenhagen 2100, Denmark
| | - Jon Sporring
- University of Copenhagen , Department of Computer Science, DIKU, Sigursgade 41, Copenhagen 2100, Denmark
| | - Sune Darkner
- Biomediq A/S , Fruebjergvej 3, Copenhagen 2100, Denmark
| | - Erik B Dam
- University of Copenhagen, Department of Computer Science, DIKU, Sigursgade 41, Copenhagen 2100, Denmark; Biomediq A/S, Fruebjergvej 3, Copenhagen 2100, Denmark
| | | | - Dan Jørgensen
- Biomediq A/S , Fruebjergvej 3, Copenhagen 2100, Denmark
| | - Joonmi Oh
- Bioclinica , 7707 Gateway Boulevard, 3rd Floor Newark, California 94560, United States
| | - Gennan Chen
- Bioclinica , 7707 Gateway Boulevard, 3rd Floor Newark, California 94560, United States
| | - Joyce Suhy
- Bioclinica , 7707 Gateway Boulevard, 3rd Floor Newark, California 94560, United States
| | | | - Mads Nielsen
- University of Copenhagen, Department of Computer Science, DIKU, Sigursgade 41, Copenhagen 2100, Denmark; Biomediq A/S, Fruebjergvej 3, Copenhagen 2100, Denmark
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28
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Shi J, Collignon O, Xu L, Wang G, Kang Y, Leporé F, Lao Y, Joshi AA, Leporé N, Wang Y. Impact of Early and Late Visual Deprivation on the Structure of the Corpus Callosum: A Study Combining Thickness Profile with Surface Tensor-Based Morphometry. Neuroinformatics 2016; 13:321-336. [PMID: 25649876 DOI: 10.1007/s12021-014-9259-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Blindness represents a unique model to study how visual experience may shape the development of brain organization. Exploring how the structure of the corpus callosum (CC) reorganizes ensuing visual deprivation is of particular interest due to its important functional implication in vision (e.g., via the splenium of the CC). Moreover, comparing early versus late visually deprived individuals has the potential to unravel the existence of a sensitive period for reshaping the CC structure. Here, we develop a novel framework to capture a complete set of shape differences in the CC between congenitally blind (CB), late blind (LB) and sighted control (SC) groups. The CCs were manually segmented from T1-weighted brain MRI and modeled by 3D tetrahedral meshes. We statistically compared the combination of local area and thickness at each point between subject groups. Differences in area are found using surface tensor-based morphometry; thickness is estimated by tracing the streamlines in the volumetric harmonic field. Group differences were assessed on this combined measure using Hotelling's T(2) test. Interestingly, we observed that the total callosal volume did not differ between the groups. However, our fine-grained analysis reveals significant differences mostly localized around the splenium areas between both blind groups and the sighted group (general effects of blindness) and, importantly, specific dissimilarities between the LB and CB groups, illustrating the existence of a sensitive period for reorganization. The new multivariate statistics also gave better effect sizes for detecting morphometric differences, relative to other statistics. They may boost statistical power for CC morphometric analyses.
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Affiliation(s)
- Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | | | - Liang Xu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Gang Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
- School of Information and Electrical Engineering, Ludong University, Yantai, China
| | - Yue Kang
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Franco Leporé
- Department of Psychology, University of Montreal, Montreal, QC, Canada
| | - Yi Lao
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Anand A Joshi
- Signal and Image Processing Institute, Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA
| | - Natasha Leporé
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA
- Department of Radiology & Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
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29
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Moon SW, Dinov ID, Hobel S, Zamanyan A, Choi YC, Shi R, Thompson PM, Toga AW. Structural Brain Changes in Early-Onset Alzheimer's Disease Subjects Using the LONI Pipeline Environment. J Neuroimaging 2015; 25:728-37. [PMID: 25940587 PMCID: PMC4537660 DOI: 10.1111/jon.12252] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2014] [Revised: 03/20/2015] [Accepted: 03/22/2015] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND AND PURPOSE This study investigates 36 subjects aged 55-65 from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database to expand our knowledge of early-onset (EO) Alzheimer's Disease (EO-AD) using neuroimaging biomarkers. METHODS Nine of the subjects had EO-AD, and 27 had EO mild cognitive impairment (EO-MCI). The structural ADNI data were parcellated using BrainParser, and the 15 most discriminating neuroimaging markers between the two cohorts were extracted using the Global Shape Analysis (GSA) Pipeline workflow. Then the Local Shape Analysis (LSA) Pipeline workflow was used to conduct local (per-vertex) post-hoc statistical analyses of the shape differences based on the participants' diagnoses (EO-MCI+EO-AD). Tensor-based Morphometry (TBM) and multivariate regression models were used to identify the significance of the structural brain differences based on the participants' diagnoses. RESULTS The significant between-group regional differences using GSA were found in 15 neuroimaging markers. The results of the LSA analysis workflow were based on the subject diagnosis, age, years of education, apolipoprotein E (ε4), Mini-Mental State Examination, visiting times, and logical memory as regressors. All the variables had significant effects on the regional shape measures. Some of these effects survived the false discovery rate (FDR) correction. Similarly, the TBM analysis showed significant effects on the Jacobian displacement vector fields, but these effects were reduced after FDR correction. CONCLUSIONS These results may explain some of the differences between EO-AD and EO-MCI, and some of the characteristics of the EO cognitive impairment subjects.
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Affiliation(s)
- Seok Woo Moon
- Department of Psychiatry, Konkuk University School of Medicine, Seoul 143-701, Korea
| | - Ivo D. Dinov
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
- University of Michigan, School of Nursing, Ann Arbor, MI 48109, USA
| | - Sam Hobel
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
| | - Alen Zamanyan
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
| | - Young Chil Choi
- Department of Radiology, Konkuk University School of Medicine, Seoul 143-701, Korea
| | - Ran Shi
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
| | - Paul M. Thompson
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
| | - Arthur W. Toga
- Laboratory of Neuro Imaging, Institute for Neuroimaging and Informatics, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA 90032, USA
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Abstract
In much of the developed world, the HIV epidemic has largely been controlled by antiretroviral treatment. Even so, there is growing concern that HIV-infected individuals may be at risk for accelerated brain aging and a range of cognitive impairments. What promotes or resists these changes is largely unknown. There is also interest in discovering factors that promote resilience to HIV and combat its adverse effects in children. Here, we review recent developments in brain imaging that reveal how the virus affects the brain. We relate these brain changes to changes in blood markers, cognitive function, and other patient outcomes or symptoms, such as apathy or neuropathic pain. We focus on new and emerging techniques, including new variants of brain MRI. Diffusion tensor imaging, for example, can map the brain's structural connections, while fMRI can uncover functional connections. Finally, we suggest how large-scale global research alliances, such as ENIGMA, may resolve controversies over effects where evidence is now lacking. These efforts pool scans from tens of thousands of individuals and offer a source of power not previously imaginable for brain imaging studies.
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Affiliation(s)
- Paul Thompson
- Dept. of Neurology, Keck USC School of Medicine, Imaging Genetics Center, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA 90292, Phone: (323) 44-BRAIN Fax: (323) 442-0137
| | - Neda Jahanshad
- Dept. of Neurology, Keck USC School of Medicine, Imaging Genetics Center, University of Southern California, 4676 Admiralty Way, Marina del Rey, CA 90292, Phone: (323) 44-BRAIN Fax: (323) 442-0137
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31
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Nitzken MJ, Casanova MF, Gimelfarb G, Inanc T, Zurada JM, El-Baz A. Shape analysis of the human brain: a brief survey. IEEE J Biomed Health Inform 2015; 18:1337-54. [PMID: 25014938 DOI: 10.1109/jbhi.2014.2298139] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The survey outlines and compares popular computational techniques for quantitative description of shapes of major structural parts of the human brain, including medial axis and skeletal analysis, geodesic distances, Procrustes analysis, deformable models, spherical harmonics, and deformation morphometry, as well as other less widely used techniques. Their advantages, drawbacks, and emerging trends, as well as results of applications, in particular, for computer-aided diagnostics, are discussed.
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32
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Commowick O, Maarouf A, Ferré JC, Ranjeva JP, Edan G, Barillot C. Diffusion MRI abnormalities detection with orientation distribution functions: a multiple sclerosis longitudinal study. Med Image Anal 2015; 22:114-23. [PMID: 25867549 DOI: 10.1016/j.media.2015.02.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2014] [Revised: 02/04/2015] [Accepted: 02/26/2015] [Indexed: 11/19/2022]
Abstract
We propose a new algorithm for the voxelwise analysis of orientation distribution functions between one image and a group of reference images. It relies on a generic framework for the comparison of diffusion probabilities on the sphere, sampled from the underlying models. We demonstrate that this method, combined to dimensionality reduction through a principal component analysis, allows for more robust detection of lesions on simulated data when compared to classical tensor-based analysis. We then demonstrate the efficiency of this pipeline on the longitudinal comparison of multiple sclerosis patients at an early stage of the disease: right after their first clinically isolated syndrome (CIS) and three months later. We demonstrate the predictive value of ODF-based scores for the early detection of lesions that will appear or heal.
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Affiliation(s)
- Olivier Commowick
- VISAGES: INSERM U746, CNRS UMR6074, INRIA, University of Rennes I, France.
| | - Adil Maarouf
- Neurology Department, University Hospital of Reims, France
| | - Jean-Christophe Ferré
- VISAGES: INSERM U746, CNRS UMR6074, INRIA, University of Rennes I, France; Radiology Department, University Hospital of Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France
| | | | - Gilles Edan
- VISAGES: INSERM U746, CNRS UMR6074, INRIA, University of Rennes I, France; Neurology Department, University Hospital of Rennes, 2 Rue Henri le Guilloux, 35000 Rennes, France
| | - Christian Barillot
- VISAGES: INSERM U746, CNRS UMR6074, INRIA, University of Rennes I, France
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Lao Y, Law M, Shi J, Gajawelli N, Haas L, Wang Y, Leporé N. A T1 and DTI fused 3D Corpus Callosum analysis in pre- vs. post-season contact sports players. PROCEEDINGS OF SPIE--THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 2015; 9287:92870O. [PMID: 26412925 PMCID: PMC4580707 DOI: 10.1117/12.2072600] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Sports related traumatic brain injury (TBI) is a worldwide public health issue, and damage to the corpus callosum (CC) has been considered as an important indicator of TBI. However, contact sports players suffer repeated hits to the head during the course of a season even in the absence of diagnosed concussion, and less is known about their effect on callosal anatomy. In addition, T1-weighted and diffusion tensor brain magnetic resonance images (DTI) have been analyzed separately, but a joint analysis of both types of data may increase statistical power and give a more complete understanding of anatomical correlates of subclinical concussions in these athletes. Here, for the first time, we fuse T1 surface-based morphometry and a new DTI analysis on 3D surface representations of the CCs into a single statistical analysis on these subjects. Our new combined method successfully increases detection power in detecting differences between pre- vs. post-season contact sports players. Alterations are found in the ventral genu, isthmus, and splenium of CC. Our findings may inform future health assessments in contact sports players. The new method here is also the first truly multimodal diffusion and T1-weighted analysis of the CC in TBI, and may be useful to detect anatomical changes in the corpus callosum in other multimodal datasets.
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Affiliation(s)
- Yi Lao
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles CA, USA ; Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Meng Law
- Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA ; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Niharika Gajawelli
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles CA, USA ; Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Lauren Haas
- Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Natasha Leporé
- Department of Radiology, Children's Hospital Los Angeles, Los Angeles CA, USA ; Department of Biomedical Engineering, University of Southern California, Los Angeles CA, USA
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Datta S, Staewen TD, Cofield SS, Cutter GR, Lublin FD, Wolinsky JS, Narayana PA. Regional gray matter atrophy in relapsing remitting multiple sclerosis: baseline analysis of multi-center data. Mult Scler Relat Disord 2015; 4:124-36. [PMID: 25787188 PMCID: PMC4366621 DOI: 10.1016/j.msard.2015.01.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2014] [Revised: 11/25/2014] [Accepted: 01/12/2015] [Indexed: 11/28/2022]
Abstract
Regional gray matter (GM) atrophy in multiple sclerosis (MS) at disease onset and its temporal variation can provide objective information regarding disease evolution. An automated pipeline for estimating atrophy of various GM structures was developed using tensor based morphometry (TBM) and implemented on a multi-center sub-cohort of 1008 relapsing remitting MS (RRMS) patients enrolled in a Phase 3 clinical trial. Four hundred age and gender matched healthy controls were used for comparison. Using the analysis of covariance, atrophy differences between MS patients and healthy controls were assessed on a voxel-by-voxel analysis. Regional GM atrophy was observed in a number of deep GM structures that included thalamus, caudate nucleus, putamen, and cortical GM regions. General linear regression analysis was performed to analyze the effects of age, gender, and scanner field strength, and imaging sequence on the regional atrophy. Correlations between regional GM volumes and expanded disability status scale (EDSS) scores, disease duration (DD), T2 lesion load (T2 LL), T1 lesion load (T1 LL), and normalized cerebrospinal fluid (nCSF) were analyzed using Pearson׳s correlation coefficient. Thalamic atrophy observed in MS patients compared to healthy controls remained consistent within subgroups based on gender and scanner field strength. Weak correlations between thalamic volume and EDSS (r=-0.133; p<0.001) and DD (r=-0.098; p=0.003) were observed. Of all the structures, thalamic volume moderately correlated with T2 LL (r=-0.492; P-value<0.001), T1 LL (r=-0.473; P-value<0.001) and nCSF (r=-0.367; P-value<0.001).
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Affiliation(s)
- Sushmita Datta
- Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, 6431 Fannin, Houston, TX 77030, United States.
| | - Terrell D Staewen
- Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, 6431 Fannin, Houston, TX 77030, United States
| | - Stacy S Cofield
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Gary R Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Fred D Lublin
- The Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - Jerry S Wolinsky
- Department of Neurology University of Texas Medical School at Houston, 6431 Fannin, Houston, TX 77030, United States
| | - Ponnada A Narayana
- Department of Diagnostic and Interventional Imaging, University of Texas Medical School at Houston, 6431 Fannin, Houston, TX 77030, United States
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Lao Y, Wang Y, Shi J, Ceschin R, Nelson MD, Panigrahy A, Leporé N. Thalamic alterations in preterm neonates and their relation to ventral striatum disturbances revealed by a combined shape and pose analysis. Brain Struct Funct 2014; 221:487-506. [PMID: 25366970 DOI: 10.1007/s00429-014-0921-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2014] [Accepted: 10/15/2014] [Indexed: 10/24/2022]
Abstract
Finding the neuroanatomical correlates of prematurity is vital to understanding which structures are affected, and to designing efficient prevention and treatment strategies. Converging results reveal that thalamic abnormalities are important indicators of prematurity. However, little is known about the localization of the abnormalities within the subnuclei of the thalamus, or on the association of altered thalamic development with other deep gray matter disturbances. Here, we aim to investigate the effect of prematurity on the thalamus and the putamen in the neonatal brain, and further investigate the associated abnormalities between these two structures. Using brain structural magnetic resonance imaging, we perform a novel combined shape and pose analysis of the thalamus and putamen between 17 preterm (41.12 ± 5.08 weeks) and 19 term-born (45.51 ± 5.40 weeks) neonates at term equivalent age. We also perform a set of correlation analyses between the thalamus and the putamen, based on the surface and pose results. We locate significant alterations on specific surface regions such as the anterior and ventral anterior (VA) thalamic nuclei, and significant relative pose changes of the left thalamus and the right putamen. In addition, we detect significant association between the thalamus and the putamen for both surface and pose parameters. The regions that are significantly associated include the VA, and the anterior and inferior putamen. We detect statistically significant surface deformations and pose changes on the thalamus and putamen, and for the first time, demonstrate the feasibility of using relative pose parameters as indicators for prematurity in neonates. Our methods show that regional abnormalities of the thalamus are associated with alterations of the putamen, possibly due to disturbed development of shared pre-frontal connectivity. More specifically, the significantly correlated regions in these two structures point to frontal-subcortical pathways including the dorsolateral prefrontal-subcortical circuit, the lateral orbitofrontal-subcortical circuit, the motor circuit, and the oculomotor circuit. These findings reveal new insight into potential subcortical structural covariates for poor neurodevelopmental outcomes in the preterm population.
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Affiliation(s)
- Yi Lao
- Department of Radiology, University of Southern California and Children's Hospital, 4650 Sunset Blvd, MS#81, Los Angeles, CA, 90027, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA
| | - Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, 85281, USA
| | - Rafael Ceschin
- Department of Radiology, Children's Hospital of Pittsburgh UPMC, Pittsburgh, PA, USA
| | - Marvin D Nelson
- Department of Radiology, University of Southern California and Children's Hospital, 4650 Sunset Blvd, MS#81, Los Angeles, CA, 90027, USA
| | - Ashok Panigrahy
- Department of Radiology, University of Southern California and Children's Hospital, 4650 Sunset Blvd, MS#81, Los Angeles, CA, 90027, USA.,Department of Radiology, Children's Hospital of Pittsburgh UPMC, Pittsburgh, PA, USA
| | - Natasha Leporé
- Department of Radiology, University of Southern California and Children's Hospital, 4650 Sunset Blvd, MS#81, Los Angeles, CA, 90027, USA.
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Gruslys A, Acosta-Cabronero J, Nestor PJ, Williams GB, Ansorge RE. A new fast accurate nonlinear medical image registration program including surface preserving regularization. IEEE TRANSACTIONS ON MEDICAL IMAGING 2014; 33:2118-2127. [PMID: 24968094 DOI: 10.1109/tmi.2014.2332370] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Recently inexpensive graphical processing units (GPUs) have become established as a viable alternative to traditional CPUs for many medical image processing applications. GPUs offer the potential of very significant improvements in performance at low cost and with low power consumption. One way in which GPU programs differ from traditional CPU programs is that increasingly elaborate calculations per voxel may not impact of the overall processing time because memory accesses can dominate execution time. This paper presents a new GPU based elastic image registration program named Ezys. The Ezys image registration algorithm belongs to the wide class of diffeomorphic demons but uses surface preserving image smoothing and regularization filters designed for a GPU that would be computationally expensive on a CPU. We describe the methods used in Ezys and present results from two important neuroscience applications. Firstly inter-subject registration for transfer of anatomical labels and secondly longitudinal intra-subject registration to quantify atrophy in individual subjects. Both experiments showed that Ezys registration compares favorably with other popular elastic image registration programs. We believe Ezys is a useful tool for neuroscience and other applications, and also demonstrates the value of developing of novel image processing filters specifically designed for GPUs.
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Gongvatana A, Correia S, Dunsiger S, Gauthier L, Devlin KN, Ross S, Navia B, Tashima KT, DeLaMonte S, Cohen RA. Plasma cytokine levels are related to brain volumes in HIV-infected individuals. J Neuroimmune Pharmacol 2014; 9:740-50. [PMID: 25273619 DOI: 10.1007/s11481-014-9567-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Accepted: 09/09/2014] [Indexed: 02/08/2023]
Abstract
HIV-infected individuals frequently exhibit brain dysfunction despite antiretroviral treatment. The neuropathological mechanisms underlying these abnormalities remain unclear, pointing to the importance of identifying biomarkers sensitive to brain dysfunction. We examined 74 medically stable HIV-infected individuals using T1-weighted MRI. Volumes of the cortical grey matter (GM), white matter (WM), caudate, putamen, globus pallidus, thalamus, hippocampus, amygdala, and ventricles were derived using automated parcellation. A panel of plasma cytokines was measured using multiplexed bead array immunoassay. A model selection algorithm was used to select the combination of clinical and cytokine markers that best predicted each brain volumetric measure in a series of linear regression models. Higher CD4 nadir, shorter HIV infection duration, and antiretroviral treatment were significantly related to higher volumes of the putamen, thalamus, hippocampus, and WM. Older age was related to lower volumes in most brain regions and higher ventricular volume. Higher IFN-γ, MCP-1, and TNF-α were related to higher volumes of the putamen, pallidum, amygdala, GM, and WM. Higher IL-1β, IL-6, IL-16, IL-18, IP-10, MIP-1β, and SDF-1α were related to lower volumes of the putamen, pallidum, thalamus, hippocampus, amygdala, GM, and WM; and higher ventricular volume. The current findings provide evidence linking smaller brain volumes to HIV disease history, antiretroviral treatment, and advanced age. Cytokine markers, especially IL-6 and IL-16, showed robust association with brain volumes even after accounting for other clinical variables, demonstrating their utility in examining the mechanisms of HIV-associated brain abnormalities.
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Shi J, Leporé N, Gutman BA, Thompson PM, Baxter LC, Caselli RJ, Wang Y. Genetic influence of apolipoprotein E4 genotype on hippocampal morphometry: An N = 725 surface-based Alzheimer's disease neuroimaging initiative study. Hum Brain Mapp 2014; 35:3903-18. [PMID: 24453132 PMCID: PMC4269525 DOI: 10.1002/hbm.22447] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2013] [Revised: 11/23/2013] [Accepted: 11/26/2013] [Indexed: 01/12/2023] Open
Abstract
The apolipoprotein E (APOE) e4 allele is the most prevalent genetic risk factor for Alzheimer's disease (AD). Hippocampal volumes are generally smaller in AD patients carrying the e4 allele compared to e4 noncarriers. Here we examined the effect of APOE e4 on hippocampal morphometry in a large imaging database-the Alzheimer's Disease Neuroimaging Initiative (ADNI). We automatically segmented and constructed hippocampal surfaces from the baseline MR images of 725 subjects with known APOE genotype information including 167 with AD, 354 with mild cognitive impairment (MCI), and 204 normal controls. High-order correspondences between hippocampal surfaces were enforced across subjects with a novel inverse consistent surface fluid registration method. Multivariate statistics consisting of multivariate tensor-based morphometry (mTBM) and radial distance were computed for surface deformation analysis. Using Hotelling's T(2) test, we found significant morphological deformation in APOE e4 carriers relative to noncarriers in the entire cohort as well as in the nondemented (pooled MCI and control) subjects, affecting the left hippocampus more than the right, and this effect was more pronounced in e4 homozygotes than heterozygotes. Our findings are consistent with previous studies that showed e4 carriers exhibit accelerated hippocampal atrophy; we extend these findings to a novel measure of hippocampal morphometry. Hippocampal morphometry has significant potential as an imaging biomarker of early stage AD.
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Affiliation(s)
- Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State UniversityTempeArizona
| | - Natasha Leporé
- Department of RadiologyChildren's Hospital Los AngelesLos AngelesCalifornia
| | - Boris A. Gutman
- Imaging Genetics CenterInstitute for Neuroimaging and InformaticsUniversity of Southern CaliforniaLos AngelesCalifornia
| | - Paul M. Thompson
- Department of NeurologyImaging Genetics CenterLaboratory of Neuro ImagingUCLA School of MedicineLos AngelesCalifornia
- Department of Psychiatry and Biobehavioral SciencesSemel Institute, UCLA School of MedicineLos AngelesCalifornia
| | - Leslie C. Baxter
- Human Brain Imaging Laboratory, Barrow Neurological InstitutePhoenixArizona
| | | | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State UniversityTempeArizona
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Knickmeyer RC, Wang J, Zhu H, Geng X, Woolson S, Hamer RM, Konneker T, Lin W, Styner M, Gilmore JH. Common variants in psychiatric risk genes predict brain structure at birth. Cereb Cortex 2014; 24:1230-46. [PMID: 23283688 PMCID: PMC3977618 DOI: 10.1093/cercor/bhs401] [Citation(s) in RCA: 97] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Studies in adolescents and adults have demonstrated that polymorphisms in putative psychiatric risk genes are associated with differences in brain structure, but cannot address when in development these relationships arise. To determine if common genetic variants in disrupted-in-schizophrenia-1 (DISC1; rs821616 and rs6675281), catechol-O-methyltransferase (COMT; rs4680), neuregulin 1 (NRG1; rs35753505 and rs6994992), apolipoprotein E (APOE; ε3ε4 vs. ε3ε3), estrogen receptor alpha (ESR1; rs9340799 and rs2234693), brain-derived neurotrophic factor (BDNF; rs6265), and glutamate decarboxylase 1 (GAD1; rs2270335) are associated with individual differences in brain tissue volumes in neonates, we applied both automated region-of-interest volumetry and tensor-based morphometry to a sample of 272 neonates who had received high-resolution magnetic resonance imaging scans. ESR1 (rs9340799) predicted intracranial volume. Local variation in gray matter (GM) volume was significantly associated with polymorphisms in DISC1 (rs821616), COMT, NRG1, APOE, ESR1 (rs9340799), and BDNF. No associations were identified for DISC1 (rs6675281), ESR1 (rs2234693), or GAD1. Of note, neonates homozygous for the DISC1 (rs821616) serine allele exhibited numerous large clusters of reduced GM in the frontal lobes, and neonates homozygous for the COMT valine allele exhibited reduced GM in the temporal cortex and hippocampus, mirroring findings in adults. The results highlight the importance of prenatal brain development in mediating psychiatric risk.
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Affiliation(s)
| | | | | | | | | | | | - Thomas Konneker
- Department of Biomolecular Engineering, University of California, Santa Cruz, CA, USA
| | | | - Martin Styner
- Department of Psychiatry
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA and
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40
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A novel approach to estimate trabecular bone anisotropy from stress tensors. Biomech Model Mechanobiol 2014; 14:39-48. [DOI: 10.1007/s10237-014-0584-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Accepted: 04/06/2014] [Indexed: 10/25/2022]
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Prasad G, Joshi SH, Jahanshad N, Villalon-Reina J, Aganj I, Lenglet C, Sapiro G, McMahon KL, de Zubicaray GI, Martin NG, Wright MJ, Toga AW, Thompson PM. Automatic clustering and population analysis of white matter tracts using maximum density paths. Neuroimage 2014; 97:284-95. [PMID: 24747738 DOI: 10.1016/j.neuroimage.2014.04.033] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2013] [Revised: 03/24/2014] [Accepted: 04/08/2014] [Indexed: 10/25/2022] Open
Abstract
We introduce a framework for population analysis of white matter tracts based on diffusion-weighted images of the brain. The framework enables extraction of fibers from high angular resolution diffusion images (HARDI); clustering of the fibers based partly on prior knowledge from an atlas; representation of the fiber bundles compactly using a path following points of highest density (maximum density path; MDP); and registration of these paths together using geodesic curve matching to find local correspondences across a population. We demonstrate our method on 4-Tesla HARDI scans from 565 young adults to compute localized statistics across 50 white matter tracts based on fractional anisotropy (FA). Experimental results show increased sensitivity in the determination of genetic influences on principal fiber tracts compared to the tract-based spatial statistics (TBSS) method. Our results show that the MDP representation reveals important parts of the white matter structure and considerably reduces the dimensionality over comparable fiber matching approaches.
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Affiliation(s)
- Gautam Prasad
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Laboratory of Neuro Imaging, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA
| | - Shantanu H Joshi
- Department of Neurology, University of California Los Angeles, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Laboratory of Neuro Imaging, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA
| | - Julio Villalon-Reina
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Laboratory of Neuro Imaging, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA
| | - Iman Aganj
- Martinos Center for Biomedical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Guillermo Sapiro
- Dept. of Electrical and Computer Engineering, Computer Science, Duke University, NC, USA; Dept. of Biomedical Engineering, Duke University, NC, USA
| | - Katie L McMahon
- Center for Advanced Imaging, University of Queensland, Brisbane, Australia
| | | | | | - Margaret J Wright
- School of Psychology, University of Queensland, Brisbane, Australia; QIMR Berghofer Medical Research Institute, Herston, Australia
| | - Arthur W Toga
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Laboratory of Neuro Imaging, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Dept. of Neurology, Psychiatry, Engineering, Radiology, University of Southern California, Los Angeles, CA, USA; Dept. of Ophthalmology, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Laboratory of Neuro Imaging, Institute for Neuroimaging & Informatics, University of Southern California, Los Angeles, CA, USA; Department of Neurology, University of California Los Angeles, CA, USA; Dept. of Neurology, Psychiatry, Engineering, Radiology, University of Southern California, Los Angeles, CA, USA; Dept. of Ophthalmology, University of Southern California, Los Angeles, CA, USA; Department of Pediatrics, University of Southern California, Los Angeles, CA, USA.
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42
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Joint statistics on cardiac shape and fiber architecture. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2014. [PMID: 24579177 DOI: 10.1007/978-3-642-40763-5_61] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register]
Abstract
Cardiac fiber architecture plays an important role in electrophysiological and mechanical functions of the heart. Yet, its inter-subject variability and more particularly, its relationship to the shape of the myocardium, is not fully understood. In this paper, we extend the statistical analysis of cardiac fiber architecture beyond its description with a fixed average geometry. We study the co-variation of fiber architecture with either shape or strain-based information by exploring their principal modes of joint variations. We apply our general framework to a dataset of 8 ex vivo canine hearts, and find that strain-based information appears to correlate best with the fiber architecture. Furthermore, compared to current approaches that warp an average atlas to the patient geometry, our preliminary results show that joint statistics improves fiber synthesis from shape by 8.0%, with cases up to 25.9%. Our experiments also reveal evidence on a possible relation between architectural variability and myocardial thickness.
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43
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Nir TM, Jahanshad N, Busovaca E, Wendelken L, Nicolas K, Thompson PM, Valcour VG. Mapping white matter integrity in elderly people with HIV. Hum Brain Mapp 2014; 35:975-92. [PMID: 23362139 PMCID: PMC3775847 DOI: 10.1002/hbm.22228] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2012] [Revised: 11/02/2012] [Accepted: 11/05/2012] [Indexed: 01/23/2023] Open
Abstract
People with HIV are living longer as combination antiretroviral therapy (cART) becomes more widely available. However, even when plasma viral load is reduced to untraceable levels, chronic HIV infection is associated with neurological deficits and brain atrophy beyond that of normal aging. HIV is often marked by cortical and subcortical atrophy, but the integrity of the brain's white matter (WM) pathways also progressively declines. Few studies focus on older cohorts where normal aging may be compounded with HIV infection to influence deficit patterns. In this relatively large diffusion tensor imaging (DTI) study, we investigated abnormalities in WM fiber integrity in 56 HIV+ adults with access to cART (mean age: 63.9 ± 3.7 years), compared to 31 matched healthy controls (65.4 ± 2.2 years). Statistical 3D maps revealed the independent effects of HIV diagnosis and age on fractional anisotropy (FA) and diffusivity, but we did not find any evidence for an age by diagnosis interaction in our current sample. Compared to healthy controls, HIV patients showed pervasive FA decreases and diffusivity increases throughout WM. We also assessed neuropsychological (NP) summary z-score associations. In both patients and controls, fiber integrity measures were associated with NP summary scores. The greatest differences were detected in the corpus callosum and in the projection fibers of the corona radiata. These deficits are consistent with published NP deficits and cortical atrophy patterns in elderly people with HIV.
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Affiliation(s)
- Talia M Nir
- Imaging Genetics Center, Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, California
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44
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Guo M, Yap JT, Van den Abbeele AD, Lin NU, Schwartzman A. Voxelwise single-subject analysis of imaging metabolic response to therapy in neuro-oncology. Stat (Int Stat Inst) 2014; 3:172-186. [PMID: 24999285 PMCID: PMC4078880 DOI: 10.1002/sta4.53] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
F-18-Fluorodeoxyglucose positron emission tomography (FDG-PET) has been used to evaluate the metabolic response of metastatic brain tumors to treatment by comparing their tumor glucose metabolism before and after treatment. The standard analysis based on regions-of-interest has the advantage of simplicity. However, it is by definition restricted to those regions and is subject to observer variability. In addition, the observed changes in tumor metabolism are often confounded by normal changes in the tissue background, which can be heterogenous. We propose an analysis pipeline for automatically detecting the change at each voxel in the entire brain of a single subject, while adjusting for changes in the background. The complete analysis includes image registration, segmentation, a hierarchical model for background adjustment and voxelwise statistical comparisons. We demonstrate the method's ability to identify areas of tumor response and/or progression in two subjects enrolled in a clinical trial using FDG-PET to evaluate lapatinib for the treatment of brain metastases in breast cancer patients.
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Affiliation(s)
- Mengye Guo
- Department of Biostatistics, University of Washington, 6200 NE 74th St, Seattle, WA, 98115
| | - Jeffrey T. Yap
- Center for Quantitative Cancer Imaging, University of Utah, 2000 Circle of Hope, Salt Lake City, UT 84112
| | - Annick D. Van den Abbeele
- Department of Imaging, Dana-Farber/Harvard Cancer Center, 450 Brookline Avenue, DL101, Boston, MA 02215
| | - Nancy U. Lin
- Department of Medical Oncology, Dana-Farber/Harvard Cancer Center, 450 Brookline Avenue, Boston, MA 02215
| | - Armin Schwartzman
- Department of Statistics, North Carolina State University, 2311 Stinson Drive, Raleigh, NC 27615
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45
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Zhang J, Wang J, Wang X, Feng D. The adaptive FEM elastic model for medical image registration. Phys Med Biol 2013; 59:97-118. [PMID: 24334618 DOI: 10.1088/0031-9155/59/1/97] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
This paper proposes an adaptive mesh refinement strategy for the finite element method (FEM) based elastic registration model. The signature matrix for mesh refinement takes into account the regional intensity variance and the local deformation displacement. The regional intensity variance reflects detailed information for improving registration accuracy and the deformation displacement fine-tunes the mesh refinement for a more efficient algorithm. The gradient flows of two different similarity metrics, the sum of the squared difference and the spatially encoded mutual information for the mono-modal and multi-modal registrations, are used to derive external forces to drive the model to the equilibrium state. We compared our approach to three other models: (1) the conventional multi-resolution FEM registration algorithm; (2) the FEM elastic method that uses variation information for mesh refinement; and (3) the robust block matching based registration. Comparisons among different methods in a dataset with 20 CT image pairs upon artificial deformation demonstrate that our registration method achieved significant improvement in accuracies. Experimental results in another dataset of 40 real medical image pairs for both mono-modal and multi-modal registrations also show that our model outperforms the other three models in its accuracy.
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Affiliation(s)
- Jingya Zhang
- School of Electronic and Information Engineering, Soochow University, Suzhou 215006, People's Republic of China. Dept Phys, Changshu Inst Technol, Changshu 215500, People's Republic of China
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Carballido-Gamio J, Harnish R, Saeed I, Streeper T, Sigurdsson S, Amin S, Atkinson EJ, Therneau TM, Siggeirsdottir K, Cheng X, Melton LJ, Keyak J, Gudnason V, Khosla S, Harris TB, Lang TF. Structural patterns of the proximal femur in relation to age and hip fracture risk in women. Bone 2013; 57:290-9. [PMID: 23981658 PMCID: PMC3809121 DOI: 10.1016/j.bone.2013.08.017] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2012] [Revised: 08/09/2013] [Accepted: 08/13/2013] [Indexed: 11/21/2022]
Abstract
Fractures of the proximal femur are the most devastating outcome of osteoporosis. It is generally understood that age-related changes in hip structure confer increased risk, but there have been few explicit comparisons of such changes in healthy subjects to those with hip fracture. In this study, we used quantitative computed tomography and tensor-based morphometry (TBM) to identify three-dimensional internal structural patterns of the proximal femur associated with age and with incident hip fracture. A population-based cohort of 349 women representing a broad age range (21-97years) was included in this study, along with a cohort of 222 older women (mean age 79±7years) with (n=74) and without (n=148) incident hip fracture. Images were spatially normalized to a standardized space, and age- and fracture-specific morphometric features were identified based on statistical maps of shape features described as local changes of bone volume. Morphometric features were visualized as maps of local contractions and expansions, and significance was displayed as Student's t-test statistical maps. Significant age-related changes included local expansions of regions low in volumetric bone mineral density (vBMD) and local contractions of regions high in vBMD. Some significant fracture-related features resembled an accentuated aging process, including local expansion of the superior aspect of the trabecular bone compartment in the femoral neck, with contraction of the adjoining cortical bone. However, other features were observed only in the comparison of hip fracture subjects with age-matched controls including focal contractions of the cortical bone at the superior aspect of the femoral neck, the lateral cortical bone just inferior to the greater trochanter, and the anterior intertrochanteric region. Results of this study support the idea that the spatial distribution of morphometric features is relevant to age-related changes in bone and independent to fracture risk. In women, the identification by TBM of fracture-specific morphometric alterations of the proximal femur, in conjunction with vBMD and clinical risk factors, may improve hip fracture prediction.
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Affiliation(s)
- Julio Carballido-Gamio
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Roy Harnish
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Isra Saeed
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Timothy Streeper
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | | | - Shreyasee Amin
- Division of Epidemiology, Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Rheumatology, Department of Internal Medicine, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Elizabeth J. Atkinson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Terry M. Therneau
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Xiaoguang Cheng
- Department of Radiology, Beijing Ji Shui Tan Hospital, Beijing, China
| | - L. Joseph Melton
- Division of Epidemiology, Department of Health Sciences Research, College of Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Joyce Keyak
- Department of Radiological Sciences, University of California, Irvine, Irvine, CA, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Sundeep Khosla
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Tamara B. Harris
- Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Thomas F. Lang
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
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Shi J, Thompson PM, Gutman B, Wang Y. Surface fluid registration of conformal representation: application to detect disease burden and genetic influence on hippocampus. Neuroimage 2013; 78:111-34. [PMID: 23587689 PMCID: PMC3683848 DOI: 10.1016/j.neuroimage.2013.04.018] [Citation(s) in RCA: 66] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2012] [Revised: 03/06/2013] [Accepted: 04/05/2013] [Indexed: 11/23/2022] Open
Abstract
In this paper, we develop a new automated surface registration system based on surface conformal parameterization by holomorphic 1-forms, inverse consistent surface fluid registration, and multivariate tensor-based morphometry (mTBM). First, we conformally map a surface onto a planar rectangle space with holomorphic 1-forms. Second, we compute surface conformal representation by combining its local conformal factor and mean curvature and linearly scale the dynamic range of the conformal representation to form the feature image of the surface. Third, we align the feature image with a chosen template image via the fluid image registration algorithm, which has been extended into the curvilinear coordinates to adjust for the distortion introduced by surface parameterization. The inverse consistent image registration algorithm is also incorporated in the system to jointly estimate the forward and inverse transformations between the study and template images. This alignment induces a corresponding deformation on the surface. We tested the system on Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset to study AD symptoms on hippocampus. In our system, by modeling a hippocampus as a 3D parametric surface, we nonlinearly registered each surface with a selected template surface. Then we used mTBM to analyze the morphometry difference between diagnostic groups. Experimental results show that the new system has better performance than two publicly available subcortical surface registration tools: FIRST and SPHARM. We also analyzed the genetic influence of the Apolipoprotein E[element of]4 allele (ApoE4), which is considered as the most prevalent risk factor for AD. Our work successfully detected statistically significant difference between ApoE4 carriers and non-carriers in both patients of mild cognitive impairment (MCI) and healthy control subjects. The results show evidence that the ApoE genotype may be associated with accelerated brain atrophy so that our work provides a new MRI analysis tool that may help presymptomatic AD research.
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Affiliation(s)
- Jie Shi
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Paul M. Thompson
- Laboratory of Neuro Imaging, UCLA Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA, USA
| | - Boris Gutman
- Laboratory of Neuro Imaging, UCLA Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA, USA
| | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA
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48
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Hua X, Boyle CP, Harezlak J, Tate DF, Yiannoutsos CT, Cohen R, Schifitto G, Gongvatana A, Zhong J, Zhu T, Taylor MJ, Campbell TB, Daar ES, Alger JR, Singer E, Buchthal S, Toga AW, Navia B, Thompson PM. Disrupted cerebral metabolite levels and lower nadir CD4 + counts are linked to brain volume deficits in 210 HIV-infected patients on stable treatment. NEUROIMAGE-CLINICAL 2013; 3:132-42. [PMID: 24179857 PMCID: PMC3791291 DOI: 10.1016/j.nicl.2013.07.009] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2013] [Revised: 07/03/2013] [Accepted: 07/25/2013] [Indexed: 12/18/2022]
Abstract
Cognitive impairment and brain injury are common in people with HIV/AIDS, even when viral replication is effectively suppressed with combined antiretroviral therapies (cART). Metabolic and structural abnormalities may promote cognitive decline, but we know little about how these measures relate in people on stable cART. Here we used tensor-based morphometry (TBM) to reveal the 3D profile of regional brain volume variations in 210 HIV + patients scanned with whole-brain MRI at 1.5 T (mean age: 48.6 ± 8.4 years; all receiving cART). We identified brain regions where the degree of atrophy was related to HIV clinical measures and cerebral metabolite levels assessed with magnetic resonance spectroscopy (MRS). Regional brain volume reduction was linked to lower nadir CD4 + count, with a 1–2% white matter volume reduction for each 25-point reduction in nadir CD4 +. Even so, brain volume measured by TBM showed no detectable association with current CD4 + count, AIDS Dementia Complex (ADC) stage, HIV RNA load in plasma or cerebrospinal fluid (CSF), duration of HIV infection, antiretroviral CNS penetration-effectiveness (CPE) scores, or years on cART, after controlling for demographic factors, and for multiple comparisons. Elevated glutamate and glutamine (Glx) and lower N-acetylaspartate (NAA) in the frontal white matter, basal ganglia, and mid frontal cortex — were associated with lower white matter, putamen and thalamus volumes, and ventricular and CSF space expansion. Reductions in brain volumes in the setting of chronic and stable disease are strongly linked to a history of immunosuppression, suggesting that delays in initiating cART may result in imminent and irreversible brain damage. We mapped the 3D pattern of brain abnormalities in 210 HIV patients on stable cART. Brain atrophy was linked to MRS metabolite disturbances reflecting neuronal injury. Lower nadir CD4 + count was associated with greater white matter atrophy.
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Affiliation(s)
- Xue Hua
- Imaging Genetics Center, Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles, CA, USA
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49
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Shi J, Wang Y, Ceschin R, An X, Lao Y, Vanderbilt D, Nelson MD, Thompson PM, Panigrahy A, Leporé N. A multivariate surface-based analysis of the putamen in premature newborns: regional differences within the ventral striatum. PLoS One 2013; 8:e66736. [PMID: 23843961 PMCID: PMC3700976 DOI: 10.1371/journal.pone.0066736] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2013] [Accepted: 05/09/2013] [Indexed: 11/20/2022] Open
Abstract
Many children born preterm exhibit frontal executive dysfunction, behavioral problems including attentional deficit/hyperactivity disorder and attention related learning disabilities. Anomalies in regional specificity of cortico-striato-thalamo-cortical circuits may underlie deficits in these disorders. Nonspecific volumetric deficits of striatal structures have been documented in these subjects, but little is known about surface deformation in these structures. For the first time, here we found regional surface morphological differences in the preterm neonatal ventral striatum. We performed regional group comparisons of the surface anatomy of the striatum (putamen and globus pallidus) between 17 preterm and 19 term-born neonates at term-equivalent age. We reconstructed striatal surfaces from manually segmented brain magnetic resonance images and analyzed them using our in-house conformal mapping program. All surfaces were registered to a template with a new surface fluid registration method. Vertex-based statistical comparisons between the two groups were performed via four methods: univariate and multivariate tensor-based morphometry, the commonly used medial axis distance, and a combination of the last two statistics. We found statistically significant differences in regional morphology between the two groups that are consistent across statistics, but more extensive for multivariate measures. Differences were localized to the ventral aspect of the striatum. In particular, we found abnormalities in the preterm anterior/inferior putamen, which is interconnected with the medial orbital/prefrontal cortex and the midline thalamic nuclei including the medial dorsal nucleus and pulvinar. These findings support the hypothesis that the ventral striatum is vulnerable, within the cortico-stiato-thalamo-cortical neural circuitry, which may underlie the risk for long-term development of frontal executive dysfunction, attention deficit hyperactivity disorder and attention-related learning disabilities in preterm neonates.
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Affiliation(s)
- Jie Shi
- School of Computing, Informatics, Decision Systems and Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Yalin Wang
- School of Computing, Informatics, Decision Systems and Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Rafael Ceschin
- Department of Radiology, Children’s Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States of America
| | - Xing An
- School of Computing, Informatics, Decision Systems and Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Yi Lao
- Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America
| | - Douglas Vanderbilt
- Department of Pediatrics, University of Southern California, Los Angeles, California, United States of America
- Developmental-Behavioral Pediatrics Fellowship Program, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
| | - Marvin D. Nelson
- Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
- Department of Radiology, University of Southern California, Los Angeles, California, United States of America
| | - Paul M. Thompson
- Imaging Genetics Center, Laboratory of Neuro Imaging, University of California Los Angeles School of Medicine, Los Angeles, California, United States of America
| | - Ashok Panigrahy
- Department of Radiology, Children’s Hospital of Pittsburgh, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, United States of America
- Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
| | - Natasha Leporé
- Department of Radiology, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
- Department of Biomedical Engineering, University of Southern California, Los Angeles, California, United States of America
- Department of Radiology, University of Southern California, Los Angeles, California, United States of America
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50
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Zhan J, Dinov ID, Li J, Zhang Z, Hobel S, Shi Y, Lin X, Zamanyan A, Feng L, Teng G, Fang F, Tang Y, Zang F, Toga AW, Liu S. Spatial-temporal atlas of human fetal brain development during the early second trimester. Neuroimage 2013; 82:115-26. [PMID: 23727529 DOI: 10.1016/j.neuroimage.2013.05.063] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2013] [Revised: 05/15/2013] [Accepted: 05/16/2013] [Indexed: 01/29/2023] Open
Abstract
During the second trimester, the human fetal brain undergoes numerous changes that lead to substantial variation in the neonatal in terms of its morphology and tissue types. As fetal MRI is more and more widely used for studying the human brain development during this period, a spatiotemporal atlas becomes necessary for characterizing the dynamic structural changes. In this study, 34 postmortem human fetal brains with gestational ages ranging from 15 to 22 weeks were scanned using 7.0 T MR. We used automated morphometrics, tensor-based morphometry and surface modeling techniques to analyze the data. Spatiotemporal atlases of each week and the overall atlas covering the whole period with high resolution and contrast were created. These atlases were used for the analysis of age-specific shape changes during this period, including development of the cerebral wall, lateral ventricles, Sylvian fissure, and growth direction based on local surface measurements. Our findings indicate that growth of the subplate zone is especially striking and is the main cause for the lamination pattern changes. Changes in the cortex around Sylvian fissure demonstrate that cortical growth may be one of the mechanisms for gyration. Surface deformation mapping, revealed by local shape analysis, indicates that there is global anterior-posterior growth pattern, with frontal and temporal lobes developing relatively quickly during this period. Our results are valuable for understanding the normal brain development trajectories and anatomical characteristics. These week-by-week fetal brain atlases can be used as reference in in vivo studies, and may facilitate the quantification of fetal brain development across space and time.
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Affiliation(s)
- Jinfeng Zhan
- Research Center for Sectional and Imaging Anatomy, Shandong University School of Medicine, 44 Wen-hua Xi Road, 250012 Jinan, Shandong, China
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