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Lee W, Lee S, Park Y, Kim GE, Bae JB, Han JW, Kim KW. Construction and validation of a brain magnetic resonance imaging template for normal older Koreans. BMC Neurol 2024; 24:222. [PMID: 38943101 PMCID: PMC11212263 DOI: 10.1186/s12883-024-03735-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 06/17/2024] [Indexed: 07/01/2024] Open
Abstract
BACKGROUND Spatial normalization to a standardized brain template is a crucial step in magnetic resonance imaging (MRI) studies. Brain templates made from sufficient sample size have low brain variability, improving the accuracy of spatial normalization. Using population-specific template improves accuracy of spatial normalization because brain morphology varies according to ethnicity and age. METHODS We constructed a brain template of normal Korean elderly (KNE200) using MRI scans 100 male and 100 female aged over 60 years old with normal cognition. We compared the deformation after spatial normalization of the KNE200 template to that of the KNE96, constructed from 96 cognitively normal elderly Koreans and to that of the brain template (OCF), constructed from 434 non-demented older Caucasians to examine the effect of sample size and ethnicity on the accuracy of brain template, respectively. We spatially normalized the MRI scans of elderly Koreans and quantified the amount of deformations associated with spatial normalization using the magnitude of displacement and volumetric changes of voxels. RESULTS The KNE200 yielded significantly less displacement and volumetric change in the parahippocampal gyrus, medial and posterior orbital gyrus, fusiform gyrus, gyrus rectus, cerebellum and vermis than the KNE96. The KNE200 also yielded much less displacement in the cerebellum, vermis, hippocampus, parahippocampal gyrus and thalamus and much less volumetric change in the cerebellum, vermis, hippocampus and parahippocampal gyrus than the OCF. CONCLUSION KNE200 had the better accuracy than the KNE96 due to the larger sample size and was far accurate than the template constructed from elderly Caucasians in elderly Koreans.
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Grants
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- HI09C1379 [A092077] Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- MSIT; 2018-2-00861 Institute for Information and Communications Technology Promotion
- Korean Health Technology R&D Project, Ministry of Health and Welfare, Republic of Korea
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Affiliation(s)
- Wheesung Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Subin Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Yeseung Park
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Grace Eun Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Jong Bin Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ki Woong Kim
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, Republic of Korea.
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Eisermann M, Fillon L, Saitovitch A, Boisgontier J, Vinçon-Leite A, Dangouloff-Ros V, Blauwblomme T, Bourgeois M, Dangles MT, Coste-Zeitoun D, Vignolo-Diard P, Aubart M, Kossorotoff M, Hully M, Losito E, Chemaly N, Zilbovicius M, Desguerre I, Nabbout R, Boddaert N, Kaminska A. Periodic electroencephalographic discharges and epileptic spasms involve cortico-striatal-thalamic loops on Arterial Spin Labeling Magnetic Resonance Imaging. Brain Commun 2022; 4:fcac250. [PMID: 36324869 PMCID: PMC9598541 DOI: 10.1093/braincomms/fcac250] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2021] [Revised: 06/15/2022] [Accepted: 10/05/2022] [Indexed: 11/07/2022] Open
Abstract
Periodic discharges are a rare peculiar electroencephalogram pattern, occasionally associated with motor or other clinical manifestations, usually observed in critically ill patients. Their underlying pathophysiology remains poorly understood. Epileptic spasms in clusters and periodic discharges with motor manifestations share similar electroencephalogram pattern and some aetiologies of unfavourable prognosis such as subacute sclerosing panencephalitis or herpes encephalitis. Arterial spin labelling magnetic resonance imaging identifies localizing ictal and inter-ictal changes in neurovascular coupling, therefore assumed able to reveal concerned cerebral structures. Here, we retrospectively analysed ictal and inter-ictal arterial spin labelling magnetic resonance imaging in patients aged 6 months to 15 years (median 3 years 4 months) with periodic discharges including epileptic spasms, and compared these findings with those of patients with drug-resistant focal epilepsy who never presented periodic discharges nor epileptic spasms as well as to those of age-matched healthy controls. Ictal electroencephalogram was recorded either simultaneously with arterial spin labelling magnetic resonance imaging or during the close time lapse of patients' periodic discharges, whereas inter-ictal examinations were performed during the patients' active epilepsy but without seizures during the arterial spin labelling magnetic resonance imaging. Ictal arterial spin labelling magnetic resonance imaging was acquired in five patients with periodic discharges [subacute sclerosing panencephalitis (1), stroke-like events (3), West syndrome with cortical malformation (1), two of them also had inter-ictal arterial spin labelling magnetic resonance imaging]. Inter-ictal group included patients with drug-resistant epileptic spasms of various aetiologies (14) and structural drug-resistant focal epilepsy (8). Cortex, striatum and thalamus were segmented and divided in six functional subregions: prefrontal, motor (rostral, caudal), parietal, occipital and temporal. Rest cerebral blood flow values, absolute and relative to whole brain, were compared with those of age-matched controls for each subregion. Main findings were diffuse striatal as well as cortical motor cerebral blood flow increase during ictal examinations in generalized periodic discharges with motor manifestations (subacute sclerosing panencephalitis) and focal cerebral blood flow increase in corresponding cortical-striatal-thalamic subdivisions in lateralized periodic discharges with or without motor manifestations (stroke-like events and asymmetrical epileptic spasms) with straight topographical correlation with the electroencephalogram focus. For inter-ictal examinations, patients with epileptic spasms disclosed cerebral blood flow changes in corresponding cortical-striatal-thalamic subdivisions (absolute-cerebral blood flow decrease and relative-cerebral blood flow increase), more frequently when compared with the group of drug-resistant focal epilepsies, and not related to Vigabatrin treatment. Our results suggest that corresponding cortical-striatal-thalamic circuits are involved in periodic discharges with and without motor manifestations, including epileptic spasms, opening new insights in their pathophysiology and new therapeutical perspectives. Based on these findings, we propose a model for the generation of periodic discharges and of epileptic spasms combining existing pathophysiological models of cortical-striatal-thalamic network dynamics.
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Affiliation(s)
- Monika Eisermann
- Correspondence to: Monika Eisermann Clinical Neurophysiology, Hôpital Necker Enfants Malades AP-HP, Paris Université, 149 rue de Sèvres75015 Paris, France E-mail:
| | | | - Ana Saitovitch
- Pediatric Radiology Department, AP-HP, Hôpital Necker Enfants Malades, Université de Paris, F-75015, Paris, France
- Université de Paris, Institut Imagine INSERM U1163, F-75015, France
- INSERM U1299 Trajectoires développementales & psychiatrie, Paris, France
| | - Jennifer Boisgontier
- Pediatric Radiology Department, AP-HP, Hôpital Necker Enfants Malades, Université de Paris, F-75015, Paris, France
- Université de Paris, Institut Imagine INSERM U1163, F-75015, France
- INSERM U1299 Trajectoires développementales & psychiatrie, Paris, France
| | - Alice Vinçon-Leite
- Pediatric Radiology Department, AP-HP, Hôpital Necker Enfants Malades, Université de Paris, F-75015, Paris, France
- Université de Paris, Institut Imagine INSERM U1163, F-75015, France
- INSERM U1299 Trajectoires développementales & psychiatrie, Paris, France
| | - Volodia Dangouloff-Ros
- Pediatric Radiology Department, AP-HP, Hôpital Necker Enfants Malades, Université de Paris, F-75015, Paris, France
- Université de Paris, Institut Imagine INSERM U1163, F-75015, France
- INSERM U1299 Trajectoires développementales & psychiatrie, Paris, France
| | - Thomas Blauwblomme
- Pediatric Neurosurgery, Hôpital Necker, APHP, Paris France, Université de Paris, Paris, France, INSERM U1163, IHU Imagine, Paris, France
| | - Marie Bourgeois
- Pediatric Neurosurgery, Hôpital Necker, APHP, Paris France, Université de Paris, Paris, France, INSERM U1163, IHU Imagine, Paris, France
| | - Marie-Thérèse Dangles
- Clinical Neurophysiology, Hôpital Necker Enfants Malades, AP-HP, Paris Université, Paris, France
| | - Delphine Coste-Zeitoun
- Clinical Neurophysiology, Hôpital Necker Enfants Malades, AP-HP, Paris Université, Paris, France
| | - Patricia Vignolo-Diard
- Clinical Neurophysiology, Hôpital Necker Enfants Malades, AP-HP, Paris Université, Paris, France
| | - Mélodie Aubart
- Pediatric Neurology Department, Hôpital Necker Enfants Malades, AP-HP, INSERM U1163, Paris Université, Institut Imagine, Paris, France
| | - Manoelle Kossorotoff
- Pediatric Neurology Department, Necker Enfants Malades Hospital, AP-HP, Paris Université, Paris, France
| | - Marie Hully
- Pediatric Neurology Department, Necker Enfants Malades Hospital, AP-HP, Paris Université, Paris, France
| | - Emma Losito
- Clinical Neurophysiology, Hôpital Necker Enfants Malades, AP-HP, Paris Université, Paris, France
| | - Nicole Chemaly
- Reference Center for Rare Epilepsies, Department of Pediatric Neurology, Member of EPICARE Network, Institute Imagine INSERM 1163, Université de Paris, Paris, France
| | - Monica Zilbovicius
- Pediatric Radiology Department, AP-HP, Hôpital Necker Enfants Malades, Université de Paris, F-75015, Paris, France
- Université de Paris, Institut Imagine INSERM U1163, F-75015, France
- INSERM U1299 Trajectoires développementales & psychiatrie, Paris, France
| | - Isabelle Desguerre
- Pediatric Neurology Department, Hôpital Necker Enfants Malades, AP-HP, INSERM U1163, Paris Université, Institut Imagine, Paris, France
| | - Rima Nabbout
- Reference Center for Rare Epilepsies, Department of Pediatric Neurology, Member of EPICARE Network, Institute Imagine INSERM 1163, Université de Paris, Paris, France
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Pouliquen G, Fillon L, Dangouloff-Ros V, Kuchenbuch M, Bar C, Chemaly N, Levy R, Roux CJ, Saitovitch A, Boisgontier J, Nabbout R, Boddaert N. Arterial Spin-Labeling Perfusion Imaging in the Early Stage of Sturge-Weber Syndrome. AJNR Am J Neuroradiol 2022; 43:1516-1522. [PMID: 36137664 PMCID: PMC9575527 DOI: 10.3174/ajnr.a7643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 07/27/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND AND PURPOSE Sturge-Weber syndrome is a rare congenital neuro-oculo-cutaneous disorder. Although the principal mechanism of Sturge-Weber syndrome is characterized by a leptomeningeal vascular malformation, few data regarding perfusion abnormalities of the brain parenchyma are available. Therefore, the aim of this study was to assess the diagnostic performance of arterial spin-labeling perfusion imaging in the early stage of Sturge-Weber syndrome before 1 year of age until 3.5 years of age. We hypothesized that a leptomeningeal vascular malformation has very early hypoperfusion compared with controls with healthy brains. MATERIALS AND METHODS We compared the CBF using arterial spin-labeling perfusion imaging performed at 3T MR imaging in the brain parenchymal regions juxtaposing the leptomeningeal vascular malformation in patients with Sturge-Weber syndrome (n = 16; 3.5 years of age or younger) with the corresponding areas in age-matched controls with healthy brains (n = 58). The analysis was performed following two complementary methods: a whole-brain voxel-based analysis and a visual ROI analysis focused on brain territory of the leptomeningeal vascular malformation. RESULTS Whole-brain voxel-based comparison revealed a significant unilateral decrease in CBF localized in the affected cortices of patients with Sturge-Weber syndrome (P < .001). CBF values within the ROIs in patients with Sturge-Weber syndrome were lower than those in controls (in the whole cohort: median, 25 mL/100g/min, versus 44 mL/100g/min; P < .001). This finding was also observed in the group younger than 1 year of age, emphasizing the high sensitivity of arterial spin-labeling in this age window in which the diagnosis is difficult. CONCLUSIONS Arterial spin-labeling perfusion imaging in the early stage of Sturge-Weber syndrome can help to diagnose the disease by depicting a cortical hypoperfusion juxtaposing the leptomeningeal vascular malformation.
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Affiliation(s)
- G Pouliquen
- From the Department of Pediatric Radiology (G.P., V.D.-R., R.L., C.-J.R., N.B.)
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - L Fillon
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - V Dangouloff-Ros
- From the Department of Pediatric Radiology (G.P., V.D.-R., R.L., C.-J.R., N.B.)
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - M Kuchenbuch
- Centre de Reference Epilepsies Rares (M.K., C.B., N.C., R.N.), Department of Pediatric Neurology, Necker Children's Hospital, Assistance Publique-Hôpitaux de Paris, Université de Paris, Paris, France
| | - C Bar
- Centre de Reference Epilepsies Rares (M.K., C.B., N.C., R.N.), Department of Pediatric Neurology, Necker Children's Hospital, Assistance Publique-Hôpitaux de Paris, Université de Paris, Paris, France
| | - N Chemaly
- Centre de Reference Epilepsies Rares (M.K., C.B., N.C., R.N.), Department of Pediatric Neurology, Necker Children's Hospital, Assistance Publique-Hôpitaux de Paris, Université de Paris, Paris, France
| | - R Levy
- From the Department of Pediatric Radiology (G.P., V.D.-R., R.L., C.-J.R., N.B.)
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - C-J Roux
- From the Department of Pediatric Radiology (G.P., V.D.-R., R.L., C.-J.R., N.B.)
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - A Saitovitch
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - J Boisgontier
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
| | - R Nabbout
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
- Centre de Reference Epilepsies Rares (M.K., C.B., N.C., R.N.), Department of Pediatric Neurology, Necker Children's Hospital, Assistance Publique-Hôpitaux de Paris, Université de Paris, Paris, France
| | - N Boddaert
- From the Department of Pediatric Radiology (G.P., V.D.-R., R.L., C.-J.R., N.B.)
- Imagine Institute for Genetic Diseases (G.P., L.F., V.D.-R., R.L., C.-J.R., A.S., J.B., R.N., N.B.), L'Institut National de la Santé et de la Recherche Médicale U1163, Paris, France
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Zhao L, Asis-Cruz JD, Feng X, Wu Y, Kapse K, Largent A, Quistorff J, Lopez C, Wu D, Qing K, Meyer C, Limperopoulos C. Automated 3D Fetal Brain Segmentation Using an Optimized Deep Learning Approach. AJNR Am J Neuroradiol 2022; 43:448-454. [PMID: 35177547 PMCID: PMC8910820 DOI: 10.3174/ajnr.a7419] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 12/06/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND AND PURPOSE MR imaging provides critical information about fetal brain growth and development. Currently, morphologic analysis primarily relies on manual segmentation, which is time-intensive and has limited repeatability. This work aimed to develop a deep learning-based automatic fetal brain segmentation method that provides improved accuracy and robustness compared with atlas-based methods. MATERIALS AND METHODS A total of 106 fetal MR imaging studies were acquired prospectively from fetuses between 23 and 39 weeks of gestation. We trained a deep learning model on the MR imaging scans of 65 healthy fetuses and compared its performance with a 4D atlas-based segmentation method using the Wilcoxon signed-rank test. The trained model was also evaluated on data from 41 fetuses diagnosed with congenital heart disease. RESULTS The proposed method showed high consistency with the manual segmentation, with an average Dice score of 0.897. It also demonstrated significantly improved performance (P < .001) based on the Dice score and 95% Hausdorff distance in all brain regions compared with the atlas-based method. The performance of the proposed method was consistent across gestational ages. The segmentations of the brains of fetuses with high-risk congenital heart disease were also highly consistent with the manual segmentation, though the Dice score was 7% lower than that of healthy fetuses. CONCLUSIONS The proposed deep learning method provides an efficient and reliable approach for fetal brain segmentation, which outperformed segmentation based on a 4D atlas and has been used in clinical and research settings.
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Affiliation(s)
- L Zhao
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
- Department of Biomedical Engineering (L.Z., D.W.), Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, China
| | - J D Asis-Cruz
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - X Feng
- Department of Biomedical Engineering (X.F., C.M.), University of Virginia, Charlottesville, Virginia
| | - Y Wu
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - K Kapse
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - A Largent
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - J Quistorff
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - C Lopez
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
| | - D Wu
- Department of Biomedical Engineering (L.Z., D.W.), Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, China
| | - K Qing
- Department of Radiation Oncology (K.Q.), City of Hope National Center, Duarte, California
| | - C Meyer
- Department of Biomedical Engineering (X.F., C.M.), University of Virginia, Charlottesville, Virginia
| | - C Limperopoulos
- From the Department of Diagnostic Imaging and Radiology (L.Z., J.D.A.-C., Y.W., K.K., A.L., J.Q., C. Lopez, C. Limperopoulos), Developing Brain Institute, Children's National, Washington, DC
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Korom M, Camacho MC, Filippi CA, Licandro R, Moore LA, Dufford A, Zöllei L, Graham AM, Spann M, Howell B, Shultz S, Scheinost D. Dear reviewers: Responses to common reviewer critiques about infant neuroimaging studies. Dev Cogn Neurosci 2021; 53:101055. [PMID: 34974250 PMCID: PMC8733260 DOI: 10.1016/j.dcn.2021.101055] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/28/2021] [Accepted: 12/26/2021] [Indexed: 01/07/2023] Open
Abstract
The field of adult neuroimaging relies on well-established principles in research design, imaging sequences, processing pipelines, as well as safety and data collection protocols. The field of infant magnetic resonance imaging, by comparison, is a young field with tremendous scientific potential but continuously evolving standards. The present article aims to initiate a constructive dialog between researchers who grapple with the challenges and inherent limitations of a nascent field and reviewers who evaluate their work. We address 20 questions that researchers commonly receive from research ethics boards, grant, and manuscript reviewers related to infant neuroimaging data collection, safety protocols, study planning, imaging sequences, decisions related to software and hardware, and data processing and sharing, while acknowledging both the accomplishments of the field and areas of much needed future advancements. This article reflects the cumulative knowledge of experts in the FIT’NG community and can act as a resource for both researchers and reviewers alike seeking a deeper understanding of the standards and tradeoffs involved in infant neuroimaging. The field of infant MRI is young with evolving standards. We address 20 questions that researchers commonly receive reviewers. These come from research ethics boards, grant, and manuscript reviewers. This article reflects the cumulative knowledge of experts in the FIT’NG community.
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Affiliation(s)
- Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA.
| | - M Catalina Camacho
- Division of Biology and Biomedical Sciences (Neurosciences), Washington University School of Medicine, St. Louis, MO, USA.
| | - Courtney A Filippi
- Emotion and Development Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Roxane Licandro
- Institute of Visual Computing and Human-Centered Technology, Computer Vision Lab, TU Wien, Vienna, Austria; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research, Medical University of Vienna, Vienna, Austria
| | - Lucille A Moore
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Alexander Dufford
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Lilla Zöllei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Alice M Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Marisa Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at Virginia Tech Carilion, Department of Human Development and Family Science, Virginia Polytechnic Institute and State University, Roanoke, VA, USA
| | | | - Sarah Shultz
- Division of Autism & Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA; Marcus Autism Center, Children's Healthcare of Atlanta, Atlanta, GA, USA.
| | - Dustin Scheinost
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
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Spencer APC, Byrne H, Lee-Kelland R, Jary S, Thoresen M, Cowan FM, Chakkarapani E, Brooks JCW. An Age-Specific Atlas for Delineation of White Matter Pathways in Children Aged 6-8 Years. Brain Connect 2021; 12:402-416. [PMID: 34210166 PMCID: PMC7612846 DOI: 10.1089/brain.2021.0058] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction Diffusion MRI allows non-invasive assessment of white matter connectivity in typical development and of changes due to brain injury or pathology. Probabilistic white matter atlases allow diffusion metrics to be measured in specific white matter pathways, and are a critical component in spatial normalisation for group analysis. However, given the known developmental changes in white matter it may be sub-optimal to use an adult template when assessing data acquired from children. Methods By averaging subject-specific fibre bundles from 28 children aged from 6 to 8 years, we created an age-specific probabilistic white matter atlas for 12 major white matter tracts. Using both the newly developed and Johns Hopkins adult atlases, we compared the atlas to subject-specific fibre bundles in two independent validation cohorts, assessing accuracy in terms of volumetric overlap and measured diffusion metrics. Results Our age-specific atlas gave better overall performance than the adult atlas, achieving higher volumetric overlap with subject-specific fibre tracking and higher correlation of FA measurements with those measured from subject-specific fibre bundles. Specifically, estimates of FA values for cortico-spinal tract, uncinate fasciculus, forceps minor, cingulate gyrus part of the cingulum and anterior thalamic radiation were all significantly more accurate when estimated with an age-specific atlas. Discussion The age-specific atlas allows delineation of white matter tracts in children aged 6-8 years, without the need for tractography, more accurately than when normalising to an adult atlas. To our knowledge, this is the first publicly available probabilistic atlas of white matter tracts for this age group.
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Affiliation(s)
- Arthur P C Spencer
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom.,Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Hollie Byrne
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom
| | - Richard Lee-Kelland
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sally Jary
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Marianne Thoresen
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,Faculty of Medicine, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
| | - Frances M Cowan
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,Department of Paediatrics, Imperial College London, London, United Kingdom
| | - Ela Chakkarapani
- Translational Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jonathan C W Brooks
- Clinical Research and Imaging Centre, University of Bristol, Bristol, United Kingdom.,School of Psychology, University of East Anglia, Norwich, United Kingdom
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7
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Razavi F, Raminfard S, Kalantar Hormozi H, Sisakhti M, Batouli SAH. A Probabilistic Atlas of the Pineal Gland in the Standard Space. Front Neuroinform 2021; 15:554229. [PMID: 34079447 PMCID: PMC8165226 DOI: 10.3389/fninf.2021.554229] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 04/20/2021] [Indexed: 12/15/2022] Open
Abstract
Pineal gland (PG) is a structure located in the midline of the brain, and is considered as a main part of the epithalamus. There are numerous reports on the facilitatory role of this area for brain function; hormone secretion and its role in sleep cycle are the major reports. However, reports are rarely available on the direct role of this structure in brain cognition and in information processing. A suggestion for the limited number of such studies is the lack of a standard atlas for the PG; none of the available MRI templates and atlases has provided parcellations for this structure. In this study, we used the three-dimensional (3D) T1-weighted MRI data of 152 healthy young volunteers, and provided a probabilistic map of the PG in the standard Montreal Neurologic Institute (MNI) space. The methods included collecting the data using a 64-channel head coil on a 3-Tesla Prisma MRI Scanner, manual delineation of the PG by two experts, and robust template and atlas construction algorithms. This atlas is freely accessible, and we hope importing this atlas in the well-known neuroimaging software packages would help to identify other probable roles of the PG in brain function. It could also be used to study pineal cysts, for volumetric analyses, and to test any associations between the cognitive abilities of the human and the structure of the PG.
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Affiliation(s)
- Foroogh Razavi
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Samira Raminfard
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Hadis Kalantar Hormozi
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Minoo Sisakhti
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.,Department of Cognitive Psychology, Institute for Cognitive Sciences Studies, Tehran, Iran
| | - Seyed Amir Hossein Batouli
- Neuroimaging and Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran.,Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
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8
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Serlin Y, Ben-Arie G, Lublinsky S, Flusser H, Friedman A, Shelef I. Distorted Optic Nerve Portends Neurological Complications in Infants With External Hydrocephalus. Front Neurol 2021; 12:596294. [PMID: 33597915 PMCID: PMC7882497 DOI: 10.3389/fneur.2021.596294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 01/08/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Benign external hydrocephalus (BEH) is defined by rapid increase in head circumference in infancy, with neuroimaging evidence of enlarged cerebrospinal fluid (CSF) spaces. BEH was postulated to predispose to subdural hematoma, neurocognitive impairments, and autism. There is currently no consensus on BEH diagnostic criteria and no biomarkers to predict neurological sequalae. Methods: MRI-based quantitative approach was used for measurement of potential imaging markers related to external hydrocephalus and their association with neurological outcomes. We scanned 23 infants diagnosed with BEH and 11 age-similar controls. Using anatomical measurements from a large sample of healthy infants (n = 150), Z-scores were calculated to classify subject's CSF spaces as enlarged (≥1.96SD of mean values) or normal. Results: Subjects with abnormally enlarged CSF spaces had a significantly wider and longer ON (p = 0.017 and p = 0.020, respectively), and a significantly less tortuous ON (p = 0.006). ON deformity demonstrated a high diagnostic accuracy for abnormally enlarged frontal subarachnoid space (AUC = 0.826) and interhemispheric fissure (AUC = 0.833). No significant association found between enlarged CSF spaces and neurological complications (OR = 0.330, 95%CI 0.070-1.553, p = 0.161). However, cluster analysis identified a distinct subgroup of children (23/34, 67.6%) with enlarged CSF spaces and a wider, longer and less tortuous ON, to have an increased risk for neurological complications (RR = 7.28, 95%CI 1.07-49.40). Discussion: This is the first report on the association between external hydrocephalus, ON deformity and neurological complications. Our findings challenge the current view of external hydrocephalus as a benign condition. ON deformity is a potential auxiliary marker for risk stratification in patients with enlarged CSF spaces.
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Affiliation(s)
- Yonatan Serlin
- Neurology Residency Training Program, McGill University, Montreal, QC, Canada
| | - Gal Ben-Arie
- Department of Medical Imaging, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Svetlana Lublinsky
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Hagit Flusser
- Zussman Child Development Center, Division of Pediatrics, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Alon Friedman
- Departments of Physiology and Cell Biology, Brain and Cognitive Sciences, Zlotowski Center for Neuroscience, Ben-Gurion University of the Negev, Be'er Sheva, Israel.,Department of Medical Neuroscience, Brain Repair Center, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Ilan Shelef
- Department of Medical Imaging, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
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9
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Turesky TK, Vanderauwera J, Gaab N. Imaging the rapidly developing brain: Current challenges for MRI studies in the first five years of life. Dev Cogn Neurosci 2021; 47:100893. [PMID: 33341534 PMCID: PMC7750693 DOI: 10.1016/j.dcn.2020.100893] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 10/21/2020] [Accepted: 12/05/2020] [Indexed: 12/20/2022] Open
Abstract
Rapid and widespread changes in brain anatomy and physiology in the first five years of life present substantial challenges for developmental structural, functional, and diffusion MRI studies. One persistent challenge is that methods best suited to earlier developmental stages are suboptimal for later stages, which engenders a trade-off between using different, but age-appropriate, methods for different developmental stages or identical methods across stages. Both options have potential benefits, but also biases, as pipelines for each developmental stage can be matched on methods or the age-appropriateness of methods, but not both. This review describes the data acquisition, processing, and analysis challenges that introduce these potential biases and attempts to elucidate decisions and make recommendations that would optimize developmental comparisons.
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Affiliation(s)
- Ted K Turesky
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Jolijn Vanderauwera
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Psychological Sciences Research Institute, Université Catholique De Louvain, Louvain-la-Neuve, Belgium; Institute of Neuroscience, Université Catholique De Louvain, Louvain-la-Neuve, Belgium
| | - Nadine Gaab
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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10
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François C, Garcia-Alix A, Bosch L, Rodriguez-Fornells A. Signatures of brain plasticity supporting language recovery after perinatal arterial ischemic stroke. BRAIN AND LANGUAGE 2021; 212:104880. [PMID: 33220646 DOI: 10.1016/j.bandl.2020.104880] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Revised: 09/11/2020] [Accepted: 10/11/2020] [Indexed: 06/11/2023]
Abstract
Brain imaging methods such as functional Magnetic Resonance Imaging (fMRI) and Diffusion Tensor Imaging (DTI) have already been used to decipher the functional and structural brain changes occurring during normal language development. However, little is known about the differentiation of the language network after an early lesion. While in adults, stroke over the left hemisphere generally induces post-stroke aphasia, it is not always the case when a stroke occurs in the perinatal period, thus revealing a remarkable plastic power of the language network during early development. In particular, the role of perilesional tissues, as opposed to undamaged brain areas in the functional recovery of language functions after an early insult, remains unclear. In this review article, we provide an overview of the extant literature using functional and structural neuroimaging data revealing the signatures of brain plasticity underlying near-normal language development.
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Affiliation(s)
| | - Alfredo Garcia-Alix
- Service of Genetic and Molecular Medicine, Hospital Sant Joan de Déu, Barcelona, Spain; Institut de Recerca Sant Joan de Déu, Barcelona, Spain; NeNe Foundation, Madrid, Spain
| | - Laura Bosch
- Institut de Recerca Sant Joan de Déu, Barcelona, Spain; Department of Cognition, Development and Educational Psychology, University of Barcelona, Barcelona, Spain; Institute of Neurosciences (UBNeuro), University of Barcelona, Barcelona, Spain
| | - Antoni Rodriguez-Fornells
- Cognition and Brain Plasticity Group, IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain; Catalan Institution for Research and Advanced Studies, ICREA, Barcelona, Spain
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11
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Arterial spin labeling brain MRI study to evaluate the impact of deafness on cerebral perfusion in 79 children before cochlear implantation. NEUROIMAGE-CLINICAL 2020; 29:102510. [PMID: 33369563 PMCID: PMC7777537 DOI: 10.1016/j.nicl.2020.102510] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 11/06/2020] [Accepted: 11/16/2020] [Indexed: 01/06/2023]
Abstract
Arterial spin labeling brain MRI measure deafness impact on cerebral perfusion. Deafness in childhood modifies the temporal perfusion evolution across age. Cochlear implant pronostics is bad in case of high CBF values in occipital regions. Cochlear implantation before 4 years old is required.
Age at implantation is considered to be a major factor, influencing outcomes after pediatric cochlear implantation. In the absence of acoustic input, it has been proposed that cross-modal reorganization can be detrimental for adaptation to the new electrical input provided by a cochlear implant. Here, through a retrospective study, we aimed to investigate differences in cerebral blood flow (CBF) at rest prior to implantation in children with congenital deafness compared to normally hearing children. In addition, we looked at the putative link between pre-operative rest-CBF and the oral intelligibility scores at 12 months post-implantation. Finally, we observed the evolution of perfusion with age, within brain areas showing abnormal rest-CBF associated to deafness, in deaf children and in normally hearing children. In children older than 5 years old, results showed a significant bilateral hypoperfusion in temporal regions in deaf children, particularly in Heschl’s gyrus, and a significant hyperperfusion of occipital regions. Furthermore, in children older than 5 years old, whole brain voxel-by-voxel correlation analysis between pre-operative rest-CBF and oral intelligibility scores at 12 months post-implantation, showed significant negative correlation localized in the occipital regions: children who performed worse in the speech perception test one year after implantation were those presenting higher preoperative CBF values in these occipital regions. Finally, when comparing mean relative perfusion (extracted from the temporal regions found abnormal on whole-brain voxel-based analysis) across ages in patients and controls, we observed that the temporal perfusion evolution was significantly different in deaf children than in normally hearing children. Indeed, while temporal perfusion increased with age in normally hearing children, it remained stable in deaf children. We showed a critical period around 4 years old, where in the context of auditory deprivation, there is a lack of synaptic activity in auditory regions. These results support the benefits of early cochlear implantation to maximize the effectiveness of auditory rehabilitation and to avoid cross-modal reorganization.
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12
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Haynes L, Ip A, Cho IYK, Dimond D, Rohr CS, Bagshawe M, Dewey D, Lebel C, Bray S. Grey and white matter volumes in early childhood: A comparison of voxel-based morphometry pipelines. Dev Cogn Neurosci 2020; 46:100875. [PMID: 33166899 PMCID: PMC7652784 DOI: 10.1016/j.dcn.2020.100875] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/10/2020] [Accepted: 10/21/2020] [Indexed: 10/30/2022] Open
Abstract
Early childhood is an important period of sensory, motor, cognitive and socio-emotional maturation, yet relatively little is known about the brain changes specific to this period. Voxel-based morphometry (VBM) is a technique to estimate regional brain volumes from magnetic resonance (MR) images. The default VBM processing pipeline can be customized to increase accuracy of segmentation and normalization, yet the impact of customizations on analyses in young children are not clear. Here, we assessed the impact of different preprocessing steps on T1-weighted MR images from typically developing children in two separate cohorts. Data were processed with the Computational Anatomy Toolbox (CAT12), using seven different VBM pipelines with distinct combinations of tissue probability maps (TPMs) and DARTEL templates created using the Template-O-Matic, and CerebroMatic. The first cohort comprised female children aged 3.9-7.9 years (N = 62) and the second included boys and girls aged 2.7-8 years (N = 74). We found that pipelines differed significantly in their tendency to classify voxels as grey or white matter and the conclusions about some age effects were pipeline-dependent. Our study helps to both understand age-associations in grey and white matter volume across early childhood and elucidate the impact of VBM customization on brain volumes in this age range.
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Affiliation(s)
- Logan Haynes
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Amanda Ip
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Ivy Y K Cho
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Dennis Dimond
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Christiane S Rohr
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Mercedes Bagshawe
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada
| | - Deborah Dewey
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Paediatrics, Cumming School of Medicine, University of Calgary, Calgary, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Canada; Owerko Centre, University of Calgary, Calgary, Canada
| | - Catherine Lebel
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Signe Bray
- Child and Adolescent Imaging Research Program, University of Calgary, Calgary, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, Canada; Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.
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13
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Functional connectivity alterations associated with literacy difficulties in early readers. Brain Imaging Behav 2020; 15:2109-2120. [PMID: 33048291 DOI: 10.1007/s11682-020-00406-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2020] [Indexed: 10/23/2022]
Abstract
The link between literacy difficulties and brain alterations has been described in depth. Resting-state fMRI (rs-fMRI) has been successfully applied to the study of intrinsic functional connectivity (iFc) both in dyslexia and typically developing children. Most related studies have focused on the stages from late childhood into adulthood using a seed to voxel approach. Our study analyzes iFc in an early childhood sample using the multivariate pattern analysis. This facilitates a hypothesis-free analysis and the possible identification of abnormal functional connectivity patterns at a whole brain level. Thirty-four children with literacy difficulties (LD) (7.1 ± 0.69 yr.) and 30 typically developing children (TD) (7.43 ± 0.52 yr.) were selected. Functional brain connectivity was measured using an rs-fMRI acquisition. The LD group showed a higher iFc between the right middle frontal gyrus (rMFG) and the default mode network (DMN) regions, and a lower iFc between the rMFG and both the bilateral insular cortex and the supramarginal gyrus. These results are interpreted as a DMN on/off routine malfunction in the LD group, which suggests an alteration of the task control network regulating DMN activity. In the LD group, the posterior cingulate cortex also showed a lower iFc with both the middle temporal poles and the fusiform gyrus. This could be interpreted as a failure in the integration of information between brain regions that facilitate reading. Our results show that children with literacy difficulties have an altered functional connectivity in their reading and attentional networks at the beginning of the literacy acquisition. Future studies should evaluate whether or not these alterations could indicate a risk of developing dyslexia.
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14
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Pai PP, Mandal PK, Punjabi K, Shukla D, Goel A, Joon S, Roy S, Sandal K, Mishra R, Lahoti R. BRAHMA: Population specific T1, T2, and FLAIR weighted brain templates and their impact in structural and functional imaging studies. Magn Reson Imaging 2020; 70:5-21. [PMID: 31917995 DOI: 10.1016/j.mri.2019.12.009] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 11/18/2019] [Accepted: 12/30/2019] [Indexed: 02/06/2023]
Abstract
Differences in brain morphology across population groups necessitate creation of population-specific Magnetic Resonance Imaging (MRI) brain templates for interpretation of neuroimaging data. Variations in the neuroanatomy in a genetically heterogeneous population make the development of a population-specific brain template for the Indian subcontinent imperative. A dataset of high-resolution 3D T1, T2-weighted, and FLAIR images acquired from a group of 113 volunteers (M/F - 56/57, mean age-28.96 ± 7.80 years) are used to construct T1, T2-weighted, and FLAIR templates, collectively referred to as Indian Brain Template, "BRAHMA". A processing pipeline is developed and implemented in a MATLAB based toolbox for template construction and generation of tissue probability maps and segmentation atlases, with additional labels for deep brain regions such as the Substantia Nigra generated from the T2-weighted and FLAIR templates. The use of BRAHMA template for analysis of structural and functional neuroimaging data obtained from Indian participants, provides improved accuracy with statistically significant results over that obtained using the ICBM-152 (International Consortium for Brain Mapping) template. Our results indicate that segmentations generated on structural images are closer in volume to those obtained from registration to the BRAHMA template than to the ICBM-152. Furthermore, functional MRI data obtained for Working Memory and Finger Tapping paradigms processed using the BRAHMA template show a significantly higher percentage of the activation area than ICBM-152 in relevant brain regions, i.e. the left middle frontal gyrus, and the left and right precentral gyri, respectively. The availability of different image contrasts, tissue maps, and segmentation atlases makes the BRAHMA template a comprehensive tool for multi-modal image analysis in laboratory and clinical settings.
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Affiliation(s)
- Praful P Pai
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Pravat K Mandal
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India; Florey Institute of Neuroscience and Mental Health, Melbourne School of Medicine, Melbourne, Victoria, Australia.
| | - Khushboo Punjabi
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Deepika Shukla
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Anshika Goel
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Shallu Joon
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Saurav Roy
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Kanika Sandal
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Ritwick Mishra
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
| | - Ritu Lahoti
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, Haryana, India
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15
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Serai SD, Dudley J, Leach JL. Comparison of whole brain segmentation and volume estimation in children and young adults using SPM and SyMRI. Clin Imaging 2019; 57:77-82. [DOI: 10.1016/j.clinimag.2019.05.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 05/03/2019] [Accepted: 05/17/2019] [Indexed: 11/29/2022]
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16
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Farah R, Horowitz-Kraus T. Increased Functional Connectivity Within and Between Cognitive-Control Networks from Early Infancy to Nine Years During Story Listening. Brain Connect 2019; 9:285-295. [PMID: 30777454 DOI: 10.1089/brain.2018.0625] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The cingulo-opercular (CO) and frontoparietal (FP) networks are part of the cognitive-control system of the brain. Evidence suggests that over the course of development, brain regions supporting cognitive-control functions become more integrated within their networks (i.e., have increased within-network connectivity), more separated from other networks, and, due to increased maturation along development, are more functionally connected between the networks. The focus of this study was to characterize the developmental trajectory of the CO and FP networks from early infancy (17 months) to 9 years of age in typically developing children while listening to stories, using functional connectivity analyses. Seventy-four children underwent a functional magnetic resonance imaging session while listening to stories inside the scanner. Within- and between-network functional connectivity and graph theory measures were compared during development. Developmental increase in functional connectivity within the CO network and between the CO and FP networks, as well as global efficiency of the CO network from 17 months to 9 years of age, was observed. These findings highlight the involvement of the CO and FP networks in story listening from early infancy, which increases along development. Future studies examining failures in language acquisition to further explore the role of these networks in story listening are warranted.
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Affiliation(s)
- Rola Farah
- 1 Faculty of Biomedical Engineering, Educational Neuroimaging Center, Technion, Haifa, Israel.,2 Faculty of Education in Science and Technology, Educational Neuroimaging Center, Technion, Haifa, Israel
| | - Tzipi Horowitz-Kraus
- 1 Faculty of Biomedical Engineering, Educational Neuroimaging Center, Technion, Haifa, Israel.,3 Division of General and Community Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
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17
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Zhang H, Shen D, Lin W. Resting-state functional MRI studies on infant brains: A decade of gap-filling efforts. Neuroimage 2019; 185:664-684. [PMID: 29990581 PMCID: PMC6289773 DOI: 10.1016/j.neuroimage.2018.07.004] [Citation(s) in RCA: 68] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 05/19/2018] [Accepted: 07/02/2018] [Indexed: 12/16/2022] Open
Abstract
Resting-state functional MRI (rs-fMRI) is one of the most prevalent brain functional imaging modalities. Previous rs-fMRI studies have mainly focused on adults and elderly subjects. Recently, infant rs-fMRI studies have become an area of active research. After a decade of gap filling studies, many facets of the brain functional development from early infancy to toddler has been uncovered. However, infant rs-fMRI is still in its infancy. The image analysis tools for neonates and young infants can be quite different from those for adults. From data analysis to result interpretation, more questions and issues have been raised, and new hypotheses have been formed. With the anticipated availability of unprecedented high-resolution rs-fMRI and dedicated analysis pipelines from the Baby Connectome Project (BCP), it is important now to revisit previous findings and hypotheses, discuss and comment existing issues and problems, and make a "to-do-list" for the future studies. This review article aims to comprehensively review a decade of the findings, unveiling hidden jewels of the fields of developmental neuroscience and neuroimage computing. Emphases will be given to early infancy, particularly the first few years of life. In this review, an end-to-end summary, from infant rs-fMRI experimental design to data processing, and from the development of individual functional systems to large-scale brain functional networks, is provided. A comprehensive summary of the rs-fMRI findings in developmental patterns is highlighted. Furthermore, an extensive summary of the neurodevelopmental disorders and the effects of other hazardous factors is provided. Finally, future research trends focusing on emerging dynamic functional connectivity and state-of-the-art functional connectome analysis are summarized. In next decade, early infant rs-fMRI and developmental connectome study could be one of the shining research topics.
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Affiliation(s)
- Han Zhang
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA
| | - Dinggang Shen
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul, 02841, Republic of Korea.
| | - Weili Lin
- Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, NC, 27599, USA.
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18
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Feng L, Li H, Oishi K, Mishra V, Song L, Peng Q, Ouyang M, Wang J, Slinger M, Jeon T, Lee L, Heyne R, Chalak L, Peng Y, Liu S, Huang H. Age-specific gray and white matter DTI atlas for human brain at 33, 36 and 39 postmenstrual weeks. Neuroimage 2019; 185:685-698. [PMID: 29959046 PMCID: PMC6289605 DOI: 10.1016/j.neuroimage.2018.06.069] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 05/21/2018] [Accepted: 06/25/2018] [Indexed: 01/24/2023] Open
Abstract
During the 3rd trimester, dramatic structural changes take place in the human brain, underlying the neural circuit formation. The survival rate of premature infants has increased significantly in recent years. The large morphological differences of the preterm brain at 33 or 36 postmenstrual weeks (PMW) from the brain at 40PMW (full term) make it necessary to establish age-specific atlases for preterm brains. In this study, with high quality (1.5 × 1.5 × 1.6 mm3 imaging resolution) diffusion tensor imaging (DTI) data obtained from 84 healthy preterm and term-born neonates, we established age-specific preterm and term-born brain templates and atlases at 33, 36 and 39PMW. Age-specific DTI templates include a single-subject template, a population-averaged template with linear transformation and a population-averaged template with nonlinear transformation. Each of the age-specific DTI atlases includes comprehensive labeling of 126 major gray matter (GM) and white matter (WM) structures, specifically 52 cerebral cortical structures, 40 cerebral WM structures, 22 brainstem and cerebellar structures and 12 subcortical GM structures. From 33 to 39 PMW, dramatic morphological changes of delineated individual neural structures such as ganglionic eminence and uncinate fasciculus were revealed. The evaluation based on measurements of Dice ratio and L1 error suggested reliable and reproducible automated labels from the age-matched atlases compared to labels from manual delineation. Applying these atlases to automatically and effectively delineate microstructural changes of major WM tracts during the 3rd trimester was demonstrated. The established age-specific DTI templates and atlases of 33, 36 and 39 PMW brains may be used for not only understanding normal functional and structural maturational processes but also detecting biomarkers of neural disorders in the preterm brains.
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Affiliation(s)
- Lei Feng
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Hang Li
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Department of Radiology, Beijing Children's Hospital Affiliated to Capital Medical University, National Center for Children's Health, Beijing, China
| | - Kenichi Oishi
- Department of Radiology, Johns Hopkins University, MD, USA
| | - Virendra Mishra
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, USA
| | - Limei Song
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Qinmu Peng
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, USA
| | - Jiaojian Wang
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Michelle Slinger
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA
| | - Tina Jeon
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA
| | - Lizette Lee
- Department of Pediatrics, University of Texas Southwestern Medical Center, TX, USA
| | - Roy Heyne
- Department of Pediatrics, University of Texas Southwestern Medical Center, TX, USA
| | - Lina Chalak
- Department of Pediatrics, University of Texas Southwestern Medical Center, TX, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital Affiliated to Capital Medical University, National Center for Children's Health, Beijing, China
| | - Shuwei Liu
- Research Center for Sectional and Imaging Anatomy, Shandong University Cheeloo College of Medicine, Shandong, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, PA, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, TX, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, PA, USA.
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19
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Palande S, Jose V, Zielinski B, Anderson J, Fletcher PT, Wang B. Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference. Brain Connect 2018; 9:13-21. [PMID: 30543119 DOI: 10.1089/brain.2018.0604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A large body of evidence relates autism with abnormal structural and functional brain connectivity. Structural covariance magnetic resonance imaging (scMRI) is a technique that maps brain regions with covarying gray matter densities across subjects. It provides a way to probe the anatomical structure underlying intrinsic connectivity networks (ICNs) through analysis of gray matter signal covariance. In this article, we apply topological data analysis in conjunction with scMRI to explore network-specific differences in the gray matter structure in subjects with autism versus age-, gender-, and IQ-matched controls. Specifically, we investigate topological differences in gray matter structure captured by structural correlation graphs derived from three ICNs strongly implicated in autism, namely the salience network, default mode network, and executive control network. By combining topological data analysis with statistical inference, our results provide evidence of statistically significant network-specific structural abnormalities in autism.
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Affiliation(s)
- Sourabh Palande
- 1 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah.,2 School of Computing, University of Utah, Salt Lake City, Utah
| | - Vipin Jose
- 2 School of Computing, University of Utah, Salt Lake City, Utah
| | - Brandon Zielinski
- 3 Department of Pediatrics, University of Utah, Salt Lake City, Utah.,4 Department of Neurology, University of Utah, Salt Lake City, Utah
| | - Jeffrey Anderson
- 5 Department of Radiology, University of Utah, Salt Lake City, Utah
| | - P Thomas Fletcher
- 1 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah.,2 School of Computing, University of Utah, Salt Lake City, Utah
| | - Bei Wang
- 1 Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah.,2 School of Computing, University of Utah, Salt Lake City, Utah
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20
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Boucher MA, Lippé S, Dupont C, Knoth IS, Lopez G, Shams R, El-Jalbout R, Damphousse A, Kadoury S. Computer-aided lateral ventricular and brain volume measurements in 3D ultrasound for assessing growth trajectories in newborns and neonates. ACTA ACUST UNITED AC 2018; 63:225012. [DOI: 10.1088/1361-6560/aaea85] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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21
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Cusack R, McCuaig O, Linke AC. Methodological challenges in the comparison of infant fMRI across age groups. Dev Cogn Neurosci 2018; 33:194-205. [PMID: 29158073 PMCID: PMC6969274 DOI: 10.1016/j.dcn.2017.11.003] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 09/29/2017] [Accepted: 11/07/2017] [Indexed: 01/31/2023] Open
Abstract
Functional MRI (fMRI) in infants is rapidly growing and providing fundamental insights into the origins of brain functions. Comparing brain development at different ages is particularly powerful, but there are a number of methodological challenges that must be addressed if confounds are to be avoided. With development, brains change in composition in a way that alters their tissue contrast, and in size, shape, and gyrification, requiring careful image processing strategies and age-specific standard templates. The hemodynamic response and other aspects of physiology change with age, requiring careful paradigm design and analysis methods. Infants move more, particularly around the second year of age, and move in a different way to adults. This movement can lead to distortion in fMRI images, and requires tailored techniques during acquisition and post-processing. Infants have different sleep patterns, and their sensory periphery is changing macroscopically and in its neural pathways. Finally, once data have been acquired and analyzed, there are important considerations during mapping of brain processes and cognitive functions across age groups. In summary, new methods are critical to the comparison across age groups, and key to maximizing the rate at which infant fMRI can provide insight into the fascinating questions about the origin of cognition.
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Affiliation(s)
- Rhodri Cusack
- Brain and Mind Institute, Western University, Canada; Trinity College, Dublin, Ireland.
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22
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Phan TV, Smeets D, Talcott JB, Vandermosten M. Processing of structural neuroimaging data in young children: Bridging the gap between current practice and state-of-the-art methods. Dev Cogn Neurosci 2018; 33:206-223. [PMID: 29033222 PMCID: PMC6969273 DOI: 10.1016/j.dcn.2017.08.009] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2016] [Revised: 07/28/2017] [Accepted: 08/17/2017] [Indexed: 11/25/2022] Open
Abstract
The structure of the brain is subject to very rapid developmental changes during early childhood. Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the developing brain, toward understanding typical and atypical trajectories. However, it has also been demonstrated that application of currently standard MRI processing methods that have been developed with datasets from adults may not be appropriate for use with pediatric datasets. In this review, we examine the approaches currently used in MRI studies involving young children, including an overview of the rationale for new MRI processing methods that have been designed specifically for pediatric investigations. These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained with longitudinal designs. The overall goal is to raise awareness of the existence of these methods and the possibilities for implementing them in developmental neuroimaging studies.
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Affiliation(s)
- Thanh Vân Phan
- Experimental Oto-rhino-laryngology, Department Neurosciences, KU Leuven, Leuven, Belgium; icometrix, Research and Development, Leuven, Belgium.
| | - Dirk Smeets
- icometrix, Research and Development, Leuven, Belgium
| | - Joel B Talcott
- Aston Brain Centre, School of Life and Health Sciences, Aston University, Birmingham, United Kingdom
| | - Maaike Vandermosten
- Experimental Oto-rhino-laryngology, Department Neurosciences, KU Leuven, Leuven, Belgium
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23
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Phan TV, Sima DM, Beelen C, Vanderauwera J, Smeets D, Vandermosten M. Evaluation of methods for volumetric analysis of pediatric brain data: The child metrix pipeline versus adult-based approaches. NEUROIMAGE-CLINICAL 2018; 19:734-744. [PMID: 30003026 PMCID: PMC6040578 DOI: 10.1016/j.nicl.2018.05.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Revised: 05/04/2018] [Accepted: 05/22/2018] [Indexed: 12/18/2022]
Abstract
Pediatric brain volumetric analysis based on Magnetic Resonance Imaging (MRI) is of particular interest in order to understand the typical brain development and to characterize neurodevelopmental disorders at an early age. However, it has been shown that the results can be biased due to head motion, inherent to pediatric data, and due to the use of methods based on adult brain data that are not able to accurately model the anatomical disparity of pediatric brains. To overcome these issues, we proposed childmetrix, a tool developed for the analysis of pediatric neuroimaging data that uses an age-specific atlas and a probabilistic model-based approach in order to segment the gray matter (GM) and white matter (WM). The tool was extensively validated on 55 scans of children between 5 and 6 years old (including 13 children with developmental dyslexia) and 10 pairs of test-retest scans of children between 6 and 8 years old and compared with two state-of-the-art methods using an adult atlas, namely icobrain (applying a probabilistic model-based segmentation) and Freesurfer (applying a surface model-based segmentation). The results obtained with childmetrix showed a better reproducibility of GM and WM segmentations and a better robustness to head motion in the estimation of GM volume compared to Freesurfer. Evaluated on two subjects, childmetrix showed good accuracy with 82-84% overlap with manual segmentation for both GM and WM, thereby outperforming the adult-based methods (icobrain and Freesurfer), especially for the subject with poor quality data. We also demonstrated that the adult-based methods needed double the number of subjects to detect significant morphological differences between dyslexics and typical readers. Once further developed and validated, we believe that childmetrix would provide appropriate and reliable measures for the examination of children's brain.
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Affiliation(s)
- Thanh Vân Phan
- icometrix, Research and Development, Leuven, Belgium; Experimental Oto-rhino-laryngology, Department Neurosciences, KU Leuven, Leuven, Belgium.
| | - Diana M Sima
- icometrix, Research and Development, Leuven, Belgium
| | - Caroline Beelen
- Parenting and Special Education Research Unit, Faculty of Psychology and Educational Science, KU Leuven, Leuven, Belgium
| | - Jolijn Vanderauwera
- Experimental Oto-rhino-laryngology, Department Neurosciences, KU Leuven, Leuven, Belgium; Parenting and Special Education Research Unit, Faculty of Psychology and Educational Science, KU Leuven, Leuven, Belgium
| | - Dirk Smeets
- icometrix, Research and Development, Leuven, Belgium
| | - Maaike Vandermosten
- Experimental Oto-rhino-laryngology, Department Neurosciences, KU Leuven, Leuven, Belgium
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24
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Bednarz HM, Kana RK. Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 2018; 90:50-69. [PMID: 29608989 DOI: 10.1016/j.neubiorev.2018.03.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 02/26/2018] [Accepted: 03/22/2018] [Indexed: 10/17/2022]
Abstract
Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.
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Affiliation(s)
- Haley M Bednarz
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rajesh K Kana
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
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25
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Computational neuroanatomy of baby brains: A review. Neuroimage 2018; 185:906-925. [PMID: 29574033 DOI: 10.1016/j.neuroimage.2018.03.042] [Citation(s) in RCA: 95] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2017] [Revised: 02/23/2018] [Accepted: 03/19/2018] [Indexed: 12/12/2022] Open
Abstract
The first postnatal years are an exceptionally dynamic and critical period of structural, functional and connectivity development of the human brain. The increasing availability of non-invasive infant brain MR images provides unprecedented opportunities for accurate and reliable charting of dynamic early brain developmental trajectories in understanding normative and aberrant growth. However, infant brain MR images typically exhibit reduced tissue contrast (especially around 6 months of age), large within-tissue intensity variations, and regionally-heterogeneous, dynamic changes, in comparison with adult brain MR images. Consequently, the existing computational tools developed typically for adult brains are not suitable for infant brain MR image processing. To address these challenges, many infant-tailored computational methods have been proposed for computational neuroanatomy of infant brains. In this review paper, we provide a comprehensive review of the state-of-the-art computational methods for infant brain MRI processing and analysis, which have advanced our understanding of early postnatal brain development. We also summarize publically available infant-dedicated resources, including MRI datasets, computational tools, grand challenges, and brain atlases. Finally, we discuss the limitations in current research and suggest potential future research directions.
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26
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Ellis CT, Turk-Browne NB. Infant fMRI: A Model System for Cognitive Neuroscience. Trends Cogn Sci 2018; 22:375-387. [PMID: 29487030 DOI: 10.1016/j.tics.2018.01.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Revised: 12/31/2017] [Accepted: 01/05/2018] [Indexed: 11/30/2022]
Abstract
Our understanding of the typical human brain has benefitted greatly from studying different kinds of brains and their associated behavioral repertoires, including animal models and neuropsychological patients. This same comparative perspective can be applied to early development - the environment, behavior, and brains of infants provide a model system for understanding how the mature brain works. This approach requires noninvasive methods for measuring brain function in awake, behaving infants. fMRI is becoming increasingly viable for this purpose, with the unique ability to precisely measure the entire brain, including both cortical and subcortical structures. Here we discuss potential lessons from infant fMRI for several domains of adult cognition and consider the challenges of conducting such research and how they might be mitigated.
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Affiliation(s)
- Cameron T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
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27
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fMRI as a Preimplant Objective Tool to Predict Postimplant Oral Language Outcomes in Children with Cochlear Implants. Ear Hear 2018; 37:e263-72. [PMID: 26689275 DOI: 10.1097/aud.0000000000000259] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Despite the positive effects of cochlear implantation, postimplant variability in speech perception and oral language outcomes is still difficult to predict. The aim of this study was to identify neuroimaging biomarkers of postimplant speech perception and oral language performance in children with hearing loss who receive a cochlear implant. The authors hypothesized positive correlations between blood oxygen level-dependent functional magnetic resonance imaging (fMRI) activation in brain regions related to auditory language processing and attention and scores on the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2) and the Early Speech Perception Test for Profoundly Hearing-Impaired Children (ESP), in children with congenital hearing loss. DESIGN Eleven children with congenital hearing loss were recruited for the present study based on referral for clinical MRI and other inclusion criteria. All participants were <24 months at fMRI scanning and <36 months at first implantation. A silent background fMRI acquisition method was performed to acquire fMRI during auditory stimulation. A voxel-based analysis technique was utilized to generate z maps showing significant contrast in brain activation between auditory stimulation conditions (spoken narratives and narrow band noise). CELF-P2 and ESP were administered 2 years after implantation. Because most participants reached a ceiling on ESP, a voxel-wise regression analysis was performed between preimplant fMRI activation and postimplant CELF-P2 scores alone. Age at implantation and preimplant hearing thresholds were controlled in this regression analysis. RESULTS Four brain regions were found to be significantly correlated with CELF-P2 scores. These clusters of positive correlation encompassed the temporo-parieto-occipital junction, areas in the prefrontal cortex and the cingulate gyrus. For the story versus silence contrast, CELF-P2 core language score demonstrated significant positive correlation with activation in the right angular gyrus (r = 0.95), left medial frontal gyrus (r = 0.94), and left cingulate gyrus (r = 0.96). For the narrow band noise versus silence contrast, the CELF-P2 core language score exhibited significant positive correlation with activation in the left angular gyrus (r = 0.89; for all clusters, corrected p < 0.05). CONCLUSIONS Four brain regions related to language function and attention were identified that correlated with CELF-P2. Children with better oral language performance postimplant displayed greater activation in these regions preimplant. The results suggest that despite auditory deprivation, these regions are more receptive to gains in oral language development performance of children with hearing loss who receive early intervention via cochlear implantation. The present study suggests that oral language outcome following cochlear implant may be predicted by preimplant fMRI with auditory stimulation using natural speech.
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28
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A fast stochastic framework for automatic MR brain images segmentation. PLoS One 2017; 12:e0187391. [PMID: 29136034 PMCID: PMC5685492 DOI: 10.1371/journal.pone.0187391] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 10/19/2017] [Indexed: 12/05/2022] Open
Abstract
This paper introduces a new framework for the segmentation of different brain structures (white matter, gray matter, and cerebrospinal fluid) from 3D MR brain images at different life stages. The proposed segmentation framework is based on a shape prior built using a subset of co-aligned training images that is adapted during the segmentation process based on first- and second-order visual appearance characteristics of MR images. These characteristics are described using voxel-wise image intensities and their spatial interaction features. To more accurately model the empirical grey level distribution of the brain signals, we use a linear combination of discrete Gaussians (LCDG) model having positive and negative components. To accurately account for the large inhomogeneity in infant MRIs, a higher-order Markov-Gibbs Random Field (MGRF) spatial interaction model that integrates third- and fourth- order families with a traditional second-order model is proposed. The proposed approach was tested and evaluated on 102 3D MR brain scans using three metrics: the Dice coefficient, the 95-percentile modified Hausdorff distance, and the absolute brain volume difference. Experimental results show better segmentation of MR brain images compared to current open source segmentation tools.
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29
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Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference. ACTA ACUST UNITED AC 2017. [PMID: 30135962 DOI: 10.1007/978-3-319-67159-8_12] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
A large body of evidence relates autism with abnormal structural and functional brain connectivity. Structural covariance MRI (scMRI) is a technique that maps brain regions with covarying gray matter density across subjects. It provides a way to probe the anatomical structures underlying intrinsic connectivity networks (ICNs) through the analysis of the gray matter signal covariance. In this paper, we apply topological data analysis in conjunction with scMRI to explore network-specific differences in the gray matter structure in subjects with autism versus age-, gender- and IQ-matched controls. Specifically, we investigate topological differences in gray matter structures captured by structural covariance networks (SCNs) derived from three ICNs strongly implicated in autism, namely, the salience network (SN), the default mode network (DMN) and the executive control network (ECN). By combining topological data analysis with statistical inference, our results provide evidence of statistically significant network-specific structural abnormalities in autism, from SCNs derived from SN and ECN. These differences in brain architecture are consistent with direct structural analysis using scMRI (Zielinski et al. 2012).
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30
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Tsuzuki D, Homae F, Taga G, Watanabe H, Matsui M, Dan I. Macroanatomical Landmarks Featuring Junctions of Major Sulci and Fissures and Scalp Landmarks Based on the International 10-10 System for Analyzing Lateral Cortical Development of Infants. Front Neurosci 2017; 11:394. [PMID: 28744192 PMCID: PMC5504468 DOI: 10.3389/fnins.2017.00394] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Accepted: 06/23/2017] [Indexed: 11/13/2022] Open
Abstract
The topographic relationships between the macroanatomical structure of the lateral cortex, including sulci and fissures, and anatomical landmarks on the external surface of the head are known to be consistent. This allows the coregistration of EEG electrodes or functional near-infrared spectroscopy over the scalp with underlying cortical regions. However, limited information is available as to whether the topographic relationships are maintained in rapidly developing infants, whose brains and heads exhibit drastic growth. We used MRIs of infants ranging in age from 3 to 22 months old, and identified 20 macroanatomical landmarks, featuring the junctions of major sulci and fissures, as well as cranial landmarks and virtually determined positions of the international 10-20 and 10-10 systems. A Procrustes analysis revealed developmental trends in changes of shape in both the cortex and head. An analysis of Euclidian distances between selected pairs of cortical landmarks at standard stereotactic coordinates showed anterior shifts of the relative positions of the premotor and parietal cortices with age. Finally, cortical landmark positions and their spatial variability were compared with 10-10 landmark positions. The results indicate that variability in the distribution of each macroanatomical landmark was much smaller than the pitch of the 10-10 landmarks. This study demonstrates that the scalp-based 10-10 system serves as a good frame of reference in infants not only for assessing the development of the macroanatomy of the lateral cortical structure, but also for functional studies of cortical development using transcranial modalities such as EEG and fNIRS.
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Affiliation(s)
- Daisuke Tsuzuki
- Department of Language Sciences, Tokyo Metropolitan UniversityTokyo, Japan.,Graduate School of Education, The University of TokyoTokyo, Japan.,Applied Cognitive Neuroscience Laboratory, Chuo UniversityTokyo, Japan
| | - Fumitaka Homae
- Department of Language Sciences, Tokyo Metropolitan UniversityTokyo, Japan.,Research Center for Language, Brain and Genetics, Tokyo Metropolitan UniversityTokyo, Japan
| | - Gentaro Taga
- Graduate School of Education, The University of TokyoTokyo, Japan
| | - Hama Watanabe
- Graduate School of Education, The University of TokyoTokyo, Japan
| | - Mie Matsui
- Department of Psychology, Graduate School of Medicine and Pharmaceutical Sciences, University of ToyamaToyama, Japan.,Department of Clinical Cognitive Neuroscience, Institute of Liberal Arts and Science, Kanazawa UniversityKanazawa, Japan
| | - Ippeita Dan
- Applied Cognitive Neuroscience Laboratory, Chuo UniversityTokyo, Japan
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31
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Ou Y, Zöllei L, Retzepi K, Castro V, Bates SV, Pieper S, Andriole KP, Murphy SN, Gollub RL, Grant PE. Using clinically acquired MRI to construct age-specific ADC atlases: Quantifying spatiotemporal ADC changes from birth to 6-year old. Hum Brain Mapp 2017; 38:3052-3068. [PMID: 28371107 PMCID: PMC5426959 DOI: 10.1002/hbm.23573] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Revised: 03/03/2017] [Accepted: 03/07/2017] [Indexed: 12/19/2022] Open
Abstract
Diffusion imaging is critical for detecting acute brain injury. However, normal apparent diffusion coefficient (ADC) maps change rapidly in early childhood, making abnormality detection difficult. In this article, we explored clinical PACS and electronic healthcare records (EHR) to create age-specific ADC atlases for clinical radiology reference. Using the EHR and three rounds of multiexpert reviews, we found ADC maps from 201 children 0-6 years of age scanned between 2006 and 2013 who had brain MRIs with no reported abnormalities and normal clinical evaluations 2+ years later. These images were grouped in 10 age bins, densely sampling the first 1 year of life (5 bins, including neonates and 4 quarters) and representing the 1-6 year age range (an age bin per year). Unbiased group-wise registration was used to construct ADC atlases for 10 age bins. We used the atlases to quantify (a) cross-sectional normative ADC variations; (b) spatiotemporal heterogeneous ADC changes; and (c) spatiotemporal heterogeneous volumetric changes. The quantified age-specific whole-brain and region-wise ADC values were compared to those from age-matched individual subjects in our study and in multiple existing independent studies. The significance of this study is that we have shown that clinically acquired images can be used to construct normative age-specific atlases. These first of their kind age-specific normative ADC atlases quantitatively characterize changes of myelination-related water diffusion in the first 6 years of life. The quantified voxel-wise spatiotemporal ADC variations provide standard references to assist radiologists toward more objective interpretation of abnormalities in clinical images. Our atlases are available at https://www.nitrc.org/projects/mgh_adcatlases. Hum Brain Mapp 38:3052-3068, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Yangming Ou
- Psychiatric Neuroimaging, Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
- Laboratory for Computational NeuroimagingAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
- Quantitative Tumor Imaging at Martinos, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
- Fetal‐Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical SchoolBostonMassachusetts
| | - Lilla Zöllei
- Laboratory for Computational NeuroimagingAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
| | - Kallirroi Retzepi
- Psychiatric Neuroimaging, Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
- Laboratory for Computational NeuroimagingAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
| | - Victor Castro
- Research Computing, Partners Healthcare, 1 Constitution CenterCharlestownMassachusetts
- Laboratory of Computer ScienceMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusetts
| | - Sara V. Bates
- Division of Newborn Medicine, Department of PediatricsMassachusetts General Hospital for Children, Harvard Medical SchoolBostonMassachusetts
| | | | - Katherine P. Andriole
- Department of RadiologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusetts
| | - Shawn N. Murphy
- Research Computing, Partners Healthcare, 1 Constitution CenterCharlestownMassachusetts
- Laboratory of Computer ScienceMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusetts
| | - Randy L. Gollub
- Psychiatric Neuroimaging, Department of PsychiatryMassachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
- Laboratory for Computational NeuroimagingAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolCharlestownMassachusetts
| | - Patricia Ellen Grant
- Fetal‐Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical SchoolBostonMassachusetts
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Wilke M, Altaye M, Holland SK. CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation. Front Comput Neurosci 2017; 11:5. [PMID: 28275348 PMCID: PMC5321046 DOI: 10.3389/fncom.2017.00005] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2016] [Accepted: 01/24/2017] [Indexed: 12/28/2022] Open
Abstract
Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps. Appropriately selecting these tissue maps becomes particularly important when investigating "unusual" populations, such as young children or elderly subjects. When creating such priors, the disadvantage of applying more deformation must be weighed against the benefit of achieving a crisper image. We have previously suggested that statistically modeling demographic variables, instead of simply averaging images, is advantageous. Both aspects (more vs. less deformation and modeling vs. averaging) were explored here. We used imaging data from 1914 subjects, aged 13 months to 75 years, and employed multivariate adaptive regression splines to model the effects of age, field strength, gender, and data quality. Within the spm/cat12 framework, we compared an affine-only with a low- and a high-dimensional warping approach. As expected, more deformation on the individual level results in lower group dissimilarity. Consequently, effects of age in particular are less apparent in the resulting tissue maps when using a more extensive deformation scheme. Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated priors based on 25, 50, or 100 subjects. Distinct effects of field strength, gender, and data quality were seen. We conclude that an extensive matching for generating tissue priors may model much of the variability inherent in the dataset which is then not contained in the resulting priors. Further, the statistical description of relevant parameters (using regression splines) allows for the generation of high-quality tissue probability maps while controlling for known confounds. The resulting CerebroMatic toolbox is available for download at http://irc.cchmc.org/software/cerebromatic.php.
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Affiliation(s)
- Marko Wilke
- Department of Pediatric Neurology and Developmental Medicine, Children's Hospital and Experimental Pediatric Neuroimaging Group, Children's Hospital and Department of Neuroradiology, University of TübingenTübingen, Germany
| | - Mekibib Altaye
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Research Foundation and Department of Pediatrics, Division of Biostatistics and Epidemiology, University of Cincinnati College of MedicineCincinnati, OH, USA
| | - Scott K. Holland
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Research Foundation and Department of Radiology, University of Cincinnati College of MedicineCincinnati, OH, USA
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Benkarim OM, Sanroma G, Zimmer VA, Muñoz-Moreno E, Hahner N, Eixarch E, Camara O, González Ballester MA, Piella G. Toward the automatic quantification of in utero brain development in 3D structural MRI: A review. Hum Brain Mapp 2017; 38:2772-2787. [PMID: 28195417 DOI: 10.1002/hbm.23536] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2016] [Revised: 01/13/2017] [Accepted: 01/25/2017] [Indexed: 11/08/2022] Open
Abstract
Investigating the human brain in utero is important for researchers and clinicians seeking to understand early neurodevelopmental processes. With the advent of fast magnetic resonance imaging (MRI) techniques and the development of motion correction algorithms to obtain high-quality 3D images of the fetal brain, it is now possible to gain more insight into the ongoing maturational processes in the brain. In this article, we present a review of the major building blocks of the pipeline toward performing quantitative analysis of in vivo MRI of the developing brain and its potential applications in clinical settings. The review focuses on T1- and T2-weighted modalities, and covers state of the art methodologies involved in each step of the pipeline, in particular, 3D volume reconstruction, spatio-temporal modeling of the developing brain, segmentation, quantification techniques, and clinical applications. Hum Brain Mapp 38:2772-2787, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
| | | | | | - Emma Muñoz-Moreno
- Fetal i+D Fetal Medicine Research Center, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, Spain.,Experimental 7T MRI Unit, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Nadine Hahner
- Fetal i+D Fetal Medicine Research Center, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, Spain
| | - Elisenda Eixarch
- Fetal i+D Fetal Medicine Research Center, BCNatal - Barcelona Center for Maternal-Fetal and Neonatal Medicine (Hospital Clínic and Hospital Sant Joan de Deu), IDIBAPS, University of Barcelona, Spain
| | - Oscar Camara
- DTIC, Universitat Pompeu Fabra, Barcelona, Spain
| | | | - Gemma Piella
- DTIC, Universitat Pompeu Fabra, Barcelona, Spain
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Ghadimi S, Mohtasebi M, Abrishami Moghaddam H, Grebe R, Gity M, Wallois F. A Neonatal Bimodal MR-CT Head Template. PLoS One 2017; 12:e0166112. [PMID: 28129340 PMCID: PMC5271307 DOI: 10.1371/journal.pone.0166112] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2016] [Accepted: 10/24/2016] [Indexed: 11/20/2022] Open
Abstract
Neonatal MR templates are appropriate for brain structural analysis and spatial normalization. However, they do not provide the essential accurate details of cranial bones and fontanels-sutures. Distinctly, CT images provide the best contrast for bone definition and fontanels-sutures. In this paper, we present, for the first time, an approach to create a fully registered bimodal MR-CT head template for neonates with a gestational age of 39 to 42 weeks. Such a template is essential for structural and functional brain studies, which require precise geometry of the head including cranial bones and fontanels-sutures. Due to the special characteristics of the problem (which requires inter-subject inter-modality registration), a two-step intensity-based registration method is proposed to globally and locally align CT images with an available MR template. By applying groupwise registration, the new neonatal CT template is then created in full alignment with the MR template to build a bimodal MR-CT template. The mutual information value between the CT and the MR template is 1.17 which shows their perfect correspondence in the bimodal template. Moreover, the average mutual information value between normalized images and the CT template proposed in this study is 1.24±0.07. Comparing this value with the one reported in a previously published approach (0.63±0.07) demonstrates the better generalization properties of the new created template and the superiority of the proposed method for the creation of CT template in the standard space provided by MR neonatal head template. The neonatal bimodal MR-CT head template is freely downloadable from https://www.u-picardie.fr/labo/GRAMFC.
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Affiliation(s)
- Sona Ghadimi
- Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
- Inserm UMR 1105, Faculté de Médecine, Université de Picardie Jules Verne, Amiens, France
| | - Mehrana Mohtasebi
- Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Hamid Abrishami Moghaddam
- Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran, Iran
- Inserm UMR 1105, Faculté de Médecine, Université de Picardie Jules Verne, Amiens, France
- * E-mail:
| | - Reinhard Grebe
- Inserm UMR 1105, Faculté de Médecine, Université de Picardie Jules Verne, Amiens, France
| | | | - Fabrice Wallois
- Inserm UMR 1105, Faculté de Médecine, Université de Picardie Jules Verne, Amiens, France
- Inserm UMR 1105, Centre Hospitalier Universitaire d'Amiens, Amiens, France
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35
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Serag A, Wilkinson AG, Telford EJ, Pataky R, Sparrow SA, Anblagan D, Macnaught G, Semple SI, Boardman JP. SEGMA: An Automatic SEGMentation Approach for Human Brain MRI Using Sliding Window and Random Forests. Front Neuroinform 2017; 11:2. [PMID: 28163680 PMCID: PMC5247463 DOI: 10.3389/fninf.2017.00002] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2016] [Accepted: 01/05/2017] [Indexed: 11/29/2022] Open
Abstract
Quantitative volumes from brain magnetic resonance imaging (MRI) acquired across the life course may be useful for investigating long term effects of risk and resilience factors for brain development and healthy aging, and for understanding early life determinants of adult brain structure. Therefore, there is an increasing need for automated segmentation tools that can be applied to images acquired at different life stages. We developed an automatic segmentation method for human brain MRI, where a sliding window approach and a multi-class random forest classifier were applied to high-dimensional feature vectors for accurate segmentation. The method performed well on brain MRI data acquired from 179 individuals, analyzed in three age groups: newborns (38–42 weeks gestational age), children and adolescents (4–17 years) and adults (35–71 years). As the method can learn from partially labeled datasets, it can be used to segment large-scale datasets efficiently. It could also be applied to different populations and imaging modalities across the life course.
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Affiliation(s)
- Ahmed Serag
- MRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK
| | | | - Emma J Telford
- MRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK
| | - Rozalia Pataky
- MRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK
| | - Sarah A Sparrow
- MRC Centre for Reproductive Health, University of Edinburgh Edinburgh, UK
| | - Devasuda Anblagan
- MRC Centre for Reproductive Health, University of EdinburghEdinburgh, UK; Centre for Clinical Brain Sciences, University of EdinburghEdinburgh, UK
| | - Gillian Macnaught
- Clinical Research Imaging Centre, University of Edinburgh Edinburgh, UK
| | - Scott I Semple
- Clinical Research Imaging Centre, University of EdinburghEdinburgh, UK; Centre for Cardiovascular Science, University of EdinburghEdinburgh, UK
| | - James P Boardman
- MRC Centre for Reproductive Health, University of EdinburghEdinburgh, UK; Centre for Clinical Brain Sciences, University of EdinburghEdinburgh, UK
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Dickie DA, Shenkin SD, Anblagan D, Lee J, Blesa Cabez M, Rodriguez D, Boardman JP, Waldman A, Job DE, Wardlaw JM. Whole Brain Magnetic Resonance Image Atlases: A Systematic Review of Existing Atlases and Caveats for Use in Population Imaging. Front Neuroinform 2017; 11:1. [PMID: 28154532 PMCID: PMC5244468 DOI: 10.3389/fninf.2017.00001] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Accepted: 01/04/2017] [Indexed: 11/17/2022] Open
Abstract
Brain MRI atlases may be used to characterize brain structural changes across the life course. Atlases have important applications in research, e.g., as registration and segmentation targets to underpin image analysis in population imaging studies, and potentially in future in clinical practice, e.g., as templates for identifying brain structural changes out with normal limits, and increasingly for use in surgical planning. However, there are several caveats and limitations which must be considered before successfully applying brain MRI atlases to research and clinical problems. For example, the influential Talairach and Tournoux atlas was derived from a single fixed cadaveric brain from an elderly female with limited clinical information, yet is the basis of many modern atlases and is often used to report locations of functional activation. We systematically review currently available whole brain structural MRI atlases with particular reference to the implications for population imaging through to emerging clinical practice. We found 66 whole brain structural MRI atlases world-wide. The vast majority were based on T1, T2, and/or proton density (PD) structural sequences, had been derived using parametric statistics (inappropriate for brain volume distributions), had limited supporting clinical or cognitive data, and included few younger (>5 and <18 years) or older (>60 years) subjects. To successfully characterize brain structural features and their changes across different stages of life, we conclude that whole brain structural MRI atlases should include: more subjects at the upper and lower extremes of age; additional structural sequences, including fluid attenuation inversion recovery (FLAIR) and T2* sequences; a range of appropriate statistics, e.g., rank-based or non-parametric; and detailed cognitive and clinical profiles of the included subjects in order to increase the relevance and utility of these atlases.
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Affiliation(s)
- David Alexander Dickie
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationGlasgow, UK
| | - Susan D. Shenkin
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Geriatric Medicine Unit, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, The University of EdinburghEdinburgh, UK
| | - Devasuda Anblagan
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationGlasgow, UK
- MRC Centre for Reproductive Health, Queen's Medical Research InstituteEdinburgh, UK
| | - Juyoung Lee
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of TübingenTübingen, Germany
| | - Manuel Blesa Cabez
- MRC Centre for Reproductive Health, Queen's Medical Research InstituteEdinburgh, UK
| | - David Rodriguez
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationGlasgow, UK
| | - James P. Boardman
- MRC Centre for Reproductive Health, Queen's Medical Research InstituteEdinburgh, UK
| | - Adam Waldman
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
| | - Dominic E. Job
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationGlasgow, UK
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Neuroimaging Sciences, Centre for Clinical Brain Sciences, Royal Infirmary of Edinburgh, The University of EdinburghEdinburgh, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) CollaborationGlasgow, UK
- Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, The University of EdinburghEdinburgh, UK
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37
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Horowitz-Kraus T, Farah R, Hajinazarian A, Eaton K, Rajagopal A, Schmithorst VJ, Altaye M, Vannest JJ, Holland SK. Maturation of Brain Regions Related to the Default Mode Network during Adolescence Facilitates Narrative Comprehension. ACTA ACUST UNITED AC 2017; 5. [PMID: 32524005 PMCID: PMC7286598 DOI: 10.4172/2375-4494.1000328] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Objectives Although the Default Mode Network (DMN) has been examined extensively in adults, developmental characteristics of this network during childhood are not fully understood. Methods In this longitudinal study, we characterized the developmental changes in the DMN in fifteen children who were each scanned three times during a narrative comprehension task using magnetic resonance imaging. Results Despite similar brain-activation patterns along developmental ages 5 to 18 years when listening to stories, increased, widely distributed deactivation of the DMN was observed in children between the ages of 11 and 18 years. Our findings suggest that changes occurring with increased age, primarily brain maturation and cognitive development drive deactivation of the DMN, which in turn might facilitate attendance to the task. Conclusions The interpretation of our results is as a possible reference for the typical course of deactivation of the DMN and to explain the impaired patterns in this neural network associated with different language-related pathologies.
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Affiliation(s)
- Tzipi Horowitz-Kraus
- Educational Neuroimaging Center, Faculty of Education in Science and Technology, Technion, Israel.,Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.,Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA.,Communication Sciences Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Rola Farah
- Educational Neuroimaging Center, Faculty of Education in Science and Technology, Technion, Israel
| | - Ardag Hajinazarian
- Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.,Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA.,Communication Sciences Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Kenneth Eaton
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA
| | - Akila Rajagopal
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA
| | - Vincent J Schmithorst
- Department of Radiology, Children's Hospital of Pittsburgh of UPMC, Pittsburgh, Pennsylvania, USA
| | - Mekibib Altaye
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA
| | - Jennifer J Vannest
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA
| | - Scott K Holland
- Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.,Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA.,Communication Sciences Research Center, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
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38
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Mongerson CRL, Jennings RW, Borsook D, Becerra L, Bajic D. Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality. Front Pediatr 2017; 5:159. [PMID: 28856131 PMCID: PMC5557740 DOI: 10.3389/fped.2017.00159] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2017] [Accepted: 07/04/2017] [Indexed: 11/02/2022] Open
Abstract
Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used.
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Affiliation(s)
- Chandler R L Mongerson
- Center for Pain and the Brain, Boston Children's Hospital, Boston, MA, United States.,Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States
| | - Russell W Jennings
- Department of Surgery, Boston Children's Hospital, Boston, MA, United States.,Department of Surgery, Harvard Medical School, Boston, MA, United States
| | - David Borsook
- Center for Pain and the Brain, Boston Children's Hospital, Boston, MA, United States.,Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States.,Department of Anaesthesia, Harvard Medical School, Boston, MA, United States
| | - Lino Becerra
- Center for Pain and the Brain, Boston Children's Hospital, Boston, MA, United States.,Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States.,Department of Anaesthesia, Harvard Medical School, Boston, MA, United States
| | - Dusica Bajic
- Center for Pain and the Brain, Boston Children's Hospital, Boston, MA, United States.,Department of Anesthesiology, Perioperative and Pain Medicine, Boston Children's Hospital, Boston, MA, United States.,Department of Anaesthesia, Harvard Medical School, Boston, MA, United States
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39
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Novel Multimodal Atlas Template for Spatial Normalization of Whole-Brain Images of Newborns. Ing Rech Biomed 2016. [DOI: 10.1016/j.irbm.2016.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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40
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Horowitz-Kraus T, Buck C, Dorrmann D. Altered neural circuits accompany lower performance during narrative comprehension in children with reading difficulties: an fMRI study. ANNALS OF DYSLEXIA 2016; 66:301-318. [PMID: 26987654 DOI: 10.1007/s11881-016-0124-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2015] [Accepted: 01/28/2016] [Indexed: 06/05/2023]
Abstract
Narrative comprehension is a linguistic ability that is foundational for future reading ability. The aim of the current study was to examine the neural circuitry of children with reading difficulties (RD) compared to typical readers during a narrative-comprehension task. We hypothesized that due to deficient executive functions, which support narrative comprehension abilities, children with RD would display altered activation and functional connectivity, as well as lower performance on a narrative-comprehension task. Children with RD and typical readers were scanned during a narrative-comprehension task and administered reading behavioral tests. Children with RD scored significantly lower on the narrative-comprehension task than did typical readers. Composite activation maps showed more diffused activation during narrative comprehension in the RD group. Maps comparing the two reading groups showed more activation in the frontal lobes (regions responsible for executive functions), and functional connectivity showed higher global efficiency in children with RD than in typical readers. Global efficiency was negatively correlated with phonological awareness and reading and executive function scores in the entire study group. Children with RD may suffer from narrative-comprehension difficulties due to diffused activation of language areas, as was observed during a narrative-comprehension task. Greater effort in this task may be reflected by the engagement of brain regions related to executive functions and higher functional connectivity or attributed to difficulties in phonological processing and reading and executive functions. Therefore, the accommodation given to children with RD of reading aloud may need to be revised due to the observed difficulty in this domain.
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Affiliation(s)
- Tzipi Horowitz-Kraus
- Educational Neuroimaging Center, Faculty of Education in Science and Technology, Technion- Israel institute of Technology, Haifa, Israel.
- Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, 3333 Burnet Av., Cincinnati, Ohio, USA.
- Pediatric Neuroimaging Research Consortium, Cincinnati Children's Hospital Medical Center, 3333 Burnet Av., Cincinnati, Ohio, USA.
| | - Catherine Buck
- Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, 3333 Burnet Av., Cincinnati, Ohio, USA
| | - Dana Dorrmann
- Reading and Literacy Discovery Center, Cincinnati Children's Hospital Medical Center, 3333 Burnet Av., Cincinnati, Ohio, USA
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41
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Language learning and brain reorganization in a 3.5-year-old child with left perinatal stroke revealed using structural and functional connectivity. Cortex 2016; 77:95-118. [DOI: 10.1016/j.cortex.2016.01.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2015] [Revised: 08/09/2015] [Accepted: 01/18/2016] [Indexed: 11/20/2022]
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42
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Levman J, Takahashi E. Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI. Front Neuroanat 2016; 9:163. [PMID: 26834576 PMCID: PMC4720794 DOI: 10.3389/fnana.2015.00163] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Accepted: 12/04/2015] [Indexed: 11/13/2022] Open
Abstract
Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neurological medical imaging related challenges including the evaluation of healthy brain development, the automated analysis of brain tissues and structures through image segmentation, evaluating the effects of genetic and environmental factors on brain development, evaluating sensory stimulation's relationship with functional brain activity and much more. Compared to adult imaging, pediatric, neonatal and fetal imaging have attracted less attention from MVA researchers, however, recent years have seen remarkable MVA research growth in pre-adult populations. This paper presents the results of a systematic review of the literature focusing on MVA applied to healthy subjects in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in brain MRI, the field is still young and significant research growth will continue into the future.
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Affiliation(s)
- Jacob Levman
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA
| | - Emi Takahashi
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Harvard Medical SchoolBoston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General HospitalCharlestown, MA, USA
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Fengler A, Meyer L, Friederici AD. How the brain attunes to sentence processing: Relating behavior, structure, and function. Neuroimage 2016; 129:268-278. [PMID: 26777477 PMCID: PMC4819595 DOI: 10.1016/j.neuroimage.2016.01.012] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Revised: 11/24/2015] [Accepted: 01/06/2016] [Indexed: 11/25/2022] Open
Abstract
Unlike other aspects of language comprehension, the ability to process complex sentences develops rather late in life. Brain maturation as well as verbal working memory (vWM) expansion have been discussed as possible reasons. To determine the factors contributing to this functional development, we assessed three aspects in different age-groups (5–6 years, 7–8 years, and adults): first, functional brain activity during the processing of increasingly complex sentences; second, brain structure in language-related ROIs; and third, the behavioral comprehension performance on complex sentences and the performance on an independent vWM test. At the whole-brain level, brain functional data revealed a qualitatively similar neural network in children and adults including the left pars opercularis (PO), the left inferior parietal lobe together with the posterior superior temporal gyrus (IPL/pSTG), the supplementary motor area, and the cerebellum. While functional activation of the language-related ROIs PO and IPL/pSTG predicted sentence comprehension performance for all age-groups, only adults showed a functional selectivity in these brain regions with increased activation for more complex sentences. The attunement of both the PO and IPL/pSTG toward a functional selectivity for complex sentences is predicted by region-specific gray matter reduction while that of the IPL/pSTG is additionally predicted by vWM span. Thus, both structural brain maturation and vWM expansion provide the basis for the emergence of functional selectivity in language-related brain regions leading to more efficient sentence processing during development.
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Affiliation(s)
- Anja Fengler
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103 Leipzig, Germany.
| | - Lars Meyer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103 Leipzig, Germany
| | - Angela D Friederici
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103 Leipzig, Germany
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Lee H, Yoo BI, Han JW, Lee JJ, Oh SYW, Lee EY, Kim JH, Kim KW. Construction and Validation of Brain MRI Templates from a Korean Normal Elderly Population. Psychiatry Investig 2016; 13:135-45. [PMID: 26766956 PMCID: PMC4701677 DOI: 10.4306/pi.2016.13.1.135] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Revised: 05/21/2015] [Accepted: 06/03/2015] [Indexed: 11/20/2022] Open
Abstract
OBJECTIVE This study aimed to construct a Korean normal elderly brain template (KNE96) using Korean elderly individuals for use in brain MRI studies and to validate it. METHODS We used high-resolution 3.0T T1 structural MR images from 96 Korean normal elderly individuals (M/F=48/48), aged 60 years or older (M=69.5±6.2 years, F=70.1±7.0 years), for constructing the KNE96 template. The KNE96 template was validated by comparing the registration-induced deformations between the KNE96 and ICBM152 templates using different MR images from 48 Korean normal elderly individuals (M/F=24/24), aged 60 years or older (M=71.5±5.9 years, F=72.8±5.1 years). We used the magnitude of displacement vectors (mag-displacement) and log of Jacobian determinants (log-Jacobian) to quantify the deformation produced during registration process to templates. RESULTS The mag-displacement and log-Jacobian of the registration were much smaller using the KNE96 template than with the ICBM152 template in most brain regions. There was a prominent difference in the significant averaged differences (SADs) of the mag-displacement and log-Jacobian between the KNE96 and ICBM152 at the superior, medial, and middle frontal gyrus, the lingual, inferior, middle, and superior occipital gyrus, and the caudate and thalamus. CONCLUSION This study suggests that templates constructed from Asian populations, such as the KNE96, may be more desirable than those from Caucasian populations, like the ICBM152, in computational neuroimaging studies that measure and compare anatomical features of the frontal and occipital lobe, thalamus and caudate.
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Affiliation(s)
- Hyunna Lee
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
| | - Byung Il Yoo
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Jung Jae Lee
- Department of Psychiatry, Dankook University Medical College, Cheonan, Republic of Korea
| | - San Yeo Wool Oh
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Eun Young Lee
- Department of Psychiatry, Dankook University Medical College, Cheonan, Republic of Korea
| | - Jae Hyoung Kim
- Department of Radiology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Ki Woong Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
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Pramparo T, Lombardo MV, Campbell K, Barnes CC, Marinero S, Solso S, Young J, Mayo M, Dale A, Ahrens-Barbeau C, Murray SS, Lopez L, Lewis N, Pierce K, Courchesne E. Cell cycle networks link gene expression dysregulation, mutation, and brain maldevelopment in autistic toddlers. Mol Syst Biol 2015; 11:841. [PMID: 26668231 PMCID: PMC4704485 DOI: 10.15252/msb.20156108] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Genetic mechanisms underlying abnormal early neural development in toddlers with Autism Spectrum Disorder (ASD) remain uncertain due to the impossibility of direct brain gene expression measurement during critical periods of early development. Recent findings from a multi‐tissue study demonstrated high expression of many of the same gene networks between blood and brain tissues, in particular with cell cycle functions. We explored relationships between blood gene expression and total brain volume (TBV) in 142 ASD and control male toddlers. In control toddlers, TBV variation significantly correlated with cell cycle and protein folding gene networks, potentially impacting neuron number and synapse development. In ASD toddlers, their correlations with brain size were lost as a result of considerable changes in network organization, while cell adhesion gene networks significantly correlated with TBV variation. Cell cycle networks detected in blood are highly preserved in the human brain and are upregulated during prenatal states of development. Overall, alterations were more pronounced in bigger brains. We identified 23 candidate genes for brain maldevelopment linked to 32 genes frequently mutated in ASD. The integrated network includes genes that are dysregulated in leukocyte and/or postmortem brain tissue of ASD subjects and belong to signaling pathways regulating cell cycle G1/S and G2/M phase transition. Finally, analyses of the CHD8 subnetwork and altered transcript levels from an independent study of CHD8 suppression further confirmed the central role of genes regulating neurogenesis and cell adhesion processes in ASD brain maldevelopment.
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Affiliation(s)
- Tiziano Pramparo
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Michael V Lombardo
- Department of Psychology, University of Cyprus, Nicosia, Cyprus Center for Applied Neuroscience, University of Cyprus, Nicosia, Cyprus Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Kathleen Campbell
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Cynthia Carter Barnes
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Steven Marinero
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Stephanie Solso
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Julia Young
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Maisi Mayo
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Anders Dale
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Clelia Ahrens-Barbeau
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Sarah S Murray
- Scripps Genomic Medicine & The Scripps Translational Sciences Institute (STSI), La Jolla, CA, USA Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Linda Lopez
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Nathan Lewis
- Novo Nordisk Foundation Center for Biosustainability at the UCSD School of Medicine, and Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Karen Pierce
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
| | - Eric Courchesne
- Department of Neurosciences, UC San Diego Autism Center, School of Medicine University of California San Diego, La Jolla, CA, USA
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Horowitz-Kraus T, Eaton K, Farah R, Hajinazarian A, Vannest J, Holland SK. Predicting better performance on a college preparedness test from narrative comprehension at the age of 6 years: An fMRI study. Brain Res 2015; 1629:54-62. [DOI: 10.1016/j.brainres.2015.10.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2015] [Revised: 09/10/2015] [Accepted: 10/02/2015] [Indexed: 10/22/2022]
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Tan L, Holland SK, Deshpande AK, Chen Y, Choo DI, Lu LJ. A semi-supervised Support Vector Machine model for predicting the language outcomes following cochlear implantation based on pre-implant brain fMRI imaging. Brain Behav 2015; 5:e00391. [PMID: 26807332 PMCID: PMC4714644 DOI: 10.1002/brb3.391] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2015] [Revised: 07/23/2015] [Accepted: 08/09/2015] [Indexed: 11/14/2022] Open
Abstract
INTRODUCTION We developed a machine learning model to predict whether or not a cochlear implant (CI) candidate will develop effective language skills within 2 years after the CI surgery by using the pre-implant brain fMRI data from the candidate. METHODS The language performance was measured 2 years after the CI surgery by the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2). Based on the CELF-P2 scores, the CI recipients were designated as either effective or ineffective CI users. For feature extraction from the fMRI data, we constructed contrast maps using the general linear model, and then utilized the Bag-of-Words (BoW) approach that we previously published to convert the contrast maps into feature vectors. We trained both supervised models and semi-supervised models to classify CI users as effective or ineffective. RESULTS Compared with the conventional feature extraction approach, which used each single voxel as a feature, our BoW approach gave rise to much better performance for the classification of effective versus ineffective CI users. The semi-supervised model with the feature set extracted by the BoW approach from the contrast of speech versus silence achieved a leave-one-out cross-validation AUC as high as 0.97. Recursive feature elimination unexpectedly revealed that two features were sufficient to provide highly accurate classification of effective versus ineffective CI users based on our current dataset. CONCLUSION We have validated the hypothesis that pre-implant cortical activation patterns revealed by fMRI during infancy correlate with language performance 2 years after cochlear implantation. The two brain regions highlighted by our classifier are potential biomarkers for the prediction of CI outcomes. Our study also demonstrated the superiority of the semi-supervised model over the supervised model. It is always worthwhile to try a semi-supervised model when unlabeled data are available.
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Affiliation(s)
- Lirong Tan
- Division of Biomedical Informatics Cincinnati Children's Hospital Research Foundation 3333 Burnet Avenue Cincinnati Ohio 45229; Department of Electrical Engineering and Computing System University of Cincinnati 812 Rhodes Hall Cincinnati Ohio 45221-0030
| | - Scott K Holland
- Pediatric Neuroimaging Research Consortium Cincinnati Children's Hospital Medical Center Cincinnati Ohio 45221
| | - Aniruddha K Deshpande
- Department of Speech-Language-Hearing-Sciences, 106A Davison Hall 110 Hofstra University, Hempstead New York 11549
| | - Ye Chen
- Division of Biomedical Informatics Cincinnati Children's Hospital Research Foundation 3333 Burnet Avenue Cincinnati Ohio 45229; Department of Electrical Engineering and Computing System University of Cincinnati 812 Rhodes Hall Cincinnati Ohio 45221-0030
| | - Daniel I Choo
- Department of Otolaryngology College of Medicine University of Cincinnati Medical Sciences Building 231 Albert Sabin Way Cincinnati Ohio 45267
| | - Long J Lu
- Division of Biomedical Informatics Cincinnati Children's Hospital Research Foundation 3333 Burnet Avenue Cincinnati Ohio 45229; Department of Electrical Engineering and Computing System University of Cincinnati 812 Rhodes Hall Cincinnati Ohio 45221-0030; Department of Environmental Health College of Medicine University of Cincinnati 231 Albert Sabin Way Cincinnati Ohio 45267
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Fillmore PT, Richards JE, Phillips-Meek MC, Cryer A, Stevens M. Stereotaxic Magnetic Resonance Imaging Brain Atlases for Infants from 3 to 12 Months. Dev Neurosci 2015; 37:515-32. [PMID: 26440296 DOI: 10.1159/000438749] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2014] [Accepted: 07/16/2015] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Accurate labeling of brain structures within an individual or group is a key issue in neuroimaging. Methods for labeling infant brains have depended on the labels done on adult brains or average magnetic resonance imaging (MRI) templates based on adult brains. However, the features of adult brains differ in several ways from infant brains, so the creation of a labeled stereotaxic atlas based on infants would be helpful. The current work builds on the recent creation of age-appropriate average MRI templates during the first year (3, 4.5, 6, 7.5, 9, and 12 months) by creating anatomical label sets for each template. METHODS We created stereotaxic atlases for the age-specific average MRI templates. Manual delineation of cortical and subcortical areas was done on the average templates based on infants during the first year. We also applied a procedure for automatic computation of macroanatomical atlases for individual infant participants using two manually segmented adult atlases (Hammers, LONI Probabilistic Brain Atlas-LPBA40). To evaluate our methods, we did manual delineation of several cortical areas on selected individuals from each age. Linear and nonlinear registration of the individual and average template was used to transform the average atlas into the individual participant's space, and the average-transformed atlas was compared to the individual manually delineated brain areas. We also applied these methods to an external data set - not used in the atlas creation - to test generalizability of the atlases. RESULTS Age-appropriate manual atlases were the best fit to the individual manually delineated regions, with more error seen at greater age discrepancy. There was a close fit between the manually delineated and the automatically labeled regions for individual participants and for the age-appropriate template-based atlas transformed into participant space. There was close correspondence between automatic labeling of individual brain regions and those from the age-appropriate template. These relationships held even when tested on an external set of images. CONCLUSION We have created age-appropriate labeled templates for use in the study of infant development at 6 ages (3, 4.5, 6, 7.5, 9, and 12 months). Comparison with manual methods was quite good. We developed three stereotaxic atlases (one manual, two automatic) for each infant age, which should allow more fine-grained analysis of brain structure for these populations than was previously possible with existing tools. The template-based atlases constructed in the current study are available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase).
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Affiliation(s)
- Paul T Fillmore
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, S.C., USA
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Li G, Wang L, Shi F, Gilmore JH, Lin W, Shen D. Construction of 4D high-definition cortical surface atlases of infants: Methods and applications. Med Image Anal 2015; 25:22-36. [PMID: 25980388 PMCID: PMC4540689 DOI: 10.1016/j.media.2015.04.005] [Citation(s) in RCA: 90] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Revised: 04/07/2015] [Accepted: 04/09/2015] [Indexed: 11/24/2022]
Abstract
In neuroimaging, cortical surface atlases play a fundamental role for spatial normalization, analysis, visualization, and comparison of results across individuals and different studies. However, existing cortical surface atlases created for adults are not suitable for infant brains during the first two postnatal years, which is the most dynamic period of postnatal structural and functional development of the highly-folded cerebral cortex. Therefore, spatiotemporal cortical surface atlases for infant brains are highly desired yet still lacking for accurate mapping of early dynamic brain development. To bridge this significant gap, leveraging our infant-dedicated computational pipeline for cortical surface-based analysis and the unique longitudinal infant MRI dataset acquired in our research center, in this paper, we construct the first spatiotemporal (4D) high-definition cortical surface atlases for the dynamic developing infant cortical structures at seven time points, including 1, 3, 6, 9, 12, 18, and 24 months of age, based on 202 serial MRI scans from 35 healthy infants. For this purpose, we develop a novel method to ensure the longitudinal consistency and unbiasedness to any specific subject and age in our 4D infant cortical surface atlases. Specifically, we first compute the within-subject mean cortical folding by unbiased groupwise registration of longitudinal cortical surfaces of each infant. Then we establish longitudinally-consistent and unbiased inter-subject cortical correspondences by groupwise registration of the geometric features of within-subject mean cortical folding across all infants. Our 4D surface atlases capture both longitudinally-consistent dynamic mean shape changes and the individual variability of cortical folding during early brain development. Experimental results on two independent infant MRI datasets show that using our 4D infant cortical surface atlases as templates leads to significantly improved accuracy for spatial normalization of cortical surfaces across infant individuals, in comparison to the infant surface atlases constructed without longitudinal consistency and also the FreeSurfer adult surface atlas. Moreover, based on our 4D infant surface atlases, for the first time, we reveal the spatially-detailed, region-specific correlation patterns of the dynamic cortical developmental trajectories between different cortical regions during early brain development.
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Affiliation(s)
- Gang Li
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Feng Shi
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA
| | - John H Gilmore
- Department of Psychiatry, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Weili Lin
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Dinggang Shen
- Department of Radiology and BRIC, University of North Carolina at Chapel Hill, NC 27599, USA; Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
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Xie W, Richards JE, Lei D, Zhu H, Lee K, Gong Q. The construction of MRI brain/head templates for Chinese children from 7 to 16 years of age. Dev Cogn Neurosci 2015; 15:94-105. [PMID: 26343862 PMCID: PMC4714595 DOI: 10.1016/j.dcn.2015.08.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2015] [Revised: 08/24/2015] [Accepted: 08/25/2015] [Indexed: 02/05/2023] Open
Abstract
Population-specific brain templates that provide detailed brain information are beneficial to both structural and functional neuroimaging research. However, age-specific MRI templates have not been constructed for Chinese or any Asian developmental populations. This study developed novel T1-weighted average brain and head templates for Chinese children from 7 to 16 years of age in two-year increments using high quality magnetic resonance imaging (MRI) and well-validated image analysis techniques. A total of 138 Chinese children (51 F/87 M) were included in this study. The internally and externally validated registrations show that these Chinese age-specific templates fit Chinese children's MR images significantly better than age-specific templates created from U.S. children, or adult templates based on either Chinese or North American adults. It implies that age-inappropriate (e.g., the Chinese56 template, the US20-24 template) and nationality-inappropriate brain templates (e.g., U.S. children's templates, the US20-24 template) do not provide optimal reference MRIs for processing MR brain images of Chinese pediatric populations. Thus, our age-specific MRI templates are the first of the kind and should be useful in neuroimaging studies with children from Chinese or other Asian populations. These templates can also serve as the foundations for the construction of more comprehensive sets of nationality-specific templates for Asian developmental populations. These templates are available for use in our database.
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Affiliation(s)
- Wanze Xie
- Department of Psychology, and Institute for Mind and Brain, University of South Carolina, United States; Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, China.
| | - John E Richards
- Department of Psychology, and Institute for Mind and Brain, University of South Carolina, United States
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, China
| | - Hongyan Zhu
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, China; Laboratory of Stem Cell Biology, State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, China.
| | - Kang Lee
- Department of Human Development and Applied Psychology, and Dr. Eric Jackman Institute of Child Study, University of Toronto, Canada
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, China; Department of Psychology, School of Public Administration, Sichuan University, China
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