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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol K, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Christopher Edgar J. Functional and structural maturation of auditory cortex from 2 months to 2 years old. Clin Neurophysiol 2024; 166:232-243. [PMID: 39213880 DOI: 10.1016/j.clinph.2024.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. METHODS AND PARTICIPANTS The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints. RESULTS In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. CONCLUSIONS Findings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency. SIGNIFICANCE Infant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jeffrey I Berman
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mary E Putt
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katharina Otten
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Faculty of Medicine, RWTH Aachen University, Aachen, 52074, Germany
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Tess Yount
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol KL, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Edgar JC. Functional and structural maturation of auditory cortex from 2 months to 2 years old. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597426. [PMID: 38895425 PMCID: PMC11185738 DOI: 10.1101/2024.06.05.597426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.
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Peers de Nieuwburgh M, Dave A, Khan SA, Ngo M, Hayes KB, Slipenchuk M, Lieberman E, Youssef MR, Crompton D, Choudhry AM, Guo N, Tian Z, Rychik J, Davey MG, Flake AW. Assessment of extremely premature lambs supported by the Extrauterine Environment for Neonatal Development (EXTEND). Pediatr Res 2024:10.1038/s41390-024-03287-0. [PMID: 38834782 DOI: 10.1038/s41390-024-03287-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 03/28/2024] [Accepted: 05/07/2024] [Indexed: 06/06/2024]
Abstract
BACKGROUND Our team has previously reported physiologic support by the EXTra-uterine Environment for Neonatal Development (EXTEND) of 105 to 117 days gestational age (GA) lambs for up to 28 days with normal organ maturation. However, the fetal lamb brain matures more rapidly, requiring the study of 90-105 day GA fetal lambs to assess more neurodevelopmentally equivalent lambs to the 23-25 week GA extreme premature infant. METHODS Extremely preterm lambs (90-95 days of GA) were delivered by C-section and supported by EXTEND. Estimated circuit flows were maintained at around 325 ml/kg/min. After support on EXTEND, MRI and histopathologic analysis were performed and compared to 105-112 days GA control lambs. RESULTS The extremely preterm group includes 10 animals with a mean GA of 91.6 days, a mean weight at cannulation of 0.98 kg and a mean length of stay on EXTEND of 13.5 days (10-21 days). Hemodynamics and oxygenation showed stable parameters. Animals showed growth and physiologic cardiac function. MRI volumetric and diffusion analysis was comparable to controls. Histologic brain analysis revealed no difference between study groups. CONCLUSION EXTEND appears to support brain and cardiac development in an earlier gestation, less mature, lamb model. IMPACT Prolonged (up to 21 days) physiological support of extremely preterm lambs of closer neurodevelopmental equivalence to the 24-28 gestational week human was achieved using the EXTEND system. EXTEND treatment supported brain growth and development in extremely preterm fetal lambs and was not associated with intraventricular hemorrhage or white matter injury. Daily echocardiography demonstrated physiologic heart function, absence of cardiac afterload, and normal developmental increase in cardiac chamber dimensions. This study demonstrates hemodynamic and metabolic support by the EXTEND system in the extremely preterm ovine model.
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Affiliation(s)
| | - Apeksha Dave
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sameer A Khan
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Michelle Ngo
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kevin B Hayes
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Evan Lieberman
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Mohanad R Youssef
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Alia Mohsin Choudhry
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Nan Guo
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Zhiyun Tian
- Division of Cardiology, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jack Rychik
- Division of Cardiology, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | | | - Alan W Flake
- Center for Fetal Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
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Schmidbauer VU, Yildirim MS, Dovjak GO, Goeral K, Buchmayer J, Weber M, Kienast P, Diogo MC, Prayer F, Stuempflen M, Kittinger J, Malik J, Nowak NM, Klebermass-Schrehof K, Fuiko R, Berger A, Prayer D, Kasprian G, Giordano V. Quantitative Magnetic Resonance Imaging for Neurodevelopmental Outcome Prediction in Neonates Born Extremely Premature-An Exploratory Study. Clin Neuroradiol 2024; 34:421-429. [PMID: 38289377 PMCID: PMC11129968 DOI: 10.1007/s00062-023-01378-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 12/26/2023] [Indexed: 05/29/2024]
Abstract
PURPOSE Neonates born at < 28 weeks of gestation are at risk for neurodevelopmental delay. The aim of this study was to identify quantitative MR-based metrics for the prediction of neurodevelopmental outcomes in extremely preterm neonates. METHODS T1-/T2-relaxation times (T1R/T2R), ADC, and fractional anisotropy (FA) of the left/right posterior limb of the internal capsule (PLIC) and the brainstem were determined at term-equivalent ages in a sample of extremely preterm infants (n = 33). Scores for cognitive, language, and motor outcomes were collected at one year corrected-age. Pearson's correlation analyses detected relationships between quantitative measures and outcome data. Stepwise regression procedures identified imaging metrics to estimate neurodevelopmental outcomes. RESULTS Cognitive outcomes correlated significantly with T2R (r = 0.412; p = 0.017) and ADC (r = -0.401; p = 0.021) (medulla oblongata). Furthermore, there were significant correlations between motor outcomes and T1R (pontine tegmentum (r = 0.346; p = 0.049), midbrain (r = 0.415; p = 0.016), right PLIC (r = 0.513; p = 0.002), and left PLIC (r = 0.504; p = 0.003)); T2R (right PLIC (r = 0.405; p = 0.019)); ADC (medulla oblongata (r = -0.408; p = 0.018) and pontine tegmentum (r = -0.414; p = 0.017)); and FA (pontine tegmentum (r = -0.352; p = 0.045)). T2R/ADC (medulla oblongata) (cognitive outcomes (R2 = 0.296; p = 0.037)) and T1R (right PLIC)/ADC (medulla oblongata) (motor outcomes (R2 = 0.405; p = 0.009)) revealed predictive potential for neurodevelopmental outcomes. CONCLUSION There are relationships between relaxometry‑/DTI-based metrics determined by neuroimaging near term and neurodevelopmental outcomes collected at one year of age. Both modalities bear prognostic potential for the prediction of cognitive and motor outcomes. Thus, quantitative MRI at term-equivalent ages represents a promising approach with which to estimate neurologic development in extremely preterm infants.
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Affiliation(s)
- Victor U Schmidbauer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria.
| | - Mehmet S Yildirim
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gregor O Dovjak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katharina Goeral
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Julia Buchmayer
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Michael Weber
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Patric Kienast
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Mariana C Diogo
- Department of Neuroradiology, Hospital Garcia de Orta, Av. Torrado da Silva, 2805-267 Almada, Portugal
| | - Florian Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Marlene Stuempflen
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Jakob Kittinger
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Jakob Malik
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Nikolaus M Nowak
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Katrin Klebermass-Schrehof
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Renate Fuiko
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Angelika Berger
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
| | - Vito Giordano
- Comprehensive Center for Pediatrics, Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics, Medical University of Vienna, Waehringer Guertel 18-20, 1090, Vienna, Austria
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Shen Y, Zhao X, Wang K, Sun Y, Zhang X, Wang C, Yang Z, Feng Z, Zhang X. Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis. Acad Radiol 2024; 31:2074-2084. [PMID: 38185571 DOI: 10.1016/j.acra.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 12/09/2023] [Accepted: 12/14/2023] [Indexed: 01/09/2024]
Abstract
RATIONALE AND OBJECTIVES This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure among children with autism spectrum disorder (ASD). Additionally, an eXtreme Gradient Boosting (XGBoost) model was developed to effectively classify individuals with ASD and typical developing children (TDC). METHODS AND MATERIALS Multi-shell diffusion weighted images were acquired from 62 children with ASD and 44 TDC. Using the Pydesigner procedure, diffusion tensor (DT), diffusion kurtosis (DK), and white matter tract integrity (WMTI) metrics were computed. Subsequently, TBSS analysis was applied to discern differences in these diffusion parameters between ASD and TDC groups. The XGBoost model was then trained using metrics showing significant differences, and Shapley Additive explanations (SHAP) values were computed to assess the feature importance in the model's predictions. RESULTS TBSS analysis revealed a significant reduction in axonal diffusivity (AD) in the left posterior corona radiata and the right superior corona radiata. Among the DK indicators, mean kurtosis, axial kurtosis, and kurtosis fractional anisotropy were notably increased in children with ASD, with no significant difference in radial kurtosis. WMTI metrics such as axonal water fraction, axonal diffusivity of the extra-axonal space (EAS_AD), tortuosity of the extra-axonal space (EAS_TORT), and diffusivity of intra-axonal space (IAS_Da) were significantly increased, primarily in the corpus callosum and fornix. Notably, there was no significant difference in radial diffusivity of the extra-axial space (EAS_RD). The XGBoost model demonstrated excellent classification ability, and the SHAP analysis identified EAS_TORT as the feature with the highest importance in the model's predictions. CONCLUSION This study utilized TBSS analyses with multi-shell diffusion data to examine white matter abnormalities in pediatric autism. Additionally, the developed XGBoost model showed outstanding performance in classifying ASD and TDC. The ranking of SHAP values based on the XGBoost model underscored the significance of features in influencing model predictions.
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Affiliation(s)
- Yanyong Shen
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Kaiyu Wang
- MR Research China, GE Healthcare, Beijing, 100000, PR China (K.W.)
| | - Yongbing Sun
- Department of Radiology, Henan Provincial People's Hospital, Zhengzhou, 450000, China (Y.S.)
| | - Xiaoxue Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Changhao Wang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Zhexuan Yang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Zhanqi Feng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.)
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.); Henan International Joint Laboratory of Neuroimaging, Zhengzhou, 450052, China (Y.S., X.Z., X.Z., C.W., Z.Y., Z.F., X.Z.).
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Song L, Peng Y, Ouyang M, Peng Q, Feng L, Sotardi S, Yu Q, Kang H, Sindabizera KL, Liu S, Huang H. Diffusion-tensor-imaging 1-year-old and 2-year-old infant brain atlases with comprehensive gray and white matter labels. Hum Brain Mapp 2024; 45:e26695. [PMID: 38727010 PMCID: PMC11083905 DOI: 10.1002/hbm.26695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2023] [Revised: 03/11/2024] [Accepted: 04/10/2024] [Indexed: 05/13/2024] Open
Abstract
Human infancy is marked by fastest postnatal brain structural changes. It also coincides with the onset of many neurodevelopmental disorders. Atlas-based automated structure labeling has been widely used for analyzing various neuroimaging data. However, the relatively large and nonlinear neuroanatomical differences between infant and adult brains can lead to significant offsets of the labeled structures in infant brains when adult brain atlas is used. Age-specific 1- and 2-year-old brain atlases covering all major gray and white matter (GM and WM) structures with diffusion tensor imaging (DTI) and structural MRI are critical for precision medicine for infant population yet have not been established. In this study, high-quality DTI and structural MRI data were obtained from 50 healthy children to build up three-dimensional age-specific 1- and 2-year-old brain templates and atlases. Age-specific templates include a single-subject template as well as two population-averaged templates from linear and nonlinear transformation, respectively. Each age-specific atlas consists of 124 comprehensively labeled major GM and WM structures, including 52 cerebral cortical, 10 deep GM, 40 WM, and 22 brainstem and cerebellar structures. When combined with appropriate registration methods, the established atlases can be used for highly accurate automatic labeling of any given infant brain MRI. We demonstrated that one can automatically and effectively delineate deep WM microstructural development from 3 to 38 months by using these age-specific atlases. These established 1- and 2-year-old infant brain DTI atlases can advance our understanding of typical brain development and serve as clinical anatomical references for brain disorders during infancy.
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Affiliation(s)
- Limei Song
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- School of Medical ImagingWeifang Medical UniversityWeifangChina
| | - Yun Peng
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Minhui Ouyang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Qinmu Peng
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Lei Feng
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Susan Sotardi
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Qinlin Yu
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Huiying Kang
- Department of Radiology, Beijing Children's HospitalCapital Medical UniversityBeijingChina
| | - Kay L. Sindabizera
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Shuwei Liu
- Research Center for Sectional and Imaging AnatomyShandong University School of MedicineJinanShandongChina
| | - Hao Huang
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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7
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Magondo N, Meintjes EM, Warton FL, Little F, van der Kouwe AJW, Laughton B, Jankiewicz M, Holmes MJ. Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected. Sci Rep 2024; 14:8822. [PMID: 38627570 PMCID: PMC11021525 DOI: 10.1038/s41598-024-58339-6] [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: 07/11/2023] [Accepted: 03/27/2024] [Indexed: 04/19/2024] Open
Abstract
HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to HIV uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.
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Affiliation(s)
- Ndivhuwo Magondo
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
| | - Ernesta M Meintjes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa.
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa.
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa.
| | - Fleur L Warton
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andre J W van der Kouwe
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MI, USA
| | - Barbara Laughton
- Department of Paediatrics and Child Health and Tygerberg Children's Hospital, Faculty of Medicine and Health Sciences, Family Centre for Research with Ubuntu, Stellenbosch University, Stellenbosch, South Africa
| | - Marcin Jankiewicz
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
- ImageTech, Simon Fraser University, Surrey, BC, Canada
| | - Martha J Holmes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
- ImageTech, Simon Fraser University, Surrey, BC, Canada
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8
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Soumier A, Lio G, Demily C. Current and future applications of light-sheet imaging for identifying molecular and developmental processes in autism spectrum disorders. Mol Psychiatry 2024:10.1038/s41380-024-02487-8. [PMID: 38443634 DOI: 10.1038/s41380-024-02487-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 02/09/2024] [Accepted: 02/13/2024] [Indexed: 03/07/2024]
Abstract
Autism spectrum disorder (ASD) is identified by a set of neurodevelopmental divergences that typically affect the social communication domain. ASD is also characterized by heterogeneous cognitive impairments and is associated with cooccurring physical and medical conditions. As behaviors emerge as the brain matures, it is particularly essential to identify any gaps in neurodevelopmental trajectories during early perinatal life. Here, we introduce the potential of light-sheet imaging for studying developmental biology and cross-scale interactions among genetic, cellular, molecular and macroscale levels of circuitry and connectivity. We first report the core principles of light-sheet imaging and the recent progress in studying brain development in preclinical animal models and human organoids. We also present studies using light-sheet imaging to understand the development and function of other organs, such as the skin and gastrointestinal tract. We also provide information on the potential of light-sheet imaging in preclinical drug development. Finally, we speculate on the translational benefits of light-sheet imaging for studying individual brain-body interactions in advancing ASD research and creating personalized interventions.
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Affiliation(s)
- Amelie Soumier
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France.
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France.
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France.
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France.
| | - Guillaume Lio
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
| | - Caroline Demily
- Le Vinatier Hospital Center, 95 boulevard Pinel, 69675, Bron cedex, France
- iMIND, Center of Excellence for Autism, 95 boulevard Pinel, 69675, Bron cedex, France
- Institute of Cognitive Science Marc Jeannerod, CNRS, UMR 5229, 67 boulevard Pinel, 69675, Bron cedex, France
- University Claude Bernard Lyon 1, 43 boulevard du 11 Novembre 1918, 69622, Villeurbanne cedex, France
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9
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McFayden TC, Rutsohn J, Cetin G, Forsen E, Swanson MR, Meera SS, Wolff JJ, Elison JT, Shen MD, Botteron K, Dager SR, Estes A, Gerig G, McKinstry RC, Pandey J, Schultz R, St John T, Styner M, Truong Y, Zwaigenbaum L, Hazlett HC, Piven J, Girault JB. White matter development and language abilities during infancy in autism spectrum disorder. Mol Psychiatry 2024:10.1038/s41380-024-02470-3. [PMID: 38383768 PMCID: PMC11336031 DOI: 10.1038/s41380-024-02470-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 01/24/2024] [Accepted: 01/30/2024] [Indexed: 02/23/2024]
Abstract
White matter (WM) fiber tract differences are present in autism spectrum disorder (ASD) and could be important markers of behavior. One of the earliest phenotypic differences in ASD are language atypicalities. Although language has been linked to WM in typical development, no work has evaluated this association in early ASD. Participants came from the Infant Brain Imaging Study and included 321 infant siblings of children with ASD at high likelihood (HL) for developing ASD; 70 HL infants were later diagnosed with ASD (HL-ASD), and 251 HL infants were not diagnosed with ASD (HL-Neg). A control sample of 140 low likelihood infants not diagnosed with ASD (LL-Neg) were also included. Infants contributed expressive language, receptive language, and diffusion tensor imaging data at 6-, 12-, and 24 months. Mixed effects regression models were conducted to evaluate associations between WM and language trajectories. Trajectories of microstructural changes in the right arcuate fasciculus were associated with expressive language development. HL-ASD infants demonstrated a different developmental pattern compared to the HL-Neg and LL-Neg groups, wherein the HL-ASD group exhibited a positive association between WM fractional anisotropy and language whereas HL-Neg and LL-Neg groups showed weak or no association. No other fiber tracts demonstrated significant associations with language. In conclusion, results indicated arcuate fasciculus WM is linked to language in early toddlerhood for autistic toddlers, with the strongest associations emerging around 24 months. To our knowledge, this is the first study to evaluate associations between language and WM development during the pre-symptomatic period in ASD.
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Affiliation(s)
- Tyler C McFayden
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA.
| | - Joshua Rutsohn
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gizem Cetin
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA
| | - Elizabeth Forsen
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Meghan R Swanson
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Shoba S Meera
- Department of Speech Pathology and Audiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Jason J Wolff
- Department of Educational Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Mark D Shen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA
| | - Kelly Botteron
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Stephen R Dager
- Department of Radiology, University of Washington, Seattle, WA, USA
- Institute on Human Development and Disability, University of Washington, Seattle, WA, USA
| | - Annette Estes
- Institute on Human Development and Disability, University of Washington, Seattle, WA, USA
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, USA
| | - Guido Gerig
- Tandon School of Engineering, New York University, New York, NY, USA
| | - Robert C McKinstry
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Juhi Pandey
- Center for Autism Research, The Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA
| | - Robert Schultz
- Center for Autism Research, The Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA, USA
| | - Tanya St John
- Institute on Human Development and Disability, University of Washington, Seattle, WA, USA
- Department of Speech and Hearing Sciences, University of Washington, Seattle, WA, USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Young Truong
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Heather C Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA
| | - Jessica B Girault
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Carrboro, NC, USA
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10
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Magondo N, Meintjes EM, Warton FL, Little F, van der Kouwe AJ, Laughton B, Jankiewicz M, Holmes MJ. Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575169. [PMID: 38260347 PMCID: PMC10802593 DOI: 10.1101/2024.01.11.575169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
HIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to uninfected unexposed (HUU) populations. The effects of exposure to in utero HIV and ART regimens on the HEU the developing brain are not well understood. In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposure in utero on neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter. We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpre group compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpost group, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU. Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.
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Affiliation(s)
- Ndivhuwo Magondo
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Ernesta M. Meintjes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Fleur L. Warton
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andre J.W. van der Kouwe
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA,USA
- Department of Radiology, Harvard Medical School, Boston, MI, USA
| | - Barbara Laughton
- Family Centre for Research with Ubuntu, Department of Paediatrics and Child Health and Tygerberg Children’s Hospital, Faculty of Medicine and Health Sciences, Stellenbosch University, Stellenbosch,South Africa
| | - Marcin Jankiewicz
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
- ImageTech, Simon Fraser University, Surrey, BC, Canada
| | - Martha J. Holmes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, BC, Canada
- ImageTech, Simon Fraser University, Surrey, BC, Canada
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11
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Bagautdinova J, Bourque J, Sydnor VJ, Cieslak M, Alexander-Bloch AF, Bertolero MA, Cook PA, Gur RE, Gur RC, Hu F, Larsen B, Moore TM, Radhakrishnan H, Roalf DR, Shinohara RT, Tapera TM, Zhao C, Sotiras A, Davatzikos C, Satterthwaite TD. Development of white matter fiber covariance networks supports executive function in youth. Cell Rep 2023; 42:113487. [PMID: 37995188 PMCID: PMC10795769 DOI: 10.1016/j.celrep.2023.113487] [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: 04/14/2023] [Revised: 10/05/2023] [Accepted: 11/09/2023] [Indexed: 11/25/2023] Open
Abstract
During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.
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Affiliation(s)
- Joëlle Bagautdinova
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Josiane Bourque
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron F Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Maxwell A Bertolero
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Philip A Cook
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Fengling Hu
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Hamsanandini Radhakrishnan
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russel T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Chenying Zhao
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63130, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Lifespan Brain Institute (LiBI) of Penn Medicine and Children's Hospital of Philadelphia (CHOP), University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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12
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Grotheer M, Bloom D, Kruper J, Richie-Halford A, Zika S, Aguilera González VA, Yeatman JD, Grill-Spector K, Rokem A. Human white matter myelinates faster in utero than ex utero. Proc Natl Acad Sci U S A 2023; 120:e2303491120. [PMID: 37549280 PMCID: PMC10438384 DOI: 10.1073/pnas.2303491120] [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: 03/02/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023] Open
Abstract
The formation of myelin, the fatty sheath that insulates nerve fibers, is critical for healthy brain function. A fundamental open question is what impact being born has on myelin growth. To address this, we evaluated a large (n = 300) cross-sectional sample of newborns from the Developing Human Connectome Project (dHCP). First, we developed software for the automated identification of 20 white matter bundles in individual newborns that is well suited for large samples. Next, we fit linear models that quantify how T1w/T2w (a myelin-sensitive imaging contrast) changes over time at each point along the bundles. We found faster growth of T1w/T2w along the lengths of all bundles before birth than right after birth. Further, in a separate longitudinal sample of preterm infants (N = 34), we found lower T1w/T2w than in full-term peers measured at the same age. By applying the linear models fit on the cross-section sample to the longitudinal sample of preterm infants, we find that their delay in T1w/T2w growth is well explained by the amount of time they spent developing in utero and ex utero. These results suggest that white matter myelinates faster in utero than ex utero. The reduced rate of myelin growth after birth, in turn, explains lower myelin content in individuals born preterm and could account for long-term cognitive, neurological, and developmental consequences of preterm birth. We hypothesize that closely matching the environment of infants born preterm to what they would have experienced in the womb may reduce delays in myelin growth and hence improve developmental outcomes.
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Affiliation(s)
- Mareike Grotheer
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - David Bloom
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - John Kruper
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Adam Richie-Halford
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
| | - Stephanie Zika
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Vicente A. Aguilera González
- Department of Psychology, Philipps-Universität Marburg, Marburg35039, Germany
- Center for Mind, Brain and Behavior, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg35039, Germany
| | - Jason D. Yeatman
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
- Graduate School of Education, Stanford University, Stanford, CA94305
- Division of Developmental-Behavioral Pediatrics, Stanford University School of Medicine, Stanford, CA94305
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA94305
| | - Ariel Rokem
- Department of Psychology, University of Washington, Seattle, WA98105
- eScience Institute, University of Washington, Seattle, WA98105
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13
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Banihashemi L, Schmithorst VJ, Bertocci MA, Samolyk A, Zhang Y, Lima Santos JP, Versace A, Taylor M, English G, Northrup JB, Lee VK, Stiffler R, Aslam H, Panigrahy A, Hipwell AE, Phillips ML. Neural Network Functional Interactions Mediate or Suppress White Matter-Emotional Behavior Relationships in Infants. Biol Psychiatry 2023; 94:57-67. [PMID: 36918062 PMCID: PMC10365319 DOI: 10.1016/j.biopsych.2023.03.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 02/28/2023] [Accepted: 03/02/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND Elucidating the neural basis of infant positive emotionality and negative emotionality can identify biomarkers of pathophysiological risk. Our goal was to determine how functional interactions among large-scale networks supporting emotional regulation influence white matter (WM) microstructural-emotional behavior relationships in 3-month-old infants. We hypothesized that microstructural-emotional behavior relationships would be differentially mediated or suppressed by underlying resting-state functional connectivity (rsFC), particularly between default mode network and central executive network structures. METHODS The analytic sample comprised primary caregiver-infant dyads (52 infants [42% female, mean age at scan = 15.10 weeks]), with infant neuroimaging and emotional behavior assessments conducted at 3 months. Infant WM and rsFC were assessed by diffusion-weighted imaging/tractography and resting-state magnetic resonance imaging during natural, nonsedated sleep. The Infant Behavior Questionnaire-Revised provided measures of infant positive emotionality and negative emotionality. RESULTS After significant WM-emotional behavior relationships were observed, multimodal analyses were performed using whole-brain voxelwise mediation. Results revealed that greater cingulum bundle volume was significantly associated with lower infant positive emotionality (β = -0.263, p = .031); however, a pattern of lower rsFC between central executive network and default mode network structures suppressed this otherwise negative relationship. Greater uncinate fasciculus volume was significantly associated with lower infant negative emotionality (β = -0.296, p = .022); however, lower orbitofrontal cortex-amygdala rsFC suppressed this otherwise negative relationship, while greater orbitofrontal cortex-central executive network rsFC mediated this relationship. CONCLUSIONS Functional interactions among neural networks have an important influence on WM microstructural-emotional behavior relationships in infancy. These relationships can elucidate neural mechanisms that contribute to future behavioral and emotional problems in childhood.
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Affiliation(s)
- Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
| | - Vanessa J Schmithorst
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Michele A Bertocci
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Alyssa Samolyk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Yicheng Zhang
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - João Paulo Lima Santos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Megan Taylor
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gabrielle English
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Jessie B Northrup
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Vincent K Lee
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Richelle Stiffler
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Haris Aslam
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Ashok Panigrahy
- Department of Pediatric Radiology, University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alison E Hipwell
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
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14
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Sa de Almeida J, Baud O, Fau S, Barcos-Munoz F, Courvoisier S, Lordier L, Lazeyras F, Hüppi PS. Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study. Dev Cogn Neurosci 2023; 61:101254. [PMID: 37182337 DOI: 10.1016/j.dcn.2023.101254] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/25/2023] [Accepted: 05/09/2023] [Indexed: 05/16/2023] Open
Abstract
Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.
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Affiliation(s)
- Joana Sa de Almeida
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland.
| | - Olivier Baud
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Sebastien Fau
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Francisca Barcos-Munoz
- Division of Neonatal and Intensive Care, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - Sebastien Courvoisier
- Center of BioMedical Imaging (CIBM), University of Geneva, Geneva, Switzerland; Department of Radiology and Medical Informatics, Geneva, Switzerland
| | - Lara Lordier
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
| | - François Lazeyras
- Center of BioMedical Imaging (CIBM), University of Geneva, Geneva, Switzerland; Department of Radiology and Medical Informatics, Geneva, Switzerland
| | - Petra S Hüppi
- Division of Development and Growth, Department of Paediatrics, Gynecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland
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Onda K, Chavez-Valdez R, Graham EM, Everett AD, Northington FJ, Oishi K. Quantification of Diffusion Magnetic Resonance Imaging for Prognostic Prediction of Neonatal Hypoxic-Ischemic Encephalopathy. Dev Neurosci 2023; 46:55-68. [PMID: 37231858 PMCID: PMC10712961 DOI: 10.1159/000530938] [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: 10/18/2022] [Accepted: 02/20/2023] [Indexed: 05/27/2023] Open
Abstract
Neonatal hypoxic-ischemic encephalopathy (HIE) is the leading cause of acquired neonatal brain injury with the risk of developing serious neurological sequelae and death. An accurate and robust prediction of short- and long-term outcomes may provide clinicians and families with fundamental evidence for their decision-making, the design of treatment strategies, and the discussion of developmental intervention plans after discharge. Diffusion tensor imaging (DTI) is one of the most powerful neuroimaging tools with which to predict the prognosis of neonatal HIE by providing microscopic features that cannot be assessed by conventional magnetic resonance imaging (MRI). DTI provides various scalar measures that represent the properties of the tissue, such as fractional anisotropy (FA) and mean diffusivity (MD). Since the characteristics of the diffusion of water molecules represented by these measures are affected by the microscopic cellular and extracellular environment, such as the orientation of structural components and cell density, they are often used to study the normal developmental trajectory of the brain and as indicators of various tissue damage, including HIE-related pathologies, such as cytotoxic edema, vascular edema, inflammation, cell death, and Wallerian degeneration. Previous studies have demonstrated widespread alteration in DTI measurements in severe cases of HIE and more localized changes in neonates with mild-to-moderate HIE. In an attempt to establish cutoff values to predict the occurrence of neurological sequelae, MD and FA measurements in the corpus callosum, thalamus, basal ganglia, corticospinal tract, and frontal white matter have proven to have an excellent ability to predict severe neurological outcomes. In addition, a recent study has suggested that a data-driven, unbiased approach using machine learning techniques on features obtained from whole-brain image quantification may accurately predict the prognosis of HIE, including for mild-to-moderate cases. Further efforts are needed to overcome current challenges, such as MRI infrastructure, diffusion modeling methods, and data harmonization for clinical application. In addition, external validation of predictive models is essential for clinical application of DTI to prognostication.
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Affiliation(s)
- Kengo Onda
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Raul Chavez-Valdez
- Neuroscience Intensive Care Nursery Program, Division of Neonatology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pediatrics, Division of Neonatology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ernest M. Graham
- Department of Gynecology & Obstetrics, Division of Maternal-Fetal Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Allen D. Everett
- Department of Pediatrics, Division of Pediatric Cardiology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Frances J. Northington
- Neuroscience Intensive Care Nursery Program, Division of Neonatology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pediatrics, Division of Neonatology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kenichi Oishi
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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16
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Drobyshevsky A, Synowiec S, Goussakov I, Lu J, Gascoigne D, Aksenov DP, Yarnykh V. Temporal trajectories of normal myelination and axonal development assessed by quantitative macromolecular and diffusion MRI: Ultrastructural and immunochemical validation in a rabbit model. Neuroimage 2023; 270:119974. [PMID: 36848973 PMCID: PMC10103444 DOI: 10.1016/j.neuroimage.2023.119974] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 02/27/2023] Open
Abstract
INTRODUCTION Quantitative and non-invasive measures of brain myelination and maturation during development are of great importance to both clinical and translational research communities. While the metrics derived from diffusion tensor imaging, are sensitive to developmental changes and some pathologies, they remain difficult to relate to the actual microstructure of the brain tissue. The advent of advanced model-based microstructural metrics requires histological validation. The purpose of the study was to validate novel, model-based MRI techniques, such as macromolecular proton fraction mapping (MPF) and neurite orientation and dispersion indexing (NODDI), against histologically derived indexes of myelination and microstructural maturation at various stages of development. METHODS New Zealand White rabbit kits underwent serial in-vivo MRI examination at postnatal days 1, 5, 11, 18, and 25, and as adults. Multi-shell, diffusion-weighted experiments were processed to fit NODDI model to obtain estimates, intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Macromolecular proton fraction (MPF) maps were obtained from three source (MT-, PD-, and T1-weighted) images. After MRI sessions, a subset of animals was euthanized and regional samples of gray and white matter were taken for western blot analysis, to determine myelin basic protein (MBP), and electron microscopy, to estimate axonal, myelin fractions and g-ratio. RESULTS MPF of white matter regions showed a period of fast growth between P5 and P11 in the internal capsule, with a later onset in the corpus callosum. This MPF trajectory was in agreement with levels of myelination in the corresponding brain region, as assessed by western blot and electron microscopy. In the cortex, the greatest increase of MPF occurred between P18 and P26. In contrast, myelin, according to MBP western blot, saw the largest hike between P5 and P11 in the sensorimotor cortex and between P11 and P18 in the frontal cortex, which then seemingly plateaued after P11 and P18 respectively. G-ratio by MRI markers decreased with age in the white matter. However, electron microscopy suggest a relatively stable g-ratio throughout development. CONCLUSION Developmental trajectories of MPF accurately reflected regional differences of myelination rate in different cortical regions and white matter tracts. MRI-derived estimation of g-ratio was inaccurate during early development, likely due to the overestimation of axonal volume fraction by NODDI due to the presence of a large proportion of unmyelinated axons.
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Affiliation(s)
- Alexander Drobyshevsky
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA.
| | - Sylvia Synowiec
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Ivan Goussakov
- Department of Pediatrics, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Jing Lu
- Department of Pediatrics, University of Chicago, Chicago, IL, USA
| | - David Gascoigne
- Center for Basic MR Research, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Daniil P Aksenov
- Center for Basic MR Research, NorthShore University HealthSystem Research Institute, Evanston, IL, USA
| | - Vasily Yarnykh
- Department of Radiology, University of Washington, Seattle, WA, USA
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Corpus callosum organization and its implication to core and co-occurring symptoms of Autism Spectrum Disorder. Brain Struct Funct 2023; 228:775-785. [PMID: 36867240 DOI: 10.1007/s00429-023-02617-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 01/31/2023] [Indexed: 03/04/2023]
Abstract
Autism Spectrum Disorder (ASD) is characterized by social interaction and communication deficits, repetitive behavior and often by co-occurring conditions such as language and non-verbal IQ development delays. Previous studies reported that those behavioral abnormalities can be associated with corpus callosum organization. However, little is known about the specific differences in white matter structure of the corpus callosum parts in children with ASD and TD peers and their relationships to core and co-occurring symptoms of ASD. The aim of the study was to investigate the volumetric and microstructural characteristics of the corpus callosum parts crucially involved in social, language, and non-verbal IQ behavior in primary-school-aged children with ASD and to assess the relationships between these characteristics and behavioral measures. 38 children (19 with ASD and 19 typically developing (TD) controls) were scanned using diffusion-weighted MRI and assessed with behavioral tests. The tractography of the corpus callosum parts were performed using Quantitative Imaging Toolkit software; diffusivity and volumetric measurements were extracted for the analysis. In the ASD group, fractional anisotropy (FA) was decreased across the supplementary motor area and the ventromedial prefrontal cortex, and axial diffusivity (AD) was reduced across each of the corpus callosum parts in comparison to the TD group. Importantly, the AD decrease was related to worse language skills and more severe autistic traits in individuals with ASD. The microstructure of the corpus callosum parts differs between children with and without ASD. Abnormalities in white matter organization of the corpus callosum parts are associated with core and co-occurring symptoms of ASD.
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18
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DiPiero M, Rodrigues PG, Gromala A, Dean DC. Applications of advanced diffusion MRI in early brain development: a comprehensive review. Brain Struct Funct 2023; 228:367-392. [PMID: 36585970 PMCID: PMC9974794 DOI: 10.1007/s00429-022-02605-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/21/2022] [Indexed: 01/01/2023]
Abstract
Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.
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Affiliation(s)
- Marissa DiPiero
- Department of Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Alyssa Gromala
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Douglas C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, 53705, USA.
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19
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Zhu T, Simonetti A, Ouyang M, Kurian S, Saxena J, Soares JC, Saxena K, Huang H. Disrupted white matter microstructure correlates with impulsivity in children and adolescents with bipolar disorder. J Psychiatr Res 2023; 158:71-80. [PMID: 36577236 PMCID: PMC9898209 DOI: 10.1016/j.jpsychires.2022.12.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/29/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
Altered white matter (WM) microstructure likely occurs in children with bipolar disorder (BD) with impulsivity representing one of the core features. However, altered WM microstructures and their age-related trendlines in children with BD and those at high-risk of developing BD, as well as correlations of WM microstructures with impulsivity, have been poorly investigated. In this study, diffusion MRI, cognitive, and impulsivity assessments were obtained from children/adolescents diagnosed with BD, offspring of individuals with BD (high-risk BD) and age-matched healthy controls. A novel atlas-based WM skeleton measurement approach was used to quantify WM microstructural integrity with all diffusion-tensor-imaging (DTI) metrics including fractional anisotropy, axial, mean and radial diffusivity to survey entire WM tracts and ameliorate partial volume effects. Among all DTI-derived metric measures, radial diffusivity quantifying WM myelination was found significantly higher primarily in corpus callosum and in the corona radiata in children with BD compared to controls. Distinguished from age-related progressively decreasing diffusivities and increasing fractional anisotropy in healthy controls, flattened age-related trendlines were found in BD group, and intermediate developmental rates were observed in high-risk group. Larger radial diffusivity in the corpus callosum and corona radiata significantly correlated with shorter response times to affective words that indicate higher impulsivity in the BD group, whereas no such correlation was found in the healthy control group. This work corroborates the progressive nature of pediatric BD and suggests that WM microstructural disruption involved in affective regulation and sensitive to impulsivity may serve as a biomarker of pediatric BD progression.
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Affiliation(s)
- Tianjia Zhu
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA
| | - Alessio Simonetti
- Department of Neuroscience, Section of Psychiatry, Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, Rome, Italy; Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sherin Kurian
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
| | - Johanna Saxena
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA
| | - Jair C Soares
- Department of Psychiatry, McGovern Medical School at UTHealth, Houston, TX, USA
| | - Kirti Saxena
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA; Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA.
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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20
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Wang X, Liu X, Cheng M, Xuan D, Zhao X, Zhang X. Application of diffusion kurtosis imaging in neonatal brain development. Front Pediatr 2023; 11:1112121. [PMID: 37051430 PMCID: PMC10083282 DOI: 10.3389/fped.2023.1112121] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/13/2023] [Indexed: 04/14/2023] Open
Abstract
Background Deviations from the regular pattern of growth and development could lead to early childhood diseases, suggesting the importance of evaluating early brain development. Through this study, we aimed to explore the changing patterns of white matter and gray matter during neonatal brain development using diffusion kurtosis imaging (DKI). Materials and methods In total, 42 full-term neonates (within 28 days of birth) underwent conventional brain magnetic resonance imaging (MRI) and DKI. The DKI metrics (including kurtosis parameters and diffusion parameters) of white matter and deep gray matter were measured. DKI metrics from the different regions of interest (ROIs) were evaluated using the Kruskal-Wallis test and Bonferroni method. Spearman rank correlation analysis of the DKI metrics was conducted, and the age at the time of brain MRI acquisition was calculated. The subjects were divided into three groups according to their age at the time of brain MRI acquisition: the first group, neonates aged ≤7 days; the second group, neonates aged 8-14 days; and the third group, neonates aged 15-28 days. The rate of change in DKI metrics relative to the first group was computed. Results The mean kurtosis (MK), axial kurtosis (Ka), radial kurtosis (Kr), and fractional anisotropy (FA) values showed positive correlations, whereas mean diffusion (MD), axial diffusion (Da), and radial diffusion (Dr) values showed negative correlations with the age at the time of brain MRI acquisition. The absolute correlation coefficients between MK values of almost all ROIs (except genu of the corpus callosum and frontal white matter) and the age at the time of brain MRI acquisition were greater than other metrics. The kurtosis parameters and FA values of central white matter were significantly higher than that of peripheral white matter, whereas the MD and Dr values were significantly lower than that of peripheral white matter. The MK value of the posterior limb of the internal capsule was the highest among the white matter areas. The FA value of the splenium of the corpus callosum was significantly higher than that of the other white matter areas. The kurtosis parameters and FA values of globus pallidus and thalamus were significantly higher than those of the caudate nucleus and putamen, whereas the Da and Dr values of globus pallidus and thalamus were significantly lower than those of the caudate nucleus and putamen. The relative change rates of kurtosis parameters and FA values of all ROIs were greater than those of MD, Da, and Dr values. The amplitude of MK values of almost all ROIs (except for the genu of the corpus callosum and central white matter of the centrum semiovale level) was greater than that of other metrics. The relative change rates of the Kr values of most ROIs were greater than those of the Ka value, and the relative change rates of the Dr values of most ROIs were greater than those of the Da value. Conclusion DKI parameters showed potential advantages in detecting the changes in brain microstructure during neonatal brain development.
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Affiliation(s)
- Xueyuan Wang
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Xianglong Liu
- Department of Radiology, Zhengzhou Central Hospital Affiliated to Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Desheng Xuan
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
- Correspondence: Xin Zhao Xiaoan Zhang
| | - Xiaoan Zhang
- Department of Radiology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
- Correspondence: Xin Zhao Xiaoan Zhang
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21
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Chen R, Sun C, Liu T, Liao Y, Wang J, Sun Y, Zhang Y, Wang G, Wu D. Deciphering the developmental order and microstructural patterns of early white matter pathways in a diffusion MRI based fetal brain atlas. Neuroimage 2022; 264:119700. [PMID: 36270621 DOI: 10.1016/j.neuroimage.2022.119700] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2022] [Revised: 10/14/2022] [Accepted: 10/18/2022] [Indexed: 11/09/2022] Open
Abstract
White matter (WM) of the fetal brain undergoes rapid development to form early structural connections. Diffusion magnetic resonance imaging (dMRI) has shown to be a useful tool to depict fetal brain WM in utero, and many studies have observed increasing fractional anisotropy and decreasing diffusivity in the fetal brain during the second-to-third trimester, whereas others reported non-monotonic changes. Unbiased dMRI atlases of the fetal brain are important for characterizing the developmental trajectories of WM and providing normative references for in utero diagnosis of prenatal abnormalities. To date, the sole fetal brain dMRI atlas was collected from a Caucasian/mixed population and was constructed based on the diffusion tensor model with limited spatial resolution. In this work, we proposed a fiber orientation distribution (FOD) based pipeline for generating fetal brain dMRI atlases, which showed better registration accuracy than a diffusion tensor based pipeline. Based on the FOD-based pipeline, we constructed the first Chinese fetal brain dMRI atlas using 89 dMRI scans of normal fetuses at gestational age between 24 and 38 weeks. Complex non-monotonic trends of tensor- and FOD-derived microstructural parameters in eight WM tracts were observed, which jointly pointed to different phases of microstructural development. Specifically, we speculated that the turning point of the diffusivity trajectory may correspond to the starting point of pre-myelination, based on which, the developmental order of WM tracts can be mapped and the order was in agreement with the order of myelination from histological studies. The normative atlas also provided a reference for the detection of abnormal WM development, such as that in congenital heart disease. Therefore, the established high-order fetal brain dMRI atlas depicted the spatiotemporal pattern of early WM development, and findings may help decipher the distinct microstructural events in utero.
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Affiliation(s)
- Ruike Chen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Cong Sun
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Tingting Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuhao Liao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | | | - Yi Sun
- MR Collaboration, Siemens Healthineers Ltd., Shanghai, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China
| | - Guangbin Wang
- Department of Radiology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, China.
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22
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Jang YH, Kim H, Lee JY, Ahn JH, Chung AW, Lee HJ. Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants. Cereb Cortex 2022; 33:5507-5523. [PMID: 36408630 DOI: 10.1093/cercor/bhac438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.
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Affiliation(s)
- Yong Hun Jang
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Hyuna Kim
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Joo Young Lee
- Hanyang University Graduate School of Biomedical Science and Engineering Department of Translational Medicine, , Seoul 04763 , Republic of Korea
| | - Ja-Hye Ahn
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
| | - Ai Wern Chung
- Harvard Medical School Fetal Neonatal-Neuroimaging and Developmental Science Center, Boston Children’s Hospital, , Boston, MA 02115 , USA
- Harvard Medical School Department of Pediatrics, Boston Children’s Hospital, , Boston, MA 02115 , USA
| | - Hyun Ju Lee
- Hanyang University College of Medicine Department of Pediatrics, Hanyang University Hospital, , Seoul 04763 , Republic of Korea
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23
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Wang J, Nichols ES, Mueller ME, de Vrijer B, Eagleson R, McKenzie CA, de Ribaupierre S, Duerden EG. Semi-automatic segmentation of the fetal brain from magnetic resonance imaging. Front Neurosci 2022; 16:1027084. [PMID: 36440277 PMCID: PMC9692018 DOI: 10.3389/fnins.2022.1027084] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/19/2022] [Indexed: 11/13/2023] Open
Abstract
BACKGROUND Volumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings. METHODS Adult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9-36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB's Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman's test for repeated measures. RESULTS Comparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6-0.8] and 0.54 (IQR = 0.4-0.6), respectively. A Friedman's test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p < 0.001). CONCLUSION Deformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development.
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Affiliation(s)
- Jianan Wang
- Biomedical Engineering, Western University, London, ON, Canada
| | - Emily S. Nichols
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
| | - Megan E. Mueller
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
| | - Barbra de Vrijer
- Department of Obstetrics and Gynaecology, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Roy Eagleson
- Biomedical Engineering, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
- Department of Electrical and Computer Engineering, Western University, London, ON, Canada
| | - Charles A. McKenzie
- Department of Medical Biophysics, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Sandrine de Ribaupierre
- Biomedical Engineering, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
- Department of Anatomy and Cell Biology, Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Emma G. Duerden
- Biomedical Engineering, Western University, London, ON, Canada
- Applied Psychology, Faculty of Education, Western University, London, ON, Canada
- Western Institute for Neuroscience, Western University, London, ON, Canada
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24
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Liang W, Yu Q, Wang W, Dhollander T, Suluba E, Li Z, Xu F, Hu Y, Tang Y, Liu S. A comparative study of the superior longitudinal fasciculus subdivisions between neonates and young adults. Brain Struct Funct 2022; 227:2713-2730. [PMID: 36114859 PMCID: PMC9618541 DOI: 10.1007/s00429-022-02565-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 09/03/2022] [Indexed: 12/04/2022]
Abstract
The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.
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Affiliation(s)
- Wenjia Liang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Qiaowen Yu
- Department of Medical Imaging, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Wenjun Wang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Thijs Dhollander
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Emmanuel Suluba
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Zhuoran Li
- Department of Ultrasound, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, 250021, China
| | - Feifei Xu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yang Hu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China
| | - Yuchun Tang
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
| | - Shuwei Liu
- Department of Anatomy and Neurobiology, Research Center for Sectional and Imaging Anatomy, Shandong Key Laboratory of Mental Disorders, Shandong Key Laboratory of Digital Human and Clinical Anatomy, School of Basic Medical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, China.
- Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, 250012, China.
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25
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Warrington S, Thompson E, Bastiani M, Dubois J, Baxter L, Slater R, Jbabdi S, Mars RB, Sotiropoulos SN. Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications. SCIENCE ADVANCES 2022; 8:eabq2022. [PMID: 36260675 PMCID: PMC9581484 DOI: 10.1126/sciadv.abq2022] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 08/31/2022] [Indexed: 06/16/2023]
Abstract
Developmental and evolutionary effects on brain organization are complex, yet linked, as evidenced by the correspondence in cortical area expansion across these vastly different time scales. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric measurements. Here, we propose a novel framework that allows the integration of structural connectivity maps from humans (adults and neonates) and nonhuman primates (macaques) onto a common space. We use white matter bundles to anchor the common space and use the uniqueness of cortical connection patterns to these bundles to probe area specialization. This enabled us to quantitatively study divergences and similarities in connectivity over evolutionary and developmental scales, to reveal brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains. Our findings open new avenues for an integrative approach to imaging neuroanatomy.
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Affiliation(s)
- Shaun Warrington
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Elinor Thompson
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Matteo Bastiani
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jessica Dubois
- Université Paris Cité, Inserm, NeuroDiderot Unit, Paris, France
- University Paris-Saclay, CEA, NeuroSpin, Gif-sur-Yvette, France
| | - Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rogier B. Mars
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Stamatios N. Sotiropoulos
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
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26
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Corroenne R, Arthuis C, Kasprian G, Mahallati H, Ville Y, Millischer Bellaiche AE, Henry C, Grevent D, Salomon LJ. Diffusion tensor imaging of fetal brain: principles, potential and limitations of promising technique. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2022; 60:470-476. [PMID: 35561129 DOI: 10.1002/uog.24935] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 04/24/2022] [Accepted: 04/29/2022] [Indexed: 06/15/2023]
Abstract
Human brain development is a complex process that begins in the third week of gestation. During early development, the fetal brain undergoes dynamic morphological changes. These changes result from events such as neurogenesis, neuronal migration, synapse formation, axonal growth and myelination. Disruption of any of these processes is thought to be responsible for a wide array of different pathologies. Recent advances in magnetic resonance imaging, especially diffusion-weighted imaging and diffusion tensor imaging (DTI), have enabled characterization and evaluation of brain development in utero. In this review, aimed at practitioners involved in fetal medicine and high-risk pregnancies, we provide a comprehensive overview of fetal DTI studies focusing on characterization of early normal brain development as well as evaluation of brain pathology in utero. We also discuss the reliability and limitations of fetal brain DTI. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- R Corroenne
- Department of Obstetrics, Fetal Medicine and Surgery, Necker-Enfants Malades Hospital, APHP, Paris, France
- EA FETUS 7328 and LUMIERE Platform, University of Paris, Paris, France
| | - C Arthuis
- EA FETUS 7328 and LUMIERE Platform, University of Paris, Paris, France
- Department of Obstetrics, University Hospital of Nantes, Nantes, France
| | - G Kasprian
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - H Mahallati
- Department of Radiology, University of Calgary, Calgary, Canada
| | - Y Ville
- Department of Obstetrics, Fetal Medicine and Surgery, Necker-Enfants Malades Hospital, APHP, Paris, France
| | | | - C Henry
- EA FETUS 7328 and LUMIERE Platform, University of Paris, Paris, France
| | - D Grevent
- EA FETUS 7328 and LUMIERE Platform, University of Paris, Paris, France
- Department of Radiology, Necker-Enfants Malades Hospital, APHP, Paris, France
| | - L J Salomon
- Department of Obstetrics, Fetal Medicine and Surgery, Necker-Enfants Malades Hospital, APHP, Paris, France
- EA FETUS 7328 and LUMIERE Platform, University of Paris, Paris, France
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27
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Iwata S, Katayama R, Tsuda K, Lin YC, Kurata T, Kinoshita M, Kawase K, Kato T, Kato S, Hisano T, Oda M, Ohmae E, Takashima S, Araki Y, Saitoh S, Iwata O. Near-infrared light scattering and water diffusion in newborn brains. Ann Clin Transl Neurol 2022; 9:1417-1427. [PMID: 35943446 PMCID: PMC9463954 DOI: 10.1002/acn3.51641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 07/19/2022] [Indexed: 11/26/2022] Open
Abstract
Objective MRI provides useful information regarding brain maturation and injury in newborn infants. However, MRI studies are generally restricted during acute phase, resulting in uncertainty around upstream clinical events responsible for subtle cerebral injuries. Time‐resolved near‐infrared spectroscopy non‐invasively provides the reduced scattering coefficient (μs′), which theoretically reflects tissue structural complexity. This study aimed to test whether μs′ values of the newborn head reflected MRI findings. Methods Between June 2009 and January 2015, 77 hospitalised newborn infants (31.7 ± 3.8 weeks gestation) were assessed at 38.8 ± 1.3 weeks post‐conceptional age. Associations of μs′ values with MRI scores, mean diffusivity and fractional anisotropy were assessed. Results Univariable analysis showed that μs′ values were associated with gestational week (p = 0.035; regression coefficient [B], 0.065; 95% confidence interval [CI], 0.005–0.125), fractional anisotropy in the cortical grey matter (p = 0.020; B, −5.994; 95%CI, −11.032 to −0.957), average diffusivity in the cortical grey matter (p < 0.001; B, −4.728; 95%CI, −7.063 to −2.394) and subcortical white matter (p = 0.001; B, −2.071; 95%CI, −3.311 to −0.832), subarachnoid space (p < 0.001; B, −0.289; 95%CI, −0.376 to −0.201) and absence of brain abnormality (p = 0.042; B, −0.422; 95%CI, −0.829 to −0.015). The multivariable model to explain μs′ values comprised average diffusivity in the subcortical white matter (p < 0.001; B, −2.066; 95%CI, −3.200 to −0.932), subarachnoid space (p < 0.001; B, −0.314; 95%CI, −0.412 to −0.216) and absence of brain abnormality (p = 0.021; B, −0.400; 95%CI, −0.739 to −0.061). Interpretation Light scattering was associated with brain structure indicated by MRI‐assessed brain abnormality and diffusion‐tensor‐imaging‐assessed water diffusivity. When serially assessed in a larger population, μs′ values might help identify covert clinical events responsible for subtle cerebral injury.
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Affiliation(s)
- Sachiko Iwata
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Reiji Katayama
- Centre for the Study of Medical Education, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Kennosuke Tsuda
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Yung-Chieh Lin
- Department of Pediatrics, National Cheng Kung University Hospital, College of Medicine, National Cheng-Kung University, Tainan, 70457, Taiwan
| | - Tsuyoshi Kurata
- Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Masahiro Kinoshita
- Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
| | - Koya Kawase
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Takenori Kato
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Shin Kato
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Tadashi Hisano
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Motoki Oda
- Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Shizuoka, 434-8601, Japan
| | - Etsuko Ohmae
- Central Research Laboratory, Hamamatsu Photonics K.K., Hamamatsu, Shizuoka, 434-8601, Japan
| | - Sachio Takashima
- Yanagawa Institute for Developmental Disabilities, International University of Health and Welfare, Yanagawa, Fukuoka, 832-0813, Japan
| | - Yuko Araki
- Graduate School of Information Sciences, Tohoku University, Sendai City, Miyagi, 980-8579, Japan
| | - Shinji Saitoh
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan
| | - Osuke Iwata
- Center for Human Development and Family Science, Department of Pediatrics and Neonatology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Aichi, 467-8601, Japan.,Department of Paediatrics and Child Health, Centre for Developmental and Cognitive Neuroscience, Kurume University School of Medicine, Kurume, Fukuoka, 830-0011, Japan
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28
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Schmidbauer VU, Yildirim MS, Dovjak GO, Goeral K, Buchmayer J, Weber M, Diogo MC, Giordano V, Mayr-Geisl G, Prayer F, Stuempflen M, Lindenlaub F, List V, Glatter S, Rauscher A, Stuhr F, Lindner C, Klebermass-Schrehof K, Berger A, Prayer D, Kasprian G. Different from the Beginning: WM Maturity of Female and Male Extremely Preterm Neonates-A Quantitative MRI Study. AJNR Am J Neuroradiol 2022; 43:611-619. [PMID: 35332014 PMCID: PMC8993206 DOI: 10.3174/ajnr.a7472] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Accepted: 01/25/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND AND PURPOSE Former preterm born males are at higher risk for neurodevelopmental disabilities compared with female infants born at the same gestational age. This retrospective study investigated sex-related differences in the maturity of early myelinating brain regions in infants born <28 weeks' gestational age using diffusion tensor- and relaxometry-based MR imaging. MATERIALS AND METHODS Quantitative MR imaging sequence acquisitions were analyzed in a sample of 35 extremely preterm neonates imaged at term-equivalent ages. Quantitative MR imaging metrics (fractional anisotropy; ADC [10-3mm2/s]; and T1-/T2-relaxation times [ms]) of the medulla oblongata, pontine tegmentum, midbrain, and the right/left posterior limbs of the internal capsule were determined on diffusion tensor- and multidynamic, multiecho sequence-based imaging data. ANCOVA and a paired t test were used to compare female and male infants and to detect hemispheric developmental asymmetries. RESULTS Seventeen female (mean gestational age at birth: 26 + 0 [SD, 1 + 4] weeks+days) and 18 male (mean gestational age at birth: 26 + 1 [SD, 1 + 3] weeks+days) infants were enrolled in this study. Significant differences were observed in the T2-relaxation time (P = .014) of the pontine tegmentum, T1-relaxation time (P = .011)/T2-relaxation time (P = .024) of the midbrain, and T1-relaxation time (P = .032) of the left posterior limb of the internal capsule. In both sexes, fractional anisotropy (P [♀] < .001/P [♂] < .001) and ADC (P [♀] = .017/P [♂] = .028) differed significantly between the right and left posterior limbs of the internal capsule. CONCLUSIONS The combined use of various quantitative MR imaging metrics detects sex-related and interhemispheric differences of WM maturity. The brainstem and the left posterior limb of the internal capsule of male preterm neonates are more immature compared with those of female infants at term-equivalent ages. Sex differences in WM maturation need further attention for the personalization of neonatal brain imaging.
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Affiliation(s)
- V U Schmidbauer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M S Yildirim
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - G O Dovjak
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - K Goeral
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - J Buchmayer
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - M Weber
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M C Diogo
- Department of Neuroradiology (M.C.D.), Hospital Garcia de Orta, Almada, Portugal
| | - V Giordano
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - G Mayr-Geisl
- Department of Neurosurgery (G.M.-G.), Medical University of Vienna, Vienna, Austria
| | - F Prayer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - M Stuempflen
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - F Lindenlaub
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - V List
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - S Glatter
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - A Rauscher
- Department of Pediatrics (A.R.), University of British Columbia, Vancouver, British Columbia, Canada
| | - F Stuhr
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - C Lindner
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - K Klebermass-Schrehof
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - A Berger
- Comprehensive Center for Pediatrics (K.G., J.B., V.G., V.L., S.G., K.K.-S., A.B.), Department of Pediatrics and Adolescent Medicine, Division of Neonatology, Pediatric Intensive Care and Neuropediatrics
| | - D Prayer
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
| | - G Kasprian
- From the Department of Biomedical Imaging and Image-guided Therapy (V.U.S., M.S.Y., G.O.D., M.W., F.P., M.S., F.L., F.S., C.L., D.P., G.K.)
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29
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Fiber tracing and microstructural characterization among audiovisual integration brain regions in neonates compared with young adults. Neuroimage 2022; 254:119141. [PMID: 35342006 DOI: 10.1016/j.neuroimage.2022.119141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 02/23/2022] [Accepted: 03/21/2022] [Indexed: 11/23/2022] Open
Abstract
Audiovisual integration has been related with cognitive-processing and behavioral advantages, as well as with various socio-cognitive disorders. While some studies have identified brain regions instantiating this ability shortly after birth, little is known about the structural pathways connecting them. The goal of the present study was to reconstruct fiber tracts linking AVI regions in the newborn in-vivo brain and assess their adult-likeness by comparing them with analogous fiber tracts of young adults. We performed probabilistic tractography and compared connective probabilities between a sample of term-born neonates (N = 311; the Developing Human Connectome Project (dHCP, http://www.developingconnectome.org) and young adults (N = 311 The Human Connectome Project; https://www.humanconnectome.org/) by means of a classification algorithm. Furthermore, we computed Dice coefficients to assess between-group spatial similarity of the reconstructed fibers and used diffusion metrics to characterize neonates' AVI brain network in terms of microstructural properties, interhemispheric differences and the association with perinatal covariates and biological sex. Overall, our results indicate that the AVI fiber bundles were successfully reconstructed in a vast majority of neonates, similarly to adults. Connective probability distributional similarities and spatial overlaps of AVI fibers between the two groups differed across the reconstructed fibers. There was a rank-order correspondence of the fibers' connective strengths across the groups. Additionally, the study revealed patterns of diffusion metrics in line with early white matter developmental trajectories and a developmental advantage for females. Altogether, these findings deliver evidence of meaningful structural connections among AVI regions in the newborn in-vivo brain.
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30
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Vo Van P, Alison M, Morel B, Beck J, Bednarek N, Hertz-Pannier L, Loron G. Advanced Brain Imaging in Preterm Infants: A Narrative Review of Microstructural and Connectomic Disruption. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9030356. [PMID: 35327728 PMCID: PMC8947160 DOI: 10.3390/children9030356] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 02/21/2022] [Accepted: 03/02/2022] [Indexed: 11/16/2022]
Abstract
Preterm birth disrupts the in utero environment, preventing the brain from fully developing, thereby causing later cognitive and behavioral disorders. Such cerebral alteration occurs beneath an anatomical scale, and is therefore undetectable by conventional imagery. Prematurity impairs the microstructure and thus the histological process responsible for the maturation, including the myelination. Cerebral MRI diffusion tensor imaging sequences, based on water’s motion into the brain, allows a representation of this maturation process. Similarly, the brain’s connections become disorganized. The connectome gathers structural and anatomical white matter fibers, as well as functional networks referring to remote brain regions connected one over another. Structural and functional connectivity is illustrated by tractography and functional MRI, respectively. Their organizations consist of core nodes connected by edges. This basic distribution is already established in the fetal brain. It evolves greatly over time but is compromised by prematurity. Finally, cerebral plasticity is nurtured by a lifetime experience at microstructural and macrostructural scales. A preterm birth causes a negative and early disruption, though it can be partly mitigated by positive stimuli based on developmental neonatal care.
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Affiliation(s)
- Philippe Vo Van
- Department of Neonatology, Hospices Civils de Lyon, Femme Mère Enfant Hospital, 59 Boulevard Pinel, 69500 Bron, France
- Correspondence:
| | - Marianne Alison
- Service d’Imagerie Pédiatrique, Hôpital Robert Debré, APHP, 75019 Paris, France;
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
| | - Baptiste Morel
- Pediatric Radiology Department, Clocheville Hospital, CHRU of Tours, 37000 Tours, France;
- UMR 1253, iB-Rain, Université de Tours, Inserm, 37000 Tours, France
| | - Jonathan Beck
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Nathalie Bednarek
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Lucie Hertz-Pannier
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
- NeuroSpin, CEA-Saclay, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Gauthier Loron
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
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31
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Li X, Li M, Wang M, Wu F, Liu H, Sun Q, Zhang Y, Liu C, Jin C, Yang J. Mapping white matter maturational processes and degrees on neonates by diffusion kurtosis imaging with multiparametric analysis. Hum Brain Mapp 2022; 43:799-815. [PMID: 34708903 PMCID: PMC8720196 DOI: 10.1002/hbm.25689] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/03/2021] [Accepted: 10/07/2021] [Indexed: 11/10/2022] Open
Abstract
White matter maturation has been characterized by diffusion tensor (DT) metrics. However, maturational processes and degrees are not fully investigated due to limitations of univariate approaches and limited specificity/sensitivity. Diffusion kurtosis imaging (DKI) provides kurtosis tensor (KT) and white matter tract integrity (WMTI) metrics, besides DT metrics. Therefore, we tried to investigate performances of DKI with the multiparametric analysis in characterizing white matter maturation. Developmental changes in metrics were investigated by using tract-based spatial statistics and the region of interest analysis on 50 neonates with postmenstrual age (PMA) from 37.43 to 43.57 weeks. Changes in metrics were combined into various patterns to reveal different maturational processes. Mahalanobis distance based on DT metrics (DM,DT ) and that combing DT and KT metrics (DM,DT-KT ) were computed, separately. Performances of DM,DT-KT and DM,DT were compared in revealing correlations with PMA and the neurobehavioral score. Compared with DT metrics, WMTI metrics demonstrated additional changing patterns. Furthermore, variations of DM,DT-KT across regions were in agreement with the maturational sequence. Additionally, DM,DT-KT demonstrated stronger negative correlations with PMA and the neurobehavioral score in more regions than DM,DT . Results suggest that DKI with the multiparametric analysis benefits the understanding of white matter maturational processes and degrees on neonates.
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Affiliation(s)
- Xianjun Li
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Mengxuan Li
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Miaomiao Wang
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fan Wu
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Heng Liu
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Biomedical Engineering, The Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Qinli Sun
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Biomedical Engineering, The Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Yuli Zhang
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Congcong Liu
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Chao Jin
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jian Yang
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Biomedical Engineering, The Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China
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32
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Bouyeure A, Bekha D, Patil S, Hertz-Pannier L, Noulhiane M. OUP accepted manuscript. Cereb Cortex Commun 2022; 3:tgac004. [PMID: 35261977 PMCID: PMC8895309 DOI: 10.1093/texcom/tgac004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 01/06/2022] [Accepted: 01/08/2022] [Indexed: 11/13/2022] Open
Abstract
The structure-function relationship between white matter microstructure and episodic memory (EM) has been poorly studied in the developing brain, particularly in early childhood. Previous studies in adolescents and adults have shown that episodic memory recall is associated with prefrontal-limbic white matter microstructure. It is unknown whether this association is also observed during early ontogeny. Here, we investigated the association between prefrontal-limbic tract microstructure and EM performance in a cross-sectional sample of children aged 4 to 12 years. We used a multivariate partial least squares correlation approach to extract tract-specific latent variables representing shared information between age and diffusion parameters describing tract microstructure. Individual projections onto these latent variables describe patterns of interindividual differences in tract maturation that can be interpreted as scores of white matter tract microstructural maturity. Using these estimates of microstructural maturity, we showed that maturity scores of the uncinate fasciculus and dorsal cingulum bundle correlated with distinct measures of EM recall. Furthermore, the association between tract maturity scores and EM recall was comparable between younger and older children. Our results provide new evidence on the relation between white matter maturity and EM performance during development.
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Affiliation(s)
- Antoine Bouyeure
- UNIACT, NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- UMR1141, Inserm, Université de Paris, 75019 Paris, France
| | - Dhaif Bekha
- UNIACT, NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- UMR1141, Inserm, Université de Paris, 75019 Paris, France
| | - Sandesh Patil
- UNIACT, NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- UMR1141, Inserm, Université de Paris, 75019 Paris, France
| | - Lucie Hertz-Pannier
- UNIACT, NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- UMR1141, Inserm, Université de Paris, 75019 Paris, France
| | - Marion Noulhiane
- UNIACT, NeuroSpin, CEA, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- UMR1141, Inserm, Université de Paris, 75019 Paris, France
- Corresponding author: UNIACT, NeuroSpin, CEA, 91191 Gif-sur-Yvette, France.
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33
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Zhao X, Zhang C, Zhang B, Yan J, Wang K, Zhu Z, Zhang X. The Value of Diffusion Kurtosis Imaging in Detecting Delayed Brain Development of Premature Infants. Front Neurol 2021; 12:789254. [PMID: 34966352 PMCID: PMC8710729 DOI: 10.3389/fneur.2021.789254] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 11/15/2021] [Indexed: 11/13/2022] Open
Abstract
Objective: Preterm infants are at high risk of the adverse neurodevelopmental outcomes. Our aim is to explore the value of diffusion kurtosis imaging (DKI) in diagnosing brain developmental disorders in premature infants. Materials and Methods: A total of 52 subjects were included in this study, including 26 premature infants as the preterm group, and 26 full-term infants as the control group. Routine MRI and DKI examinations were performed. Mean kurtosis (MK), radial kurtosis (RK), fractional anisotropy (FA), and mean diffusivity (MD) values were measured in the brain regions including posterior limbs of the internal capsule (PLIC), anterior limb of internal capsule (ALIC), parietal white matter (PWM), frontal white matter (FWM), thalamus (TH), caudate nucleus (CN), and genu of the corpus callosum (GCC). The chi-squared test, t-test, Spearman's correlation analysis, and receiver operating characteristic curve were used for data analyses. Results: In the premature infant group, the MK and RK values of PLIA, ALIC, and PWM were lower than those in the control group (p < 0.05). The FA values of PWM, FWM, and TH were also lower than those of the control group (p < 0.05). The area under curves of MK in PLIC and ALIC, MD in PWM, and FA in FWM were 0.813, 0.802, 0.842, and 0.867 (p < 0.05). In the thalamus and CN, the correlations between MK, RK values, and postmenstrual age (PMA) were higher than those between FA, MD values, and PMA. Conclusion: Diffusion kurtosis imaging can be used as an effective tool in detecting brain developmental disorders in premature infants.
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Affiliation(s)
- Xin Zhao
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chunxiang Zhang
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Bohao Zhang
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Kaiyu Wang
- MRI Research, GE Healthcare, Beijing, China
| | | | - Xiaoan Zhang
- Department of Imaging, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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34
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Schmidt Mellado G, Pillay K, Adams E, Alarcon A, Andritsou F, Cobo MM, Evans Fry R, Fitzgibbon S, Moultrie F, Baxter L, Slater R. The impact of premature extrauterine exposure on infants' stimulus-evoked brain activity across multiple sensory systems. Neuroimage Clin 2021; 33:102914. [PMID: 34915328 PMCID: PMC8683775 DOI: 10.1016/j.nicl.2021.102914] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/10/2021] [Accepted: 12/09/2021] [Indexed: 11/03/2022]
Abstract
Prematurity can result in widespread neurodevelopmental impairment, with the impact of premature extrauterine exposure on brain function detectable in infancy. A range of neurodynamic and haemodynamic functional brain measures have previously been employed to study the neurodevelopmental impact of prematurity, with methodological and analytical heterogeneity across studies obscuring how multiple sensory systems are affected. Here, we outline a standardised template analysis approach to measure evoked response magnitudes for visual, tactile, and noxious stimulation in individual infants (n = 15) using EEG. By applying these templates longitudinally to an independent cohort of very preterm infants (n = 10), we observe that the evoked response template magnitudes are significantly associated with age-related maturation. Finally, in a cross-sectional study we show that the visual and tactile response template magnitudes differ between a cohort of infants who are age-matched at the time of study but who differ according to whether they are born during the very preterm or late preterm period (n = 10 and 8 respectively). These findings demonstrate the significant impact of premature extrauterine exposure on brain function and suggest that prematurity can accelerate maturation of the visual and tactile sensory system in infants born very prematurely. This study highlights the value of using a standardised multi-modal evoked-activity analysis approach to assess premature neurodevelopment, and will likely complement resting-state EEG and behavioural assessments in the study of the functional impact of developmental care interventions.
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Affiliation(s)
| | - Kirubin Pillay
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Eleri Adams
- Newborn Care Unit, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Ana Alarcon
- Newborn Care Unit, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, UK; Department of Neonatology, Hospital Sant Joan de Deu, Institut de Recerca Sant Joan de Deu, Universitat de Barcelona, Barcelona, Spain
| | | | - Maria M Cobo
- Department of Paediatrics, University of Oxford, Oxford, UK; Universidad San Francisco de Quito USFQ, Colegio de Ciencias Biologicas y Ambientales, Quito, Ecuador
| | - Ria Evans Fry
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK.
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK.
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35
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White matter abnormalities associated with ADHD outcomes in adulthood. Mol Psychiatry 2021; 26:6655-6665. [PMID: 34035475 PMCID: PMC8613296 DOI: 10.1038/s41380-021-01153-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Revised: 03/24/2021] [Accepted: 04/29/2021] [Indexed: 02/04/2023]
Abstract
It remains unclear if previously reported structural abnormalities in children with ADHD are present in adulthood regardless of clinical outcome. In this study, we examined the extent to which focal-rather than diffuse-abnormalities in fiber collinearity of 18 major white matter tracts could distinguish 126 adults with rigorously diagnosed childhood ADHD (ADHD; mean age [SD] = 34.3 [3.6] years; F/M = 12/114) from 58 adults without ADHD histories (non-ADHD; mean age [SD] = 33.9 [4.1] years; F/M = 5/53) and if any of these abnormalities were greater for those with persisting ADHD symptomatology. To this end, a tract profile approach was used. After accounting for age, sex, handedness, and comorbidities, a MANCOVA revealed a main effect of group (ADHD < non-ADHD; F[18,155] = 2.1; p = 0.007) on fractional anisotropy (FA, a measure of fiber collinearity and/or integrity), in focal portions of white matter tracts involved in visuospatial processing and memory (i.e., anterior portion of the left inferior longitudinal fasciculus, and middle portion of the left and right cingulum angular bundle). Only abnormalities in the anterior portion of the left inferior longitudinal fasciculus distinguished probands with persisting versus desisting ADHD symptomatology, suggesting that abnormalities in the cingulum angular bundle might reflect "scarring" effects of childhood ADHD. To our knowledge, this is the first study using a tract profile approach to identify focal or widespread structural abnormalities in adults with ADHD rigorously diagnosed in childhood.
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36
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Wendel KM, Short AK, Noarbe BP, Haddad E, Palma AM, Yassa MA, Baram TZ, Obenaus A. Early life adversity in male mice sculpts reward circuits. Neurobiol Stress 2021; 15:100409. [PMID: 34746338 PMCID: PMC8554344 DOI: 10.1016/j.ynstr.2021.100409] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/24/2021] [Accepted: 10/12/2021] [Indexed: 01/08/2023] Open
Abstract
Early life adversity (ELA) comprises a wide variety of negative experiences during early life and has been linked to cognitive impairments, reduced experiences of pleasure (anhedonia), and other long-term consequences implying that ELA impacts the reward circuitry. In this study, we focused on the projections from the dorsal raphe (DR) to the ventral tegmental area (VTA) and on to the nucleus accumbens (NAcc), an important pathway within the reward circuit. We hypothesized that ELA alters connectivity within the DR-VTA-NAcc pathway, associated with deficient reward seeking behaviors in adulthood. We used the limited bedding and nesting model to induce ELA in mice and measured reward-related behaviors in adulthood using the three-chamber social interaction and sucrose preference tests. High resolution ex vivo diffusion tensor imaging (DTI) was acquired and processed for regional DTI metrics, including tractography to assess circuit organization. We found brain-wide changes in radial diffusivity (RD) and altered connectivity of the reward circuit in the ELA group. DR-VTA-NAcc circuit tractography and axial diffusivity (AD) along this tract exhibited dispersed organization where AD was increased in the VTA segment. Behaviorally, ELA elicited a social anhedonia-like phenotype in adulthood with decreased direct social approach and time spent with peers in the three-chamber task, and no overt differences in sucrose preference. Our findings suggest that reward circuits, assessed using DTI, are altered following ELA and that these changes may reflect enduring reward deficits.
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Affiliation(s)
- Kara M. Wendel
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine, Irvine, CA, USA
| | - Annabel K. Short
- Department of Pediatrics, University of California, Irvine School of Medicine, Irvine, CA, USA
| | - Brenda P. Noarbe
- Department of Pediatrics, University of California, Irvine School of Medicine, Irvine, CA, USA
| | - Elizabeth Haddad
- Department of Pediatrics, University of California, Irvine School of Medicine, Irvine, CA, USA
| | - Anton M. Palma
- Institute for Clinical and Translational Science, University of California, Irvine, CA, USA
| | - Michael A. Yassa
- Department of Neurobiology and Behavior, University of California, Irvine School of Biological Sciences, Irvine, CA, USA
| | - Tallie Z. Baram
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine, Irvine, CA, USA
- Department of Pediatrics, University of California, Irvine School of Medicine, Irvine, CA, USA
| | - Andre Obenaus
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine, Irvine, CA, USA
- Department of Pediatrics, University of California, Irvine School of Medicine, Irvine, CA, USA
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37
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Khurana S, Evans ME, Kelly CE, Thompson DK, Burnsed J, Harper A, Hendricks-Munoz K, Shall MS, Stevenson RD, Inamdar K, Vorona G, Dusing SC. Longitudinal Changes in the Sensorimotor Pathways of Very Preterm Infants During the First Year of Life With and Without Intervention: A Pilot Study. Dev Neurorehabil 2021; 24:448-455. [PMID: 34160340 PMCID: PMC8429051 DOI: 10.1080/17518423.2021.1903602] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Objective: Evaluate longitudinal changes in brain microstructure and volumes in very preterm infants during the first year of life with and without intervention.Design: Descriptive pilot study.Methods: Five preterm infants in a three-arm clinical trial, one SPEEDI Early, two SPEEDI Late, and two usual care. Brain structural and diffusion MRI's were acquired within 72 hours after neonatal intensive care unit discharge (n = 5), three months post-baseline (n = 5), and six months post-baseline (n = 3). Fractional anisotropy (FA), Mean diffusivity (MD), and volume metrics were computed for five brain regions.Results: More than 60% of eligible participants completed 100% of the scheduled MRIs. FA and volume increased from baseline to six months across all brain regions. Rate of white matter volume change from baseline to six months was highest in SPEEDI Early.Conclusions: Non-sedated longitudinal MRI is feasible in very preterm infants and appears to demonstrate longitudinal changes in brain structure and connectivity.
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Affiliation(s)
- Sonia Khurana
- Motor Development Lab, Virginia Commonwealth University, Richmond, Virginia
| | - Megan E Evans
- Motor Development Lab, Virginia Commonwealth University, Richmond, Virginia
| | - Claire E Kelly
- Victorian Infant Brain Studies (VIBeS) and Developmental Imaging, Murdoch Children’s Research Institute, Parkville, Victoria, Australia
| | - Deanne K Thompson
- Victorian Infant Brain Studies (VIBeS) and Developmental Imaging, Murdoch Children’s Research Institute, Parkville, Victoria, Australia; Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
| | - Jennifer Burnsed
- Division of Neonatology, University of Virginia, Charlottesville, Virginia
| | - Amy Harper
- Department of Neurology, Virginia Commonwealth University, Richmond, Virginia
| | - Karen Hendricks-Munoz
- Department of Pediatrics, Virginia Commonwealth University School of Medicine, Children’s Hospital of Richmond at VCU Richmond, Virginia
| | - Mary S Shall
- Department of Physical Therapy, Virginia Commonwealth University, Richmond, Virginia
| | - Richard D Stevenson
- Division of Neurodevelopmental and Behavioral Pediatrics, Department of Pediatrics, University of Virginia School of Medicine, Charlottesville, Virginia
| | - Ketaki Inamdar
- Rehabilitation and Movement Sciences, Motor Development Lab, Virginia Commonwealth University, Richmond, Virginia
| | - Greg Vorona
- Department of Radiology, Virginia Commonwealth University, Richmond, Virginia
| | - Stacey C Dusing
- Motor Development Lab, Department of Biokinesiology and Physical Therapy, University of Southern California
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38
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Zhang C, Zhao X, Cheng M, Wang K, Zhang X. The Effect of Intraventricular Hemorrhage on Brain Development in Premature Infants: A Synthetic MRI Study. Front Neurol 2021; 12:721312. [PMID: 34566865 PMCID: PMC8458889 DOI: 10.3389/fneur.2021.721312] [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: 06/06/2021] [Accepted: 07/13/2021] [Indexed: 11/27/2022] Open
Abstract
Objectives: Synthetic MRI can obtain multiple parameters in one scan, including T1 and T2 relaxation time, proton density (PD), brain volume, etc. This study aimed to investigate the parameter values T1 and T2 relaxation time, PD, and volume characteristics of intraventricular hemorrhage (IVH) newborn brain, and the ability of synthetic MRI parameters T1 and T2 relaxation time and PD to diagnose IVH. Materials and methods: The study included 50 premature babies scanned with conventional and synthetic MRI. Premature infants were allocated to the case group (n = 15) and NON IVH (n = 35). The T1, T2, PD values, and brain volume were obtained by synthetic MRI. Then we assessed the impact of IVH on these parameters. Results: In the posterior limbs of the internal capsule (PLIC), genu of the corpus callosum (GCC), central white matter (CWM), frontal white matter (FWM), and cerebellum (each p < 0.05), the T1 and T2 relaxation times of the IVH group were significantly prolonged. There were significant differences also in PD. The brain volume in many parts were also significantly reduced, which was best illustrated in gray matter (GM), cerebrospinal fluid and intracranial volume, and brain parenchymal fraction (BPF) (each p < 0.001, t = −5.232 to 4.596). The differential diagnosis ability of these quantitative values was found to be excellent in PLIC, CWM, and cerebellum (AUC 0.700–0.837, p < 0.05). Conclusion: The quantitative parameters of synthetic MRI show well the brain tissue characteristic values and brain volume changes of IVH premature infants. T1 and T2 relaxation times and PD contribute to the diagnosis and evaluation of IVH.
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Affiliation(s)
- Chunxiang Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
| | - Kaiyu Wang
- GE Healthcare, MR Research China, Beijing, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Institute of Neuroscience, Zhengzhou University, Zhengzhou, China
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39
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Sato J, Vandewouw MM, Bando N, Branson HM, O'Connor DL, Unger SL, Taylor MJ. White matter alterations and cognitive outcomes in children born very low birth weight. Neuroimage Clin 2021; 32:102843. [PMID: 34601309 PMCID: PMC8496319 DOI: 10.1016/j.nicl.2021.102843] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 10/25/2022]
Abstract
BACKGROUND Very low birth weight (VLBW) infants are at risk for disrupted white matter maturation, yet little is known about the contributing factors, particularly at preschool-age when cognitive difficulties begin to emerge. We examined white matter microstructure in five-year-old VLBW and full-term (FT) children, and its association with cognitive outcomes and birth weight. METHODS Multi-shell diffusion and MR images were obtained for 41 VLBW (mean birth weight: 1028.6 ± 256.8 g) and 26 FT (3295.4 ± 493.9 g) children. Fractional anisotropy (FA), radial diffusivity (RD), neurite orientation dispersion index (ODI) and density index (NDI) were estimated using diffusion tensor and neurite orientation dispersion and density imaging models. Between-group analyses used a general linear model with group and sex as explanatory variables. Within-group associations between white matter microstructure, cognitive outcomes and birth weight were also investigated. RESULTS VLBW compared to FT children showed lower FA and NDI across widespread white matter regions. Smaller clusters of atypical ODI were also found in VLBW children. Within-group analyses in FT children revealed that lower RD and higher NDI were associated with vocabulary acquisition and working memory. In VLBW children, higher FA and NDI, and lower RD and ODI, were associated with improved processing speed. In both groups, FA was positively associated with birth weight. CONCLUSIONS Our findings demonstrate white matter alterations in young VLBW children, including widespread reductions in axon density that may reflect sustained myelination disruptions. The associations with cognitive outcomes may also highlight which of the VLBW children are at higher risk for later cognitive difficulties.
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Affiliation(s)
- Julie Sato
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Psychology, University of Toronto, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada.
| | - Marlee M Vandewouw
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada; Autism Research Centre, Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Nicole Bando
- Translational Medicine, SickKids Research Institute, Toronto, Ontario, Canada
| | - Helen M Branson
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Medical Imaging, University of Toronto, Ontario, Canada
| | - Deborah L O'Connor
- Translational Medicine, SickKids Research Institute, Toronto, Ontario, Canada; Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada; Paediatrics, Mount Sinai Health, Toronto, Ontario, Canada
| | - Sharon L Unger
- Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada; Paediatrics, University of Toronto, Toronto, Ontario, Canada; Paediatrics, Mount Sinai Health, Toronto, Ontario, Canada; Division of Neonatology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Margot J Taylor
- Diagnostic Imaging, Hospital for Sick Children, Toronto, Ontario, Canada; Psychology, University of Toronto, Toronto, Ontario, Canada; Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada; Medical Imaging, University of Toronto, Ontario, Canada; Paediatrics, University of Toronto, Toronto, Ontario, Canada
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40
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Yu Q, Peng Y, Kang H, Peng Q, Ouyang M, Slinger M, Hu D, Shou H, Fang F, Huang H. Differential White Matter Maturation from Birth to 8 Years of Age. Cereb Cortex 2021; 30:2673-2689. [PMID: 31819951 PMCID: PMC7175013 DOI: 10.1093/cercor/bhz268] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 08/23/2019] [Accepted: 09/17/2019] [Indexed: 12/14/2022] Open
Abstract
Comprehensive delineation of white matter (WM) microstructural maturation from birth to childhood is critical for understanding spatiotemporally differential circuit formation. Without a relatively large sample of datasets and coverage of critical developmental periods of both infancy and early childhood, differential maturational charts across WM tracts cannot be delineated. With diffusion tensor imaging (DTI) of 118 typically developing (TD) children aged 0–8 years and 31 children with autistic spectrum disorder (ASD) aged 2–7 years, the microstructure of every major WM tract and tract group was measured with DTI metrics to delineate differential WM maturation. The exponential model of microstructural maturation of all WM was identified. The WM developmental curves were separated into fast, intermediate, and slow phases in 0–8 years with distinctive time period of each phase across the tracts. Shorter periods of the fast and intermediate phases in certain tracts, such as the commissural tracts, indicated faster earlier development. With TD WM maturational curves as the reference, higher residual variance of WM microstructure was found in children with ASD. The presented comprehensive and differential charts of TD WM microstructural maturation of all major tracts and tract groups in 0–8 years provide reference standards for biomarker detection of neuropsychiatric disorders.
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Affiliation(s)
- Qinlin Yu
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Huiying Kang
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Qinmu Peng
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Minhui Ouyang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Michelle Slinger
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Di Hu
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Haochang Shou
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Fang Fang
- School of Psychological and Cognitive Sciences and Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing 100871, China.,Key Laboratory of Machine Perception, Peking University, Beijing 100871, China.,Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China.,PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Hao Huang
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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41
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Demirayak P, Karli Oguz K, Ustun FS, Urgen BM, Topac Y, Gilani I, Kansu T, Saygi S, Ozcelik T, Boyaci H, Doerschner K. Cortical connectivity in the face of congenital structural changes-A case of homozygous LAMC3 mutation. Brain Behav 2021; 11:e2241. [PMID: 34124859 PMCID: PMC8413815 DOI: 10.1002/brb3.2241] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Revised: 05/17/2021] [Accepted: 05/23/2021] [Indexed: 12/19/2022] Open
Abstract
The homozygous LAMC3 gene mutation is associated with severe bilateral smoothening and thickening of the lateral occipital cortex . Despite this and further significant changes in gray matter structure, a patient harboring this mutation exhibited a range of remarkably intact perceptual abilities . One possible explanation of this perceptual sparing could be that the white matter structural integrity and functional connectivity in relevant pathways remained intact. To test this idea, we used diffusion tensor and functional magnetic resonance imaging to investigate functional connectivity in resting-state networks in major structural pathways involved in object perception and visual attention and corresponding microstructural integrity in a patient with homozygous LAMC3 mutation and sex, age, education, and socioeconomically matched healthy control group. White matter microstructural integrity results indicated widespread disruptions in both intra- and interhemispheric structural connections except inferior longitudinal fasciculus. With a few exceptions, the functional connectivity between the patient's adjacent gray matter regions of major white matter tracts of interest was conserved. In addition, functional localizers for face, object, and place areas showed similar results with a representative control, providing an explanation for the patient's intact face, place, and object recognition abilities. To generalize this finding, we also compared functional connectivity between early visual areas and face, place, and object category-selective areas, and we found that the functional connectivity of the patient was not different from the control group. Overall, our results provided complementary information about the effects of LAMC3 gene mutation on the human brain including intact temporo-occipital structural and functional connectivity that are compatible with preserved perceptual abilities.
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Affiliation(s)
- Pinar Demirayak
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Kader Karli Oguz
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey.,Department of Radiology, Hacettepe University, Ankara, Turkey
| | - Fatma Seyhun Ustun
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey
| | - Buse Merve Urgen
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey.,Neuroscience Program, Bilkent University, Ankara, Turkey
| | - Yasemin Topac
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey
| | - Irtiza Gilani
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey
| | - Tulay Kansu
- Department of Neurology, Hacettepe University, Ankara, Turkey
| | - Serap Saygi
- Department of Neurology, Hacettepe University, Ankara, Turkey
| | - Tayfun Ozcelik
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey.,Department of Molecular Biology and Genetics, Bilkent University, Ankara, Turkey
| | - Huseyin Boyaci
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey.,Neuroscience Program, Bilkent University, Ankara, Turkey.,Department of Psychology, Bilkent University, Ankara, Turkey.,Department of Psychology, JL Giessen University, Giessen, Germany
| | - Katja Doerschner
- A.S. Brain Research Center and National Magnetic Resonance Center, Bilkent University, Ankara, Turkey.,Neuroscience Program, Bilkent University, Ankara, Turkey.,Department of Psychology, Bilkent University, Ankara, Turkey.,Department of Psychology, JL Giessen University, Giessen, Germany
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42
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Zuk J, Yu X, Sanfilippo J, Figuccio MJ, Dunstan J, Carruthers C, Sideridis G, Turesky TK, Gagoski B, Grant PE, Gaab N. White matter in infancy is prospectively associated with language outcomes in kindergarten. Dev Cogn Neurosci 2021; 50:100973. [PMID: 34119849 PMCID: PMC8209179 DOI: 10.1016/j.dcn.2021.100973] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 06/01/2021] [Accepted: 06/01/2021] [Indexed: 12/24/2022] Open
Abstract
Language acquisition is of central importance to child development. Although this developmental trajectory is shaped by experience postnatally, the neural basis for language emerges prenatally. Thus, a fundamental question remains: do structural foundations for language in infancy predict long-term language abilities? Longitudinal investigation of 40 children from infancy to kindergarten reveals that white matter in infancy is prospectively associated with subsequent language abilities, specifically between: (i) left arcuate fasciculus and phonological awareness and vocabulary knowledge, (ii) left corticospinal tract and phonological awareness, and bilateral corticospinal tract with phonological memory; controlling for age, cognitive, and environmental factors. Findings link white matter in infancy with school-age language abilities, suggesting that white matter organization in infancy sets a foundation for long-term language development.
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Affiliation(s)
- Jennifer Zuk
- Department of Speech, Language & Hearing Sciences, Boston University, Boston, MA, 02215, USA; Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA.
| | - Xi Yu
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Joseph Sanfilippo
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA
| | | | - Jade Dunstan
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Clarisa Carruthers
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Georgios Sideridis
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA
| | - Ted K Turesky
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA
| | - Borjan Gagoski
- Harvard Medical School, Boston, MA, 02115, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Patricia Ellen Grant
- Harvard Medical School, Boston, MA, 02115, USA; Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, 02115, USA
| | - Nadine Gaab
- Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA, 02115, USA; Harvard Medical School, Boston, MA, 02115, USA; Harvard Graduate School of Education, Cambridge, MA, 02138, USA
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43
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Lima Santos JP, Kontos AP, Mailliard S, Eagle SR, Holland CL, Suss SJ, Abdul-Waalee H, Stiffler RS, Bitzer HB, Blaney NA, Colorito AT, Santucci CG, Brown A, Kim T, Iyengar S, Skeba A, Diler RS, Ladouceur CD, Phillips ML, Brent D, Collins MW, Versace A. White Matter Abnormalities Associated With Prolonged Recovery in Adolescents Following Concussion. Front Neurol 2021; 12:681467. [PMID: 34248824 PMCID: PMC8264142 DOI: 10.3389/fneur.2021.681467] [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: 03/16/2021] [Accepted: 05/27/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Concussion symptoms in adolescents typically resolve within 4 weeks. However, 20 - 30% of adolescents experience a prolonged recovery. Abnormalities in tracts implicated in visuospatial attention and emotional regulation (i.e., inferior longitudinal fasciculus, ILF; inferior fronto-occipital fasciculus, IFOF; uncinate fasciculus; UF) have been consistently reported in concussion; yet, to date, there are no objective markers of prolonged recovery in adolescents. Here, we evaluated the utility of diffusion MRI in outcome prediction. Forty-two adolescents (12.1 - 17.9 years; female: 44.0%) underwent a diffusion Magnetic Resonance Imaging (dMRI) protocol within the first 10 days of concussion. Based on days of injury until medical clearance, adolescents were then categorized into SHORT (<28 days; N = 21) or LONG (>28 days; N = 21) recovery time. Fractional anisotropy (FA) in the ILF, IFOF, UF, and/or concussion symptoms were used as predictors of recovery time (SHORT, LONG). Forty-two age- and sex-matched healthy controls served as reference. Higher FA in the ILF (left: adjusted odds ratio; AOR = 0.36, 95% CI = 0.15 - 0.91, P = 0.030; right: AOR = 0.28, 95% CI = 0.10 - 0.83, P = 0.021), IFOF (left: AOR = 0.21, 95% CI = 0.07 - 0.66, P = 0.008; right: AOR = 0.30, 95% CI = 0.11 - 0.83, P = 0.020), and UF (left: AOR = 0.26, 95% CI = 0.09 - 0.74, P = 0.011; right: AOR = 0.28, 95% CI = 0.10 - 0.73, P = 0.010) was associated with SHORT recovery. In additional analyses, while adolescents with SHORT recovery did not differ from HC, those with LONG recovery showed lower FA in the ILF and IFOF (P < 0.014). Notably, inclusion of dMRI findings increased the sensitivity and specificity (AUC = 0.93) of a prediction model including clinical variables only (AUC = 0.75). Our findings indicate that higher FA in long associative tracts (especially ILF) might inform a more objective and accurate prognosis for recovery time in adolescents following concussion.
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Affiliation(s)
- João Paulo Lima Santos
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Anthony P Kontos
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Sarrah Mailliard
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Shawn R Eagle
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Cynthia L Holland
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Stephen J Suss
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Halimah Abdul-Waalee
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Richelle S Stiffler
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Hannah B Bitzer
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Nicholas A Blaney
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Adam T Colorito
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Christopher G Santucci
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Allison Brown
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Tae Kim
- Department of Radiology, Magnetic Resonance Research Center, University of Pittsburgh, Pittsburgh, PA, United States
| | - Satish Iyengar
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Alexander Skeba
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rasim S Diler
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Cecile D Ladouceur
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Mary L Phillips
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - David Brent
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States
| | - Michael W Collins
- Department of Orthopaedic Surgery, University of Pittsburgh Medical Center (UPMC) Sports Concussion Program-University of Pittsburgh, Pittsburgh, PA, United States
| | - Amelia Versace
- Department of Psychiatry, Western Psychiatric Hospital, University of Pittsburgh, Pittsburgh, PA, United States.,Department of Radiology, Magnetic Resonance Research Center, University of Pittsburgh, Pittsburgh, PA, United States
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44
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Tan AP, Ngoh ZM, Yeo SSP, Koh DXP, Gluckman P, Chong YS, Daniel LM, Rifkin-Graboi A, Fortier MV, Qiu A, Meaney M. Left lateralization of neonatal caudate microstructure affects emerging language development at 24 months. Eur J Neurosci 2021; 54:4621-4637. [PMID: 34125467 PMCID: PMC9541223 DOI: 10.1111/ejn.15347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Accepted: 06/08/2021] [Indexed: 11/27/2022]
Abstract
The complex interaction between brain and behaviour in language disorder is well established. Yet to date, the imaging literature in the language disorder field has continued to pursue heterogeneous and relatively small clinical cross‐sectional samples, with emphasis on cortical structures and volumetric analyses of subcortical brain structures. In our current work, we aimed to go beyond this state of knowledge to focus on the microstructural features of subcortical brain structures (specifically the caudate nucleus) in a large cohort of neonates and study its association with emerging language skills at 24 months. Variations in neonatal brain microstructure could be interpreted as a proxy for in utero brain development. As language development is highly dependent on cognitive function and home literacy environment, we also examined their effect on the caudate–language function relationship utilizing a conditional process model. Our findings suggest that emerging language development at 24 months is influenced by the degree of left lateralization of neonatal caudate microstructure, indexed by diffusion tensor imaging (DTI)‐derived fractional anisotropy (FA). FA is an indirect measure of neuronal and dendritic density within grey matter structures. We also found that the caudate–language function relationship is partially mediated by cognitive function. The conditional indirect effect of left caudate FA on language composite score through cognitive function was only statistically significant at low levels of home literacy score (−1 standard deviation [SD]). The authors proposed that this may be related to ‘compensatory’ development of cognitive skills in less favourable home literacy environments.
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Affiliation(s)
- Ai Peng Tan
- Department of Diagnostic Imaging, National University Health System, Singapore
| | - Zhen Ming Ngoh
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore
| | - Shayne Siok Peng Yeo
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore
| | - Dawn Xin Ping Koh
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore.,Duke-National University of Singapore Graduate Medical School, Singapore
| | - Peter Gluckman
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore
| | - Lourdes Mary Daniel
- Department of Child Development, KK Women's and Children's Hospital, Singapore.,Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore
| | - Anne Rifkin-Graboi
- Centre for Research in Child Development, National Institute of Education, Singapore
| | - Marielle V Fortier
- Department of Diagnostic and Interventional Radiology, KK Women's and Children's Hospital, Singapore
| | - Anqi Qiu
- Department of Biomedical Engineering, National University of Singapore (NUS), Singapore
| | - Michael Meaney
- Singapore Institute for Clinical Sciences (SICS), A*STAR Research Entities (ARES), Singapore.,Yong Loo Lin School of Medicine, National University of Singapore (NUS), Singapore.,Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
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45
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Fouladivanda M, Kazemi K, Makki M, Khalilian M, Danyali H, Gervain J, Aarabi A. Multi-scale structural rich-club organization of the brain in full-term newborns: a combined DWI and fMRI study. J Neural Eng 2021; 18. [PMID: 33930878 DOI: 10.1088/1741-2552/abfd46] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 04/30/2021] [Indexed: 12/11/2022]
Abstract
Objective.Our understanding of early brain development is limited due to rapid changes in white matter pathways after birth. In this study, we introduced a multi-scale cross-modal approach to investigate the rich club (RC) organization and topology of the structural brain networks in 40 healthy neonates using diffusion-weighted imaging and resting-state fMRI data.Approach.A group independent component analysis was first performed to identify eight resting state networks (RSNs) used as functional modules. A groupwise whole-brain functional parcellation was also performed at five scales comprising 100-900 parcels. The distribution of RC nodes was then investigated within and between the RSNs. We further assessed the distribution of short and long-range RC, feeder and local connections across different parcellation scales.Main results.Sharing the scale-free characteristic of small-worldness, the neonatal structural brain networks exhibited an RC organization at different nodal scales (NSs). The subcortical, sensory-motor and default mode networks were found to be strongly involved in the RC organization of the structural brain networks, especially in the zones where the RSNs overlapped, with an average cross-scale proportion of 45.9%, 28.5% and 10.5%, respectively. A large proportion of the connector hubs were found to be RC members for the coarsest (73%) to finest (92%) NSs. Our results revealed a prominent involvement of cortico-subcortical and cortico-cerebellar white matter pathways in the RC organization of the neonatal brain. Regardless of the NS, the majority (more than 65.2%) of the inter-RSN connections were long distance RC or feeder with an average physical connection of 105.5 and 97.4 mm, respectively. Several key RC regions were identified, including the insula and cingulate gyri, middle and superior temporal gyri, hippocampus and parahippocampus, fusiform gyrus, precuneus, superior frontal and precentral gyri, calcarine fissure and lingual gyrus.Significance.Our results emphasize the importance of the multi-scale connectivity analysis in assessing the cross-scale reproducibility of the connectivity results concerning the global and local topological properties of the brain networks. Our findings may improve our understanding of the early brain development.
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Affiliation(s)
- Mahshid Fouladivanda
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Kamran Kazemi
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Malek Makki
- Laboratory of Functional Neuroscience and Pathologies (LNFP), University Research Center (CURS), University Hospital, Amiens, France
| | - Maedeh Khalilian
- Laboratory of Functional Neuroscience and Pathologies (LNFP), University Research Center (CURS), University Hospital, Amiens, France
| | - Habibollah Danyali
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Judit Gervain
- Integrative Neuroscience and Cognition Center, CNRS & Université de Paris, Paris, France.,Department of Developmental Psychology and Socialization, University of Padua, Padua, Italy
| | - Ardalan Aarabi
- Laboratory of Functional Neuroscience and Pathologies (LNFP), University Research Center (CURS), University Hospital, Amiens, France.,Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
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46
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Baxter L, Moultrie F, Fitzgibbon S, Aspbury M, Mansfield R, Bastiani M, Rogers R, Jbabdi S, Duff E, Slater R. Functional and diffusion MRI reveal the neurophysiological basis of neonates' noxious-stimulus evoked brain activity. Nat Commun 2021; 12:2744. [PMID: 33980860 PMCID: PMC8115252 DOI: 10.1038/s41467-021-22960-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 04/05/2021] [Indexed: 11/20/2022] Open
Abstract
Understanding the neurophysiology underlying neonatal responses to noxious stimulation is central to improving early life pain management. In this neonatal multimodal MRI study, we use resting-state and diffusion MRI to investigate inter-individual variability in noxious-stimulus evoked brain activity. We observe that cerebral haemodynamic responses to experimental noxious stimulation can be predicted from separately acquired resting-state brain activity (n = 18). Applying this prediction model to independent Developing Human Connectome Project data (n = 215), we identify negative associations between predicted noxious-stimulus evoked responses and white matter mean diffusivity. These associations are subsequently confirmed in the original noxious stimulation paradigm dataset, validating the prediction model. Here, we observe that noxious-stimulus evoked brain activity in healthy neonates is coupled to resting-state activity and white matter microstructure, that neural features can be used to predict responses to noxious stimulation, and that the dHCP dataset could be utilised for future exploratory research of early life pain system neurophysiology.
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Affiliation(s)
- Luke Baxter
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Fiona Moultrie
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | | | | | - Matteo Bastiani
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- NIHR Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Richard Rogers
- Nuffield Department of Anaesthetics, John Radcliffe Hospital, Oxford, UK
| | - Saad Jbabdi
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Eugene Duff
- Department of Paediatrics, University of Oxford, Oxford, UK
- FMRIB, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Rebeccah Slater
- Department of Paediatrics, University of Oxford, Oxford, UK.
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47
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Dubois J, Alison M, Counsell SJ, Hertz‐Pannier L, Hüppi PS, Benders MJ. MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances. J Magn Reson Imaging 2021; 53:1318-1343. [PMID: 32420684 PMCID: PMC8247362 DOI: 10.1002/jmri.27192] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 04/24/2020] [Accepted: 04/24/2020] [Indexed: 01/04/2023] Open
Abstract
In recent years, exploration of the developing brain has become a major focus for researchers and clinicians in an attempt to understand what allows children to acquire amazing and unique abilities, as well as the impact of early disruptions (eg, prematurity, neonatal insults) that can lead to a wide range of neurodevelopmental disorders. Noninvasive neuroimaging methods such as MRI are essential to establish links between the brain and behavioral changes in newborns and infants. In this review article, we aim to highlight recent and representative studies using the various techniques available: anatomical MRI, quantitative MRI (relaxometry, diffusion MRI), multiparametric approaches, and functional MRI. Today, protocols use 1.5 or 3T MRI scanners, and specialized methodologies have been put in place for data acquisition and processing to address the methodological challenges specific to this population, such as sensitivity to motion. MR sequences must be adapted to the brains of newborns and infants to obtain relevant good soft-tissue contrast, given the small size of the cerebral structures and the incomplete maturation of tissues. The use of age-specific image postprocessing tools is also essential, as signal and contrast differ from the adult brain. Appropriate methodologies then make it possible to explore multiple neurodevelopmental mechanisms in a precise way, and assess changes with age or differences between groups of subjects, particularly through large-scale projects. Although MRI measurements only indirectly reflect the complex series of dynamic processes observed throughout development at the molecular and cellular levels, this technique can provide information on brain morphology, structural connectivity, microstructural properties of gray and white matter, and on the functional architecture. Finally, MRI measures related to clinical, behavioral, and electrophysiological markers have a key role to play from a diagnostic and prognostic perspective in the implementation of early interventions to avoid long-term disabilities in children. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Jessica Dubois
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Marianne Alison
- University of ParisNeuroDiderot, INSERM,ParisFrance
- Department of Pediatric RadiologyAPHP, Robert‐Debré HospitalParisFrance
| | - Serena J. Counsell
- Centre for the Developing BrainSchool of Biomedical Engineering & Imaging Sciences, King's College LondonLondonUK
| | - Lucie Hertz‐Pannier
- University of ParisNeuroDiderot, INSERM,ParisFrance
- UNIACT, NeuroSpin, CEA; Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Petra S. Hüppi
- Division of Development and Growth, Department of Woman, Child and AdolescentUniversity Hospitals of GenevaGenevaSwitzerland
| | - Manon J.N.L. Benders
- Department of NeonatologyUniversity Medical Center Utrecht, Utrecht UniversityUtrechtthe Netherlands
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48
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Olivieri B, Rampakakis E, Gilbert G, Fezoua A, Wintermark P. Myelination may be impaired in neonates following birth asphyxia. NEUROIMAGE-CLINICAL 2021; 31:102678. [PMID: 34082365 PMCID: PMC8182124 DOI: 10.1016/j.nicl.2021.102678] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 03/17/2021] [Accepted: 04/12/2021] [Indexed: 01/23/2023]
Abstract
Myelination is a developmental process that intensifies after birth during the first years of life. We used a T2* mapping sequence to assess myelination in healthy and critically ill neonates with neonatal encephalopathy. Birth asphyxia, in addition to causing the previously well-described direct injury to the brain, may impair myelination.
Background Myelination is a developmental process that begins during the end of gestation, intensifies after birth over the first years of life, and continues well into adolescence. Any event leading to brain injury around the time of birth and during the perinatal period, such as birth asphyxia, may impair this critical process. Currently, the impact of such brain injury related to birth asphyxia on the myelination process is unknown. Objective To assess the myelination pattern over the first month of life in neonates with neonatal encephalopathy (NE) developing brain injury, compared to neonates without injury (i.e., healthy neonates and neonates with NE who do not develop brain injury). Methods Brain magnetic resonance imaging (MRI) was performed around day of life 2, 10, and 30 in healthy neonates and near-term/term neonates with NE who were treated with hypothermia. We evaluated myelination in various regions of interest using a T2* mapping sequence. In each region of interest, we compared the T2* values of the neonates with NE with brain injury to the values of the neonates without injury, according to the MRI timing, by using a repeated measures generalized linear mixed model. Results We obtained 74 MRI scans over the first month of life for 6 healthy neonates, 17 neonates with NE who were treated with hypothermia and did not develop brain injury, and 16 neonates with NE who were treated with hypothermia and developed brain injury. The T2* values significantly increased in the neonates with NE who developed injury in the posterior limbs of the internal capsule (day 2: p < 0.001; day 10: p < 0.001; and day 30: p < 0.001), the thalami (day 2: p = 0.001; day 10: p = 0.006; and day 30: p = 0.016), the lentiform nuclei (day 2: p = 0.005), the anterior white matter (day 2: p = 0.002; day 10: p = 0.006; and day 30: p = 0.002), the posterior white matter (day 2: p = 0.001; day 10: p = 0.008; and day 30: p = 0.03), the genu of the corpus callosum (day 2: p = 0.01; and day 10: p = 0.006), and the optic radiations (day 30: p < 0.001). Conclusion In the neonates with NE who were treated with hypothermia and developed brain injury, birth asphyxia impaired myelination in the regions that are myelinated at birth or soon after birth (the posterior limbs of internal capsule, the thalami, and the lentiform nuclei), in the regions where the myelination process begins only after the perinatal period (optic radiations), and in the regions where this process does not occur until months after birth (anterior/posterior white matter), which suggests that birth asphyxia, in addition to causing the previously well-described direct injury to the brain, may impair myelination.
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Affiliation(s)
- Bianca Olivieri
- Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada
| | - Emmanouil Rampakakis
- Medical Affairs, JSS Medical Research, Montreal, Québec, Canada; Department of Pediatrics, Montreal Children's Hospital, McGill University, Montreal, QC, Canada
| | | | - Aliona Fezoua
- Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada
| | - Pia Wintermark
- Research Institute of the McGill University Health Centre, McGill University, Montreal, QC, Canada; Department of Pediatrics, Division of Newborn Medicine, Montreal Children's Hospital, McGill University, Montreal, QC, Canada.
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Salimeen MSA, Liu C, Li X, Wang M, Singh M, Si S, Li M, Cheng Y, Wang X, Zhao H, Wu F, Zhang Y, Tafawa H, Pradhan A, Yang G, Yang J. Exploring Variances of White Matter Integrity and the Glymphatic System in Simple Febrile Seizures and Epilepsy. Front Neurol 2021; 12:595647. [PMID: 33967932 PMCID: PMC8097149 DOI: 10.3389/fneur.2021.595647] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 03/15/2021] [Indexed: 12/19/2022] Open
Abstract
Background: Simple febrile seizures (SFS) and epilepsy are common seizures in childhood. However, the mechanism underlying SFS is uncertain, and the presence of obvious variances in white matter (WM) integrity and glymphatic function between SFS and epilepsy remain unclear. Therefore, this study aimed to investigate the differences in WM integrity and glymphatic function between SFS and epilepsy. Material and Methods: We retrospectively included 26 children with SFS, 33 children with epilepsy, and 28 controls aged 6–60 months who underwent magnetic resonance imaging (MRI). Tract-based spatial statistics (TBSS) were used to compare the diffusion tensor imaging (DTI) metrics of WM among the above-mentioned groups. T2-weighted imaging (T2WI) was used to segment the visible Virchow-Robin space (VRS) through a custom-designed automated method. VRS counts and volume were quantified and compared among the SFS, epilepsy, and control groups. Correlations of the VRS metrics and seizure duration and VRS metrics and the time interval between seizure onset and MRI scan were also investigated. Results: In comparison with controls, children with SFS showed no significant changes in fractional anisotropy (FA), axial diffusivity (AD), or radial diffusivity (RD) in the WM (P > 0.05). Decreased FA, unchanged AD, and increased RD were observed in the epilepsy group in comparison with the SFS and control groups (P < 0.05). Meanwhile, VRS counts were higher in the SFS and epilepsy groups than in the control group (VRS_SFS, 442.42 ± 74.58, VRS_epilepsy, 629.94 ± 106.55, VRS_control, 354.14 ± 106.58; P < 0.001), and similar results were found for VRS volume (VRS_SFS, 6,228.18 ± 570.74 mm3, VRS_epilepsy, 9,684.84 ± 7,292.66mm3, VRS_control, 4,007.22 ± 118.86 mm3; P < 0.001). However, VRS metrics were lower in the SFS group than in the epilepsy group (P < 0.001). In both SFS and epilepsy, VRS metrics positively correlated with seizure duration and negatively correlated with the course after seizure onset. Conclusion: SFS may not be associated with WM microstructural disruption; however, epilepsy is related to WM alterations. Seizures are associated with glymphatic dysfunction in either SFS or epilepsy.
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Affiliation(s)
- Mustafa Salimeen Abdelkareem Salimeen
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Department of Radiology, Dongola Teaching Hospital, University of Dongola, Dongola, Sudan
| | - Congcong Liu
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xianjun Li
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Miaomiao Wang
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Martha Singh
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Shuqing Si
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Mengxuan Li
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yannan Cheng
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Xiaoyu Wang
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Huifang Zhao
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Fan Wu
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yuli Zhang
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Habib Tafawa
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Anuja Pradhan
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Guanyu Yang
- School of Electronic Engineering, Xidian University, Xi'an, China
| | - Jian Yang
- Department of Radiology, the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.,Center for Brain Science, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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German Language Adaptation of the NAVS (NAVS-G) and of the NAT (NAT-G): Testing Grammar in Aphasia. Brain Sci 2021; 11:brainsci11040474. [PMID: 33918022 PMCID: PMC8069474 DOI: 10.3390/brainsci11040474] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 04/02/2021] [Accepted: 04/04/2021] [Indexed: 11/17/2022] Open
Abstract
Grammar provides the framework for understanding and producing language. In aphasia, an acquired language disorder, grammatical deficits are diversified and widespread. However, the few assessments for testing grammar in the German language do not consider current linguistic, psycholinguistic, and functional imaging data, which have been shown to be crucial for effective treatment. This study developed German language versions of the Northwestern Assessment of Verbs and Sentences (NAVS-G) and the Northwestern Anagram Test (NAT-G) to examine comprehension and production of verbs, controlling for the number and optionality of verb arguments, and sentences with increasing syntactic complexity. The NAVS-G and NAT-G were tested in 27 healthy participants, 15 right hemispheric stroke patients without aphasia, and 15 stroke patients with mild to residual aphasia. Participants without aphasia showed near-perfect performance, with the exception of (object) relative sentences, where accuracy was associated with educational level. In each patient with aphasia, deficits in more than one subtest were observed. The within and between population-groups logistic mixed regression analyses identified significant impairments in processing syntactic complexity at the verb and sentence levels. These findings indicate that the NAVS-G and NAT-G have potential for testing grammatical competence in (German) stroke patients.
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