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Ortinau CM, Newburger JW. Placenta-Heart-Brain Connection in Congenital Heart Disease. J Am Heart Assoc 2024; 13:e033875. [PMID: 38420776 PMCID: PMC10944051 DOI: 10.1161/jaha.124.033875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Accepted: 01/04/2024] [Indexed: 03/02/2024]
Affiliation(s)
- Cynthia M. Ortinau
- Department of PediatricsWashington University in St. LouisSt. LouisMOUSA
| | - Jane W. Newburger
- Department of CardiologyBoston Children’s HospitalBostonMAUSA
- Department of PediatricsHarvard Medical SchoolBostonMAUSA
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Sadhwani A, Sood E, Van Bergen AH, Ilardi D, Sanz JH, Gaynor JW, Seed M, Ortinau CM, Marino BS, Miller TA, Gaies M, Cassidy AR, Donohue JE, Ardisana A, Wypij D, Goldberg CS. Development of the data registry for the Cardiac Neurodevelopmental Outcome Collaborative. Cardiol Young 2024; 34:79-85. [PMID: 37203794 DOI: 10.1017/s1047951123001208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Children with congenital heart disease (CHD) can face neurodevelopmental, psychological, and behavioural difficulties beginning in infancy and continuing through adulthood. Despite overall improvements in medical care and a growing focus on neurodevelopmental screening and evaluation in recent years, neurodevelopmental disabilities, delays, and deficits remain a concern. The Cardiac Neurodevelopmental Outcome Collaborative was founded in 2016 with the goal of improving neurodevelopmental outcomes for individuals with CHD and pediatric heart disease. This paper describes the establishment of a centralised clinical data registry to standardize data collection across member institutions of the Cardiac Neurodevelopmental Outcome Collaborative. The goal of this registry is to foster collaboration for large, multi-centre research and quality improvement initiatives that will benefit individuals and families with CHD and improve their quality of life. We describe the components of the registry, initial research projects proposed using data from the registry, and lessons learned in the development of the registry.
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Affiliation(s)
- Anjali Sadhwani
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Erica Sood
- Nemours Cardiac Center, Nemours Children's Health, Wilmington, DE, USA
- Department of Pediatrics, Thomas Jefferson University, Philadelphia, PA, USA
| | - Andrew H Van Bergen
- Advocate Children's Heart Institute, Advocate Children's Hospital, Oak Lawn, IL, USA
| | - Dawn Ilardi
- Department of Rehabilitation Medicine, Emory University, and the Department of Neuropsychology, Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Jacqueline H Sanz
- Division of Neuropsychology, Children's National Hospital, and Departments of Psychiatry and Behavioral Science and Pediatrics, George Washington University School of Medicine, Washington, DC, USA
| | - J William Gaynor
- Division of Cardiothoracic Surgery, Department of Surgery, Children's Hospital of Philadelphia, and the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Seed
- Division of Cardiology, Hospital for Sick Children, Toronto, Canada
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis. St. Louis. MO, USA
| | - Bradley S Marino
- Department of Pediatric Cardiology, Cleveland Clinic Children's, Cleveland, OH, USA
| | - Thomas A Miller
- Division of Pediatric Cardiology, Maine Medical Center, Portland, ME, USA
| | - Michael Gaies
- Heart Institute, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Adam R Cassidy
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
- Departments of Psychiatry and Psychology, and Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA
| | - Janet E Donohue
- Cardiac Networks United Data Core, University of Michigan, Ann Arbor, MI, USA
| | | | - David Wypij
- Department of Cardiology, Boston Children's Hospital, Department of Pediatrics, Harvard Medical School, and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Caren S Goldberg
- Department of Pediatrics, C.S. Mott Children's Hospital, University of Michigan, Ann Arbor, MI, USA
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Ortinau CM, Wypij D, Ilardi D, Rofeberg V, Miller TA, Donohue J, Reichle G, Seed M, Elhoff J, Alexander N, Allen K, Anton C, Bear L, Boucher G, Bragg J, Butcher J, Chen V, Glotzbach K, Hampton L, Lee CK, Ly LG, Marino BS, Martinez-Fernandez Y, Monteiro S, Ortega C, Peyvandi S, Raiees-Dana H, Rollins CK, Sadhwani A, Sananes R, Sanz JH, Schultz AH, Sood E, Tan A, Willen E, Wolfe KR, Goldberg CS. Factors Associated With Attendance for Cardiac Neurodevelopmental Evaluation. Pediatrics 2023; 152:e2022060995. [PMID: 37593818 PMCID: PMC10530086 DOI: 10.1542/peds.2022-060995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/14/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Neurodevelopmental evaluation of toddlers with complex congenital heart disease is recommended but reported frequency is low. Data on barriers to attending neurodevelopmental follow-up are limited. This study aims to estimate the attendance rate for a toddler neurodevelopmental evaluation in a contemporary multicenter cohort and to assess patient and center level factors associated with attending this evaluation. METHODS This is a retrospective cohort study of children born between September 2017 and September 2018 who underwent cardiopulmonary bypass in their first year of life at a center contributing data to the Cardiac Neurodevelopmental Outcome Collaborative and Pediatric Cardiac Critical Care Consortium clinical registries. The primary outcome was attendance for a neurodevelopmental evaluation between 11 and 30 months of age. Sociodemographic and medical characteristics and center factors specific to neurodevelopmental program design were considered as predictors for attendance. RESULTS Among 2385 patients eligible from 16 cardiac centers, the attendance rate was 29.0% (692 of 2385), with a range of 7.8% to 54.3% across individual centers. In multivariable logistic regression models, hospital-initiated (versus family-initiated) scheduling for neurodevelopmental evaluation had the largest odds ratio in predicting attendance (odds ratio = 4.24, 95% confidence interval, 2.74-6.55). Other predictors of attendance included antenatal diagnosis, absence of Trisomy 21, higher Society of Thoracic Surgeons-European Association for Cardio-Thoracic Surgery mortality category, longer postoperative length of stay, private insurance, and residing a shorter distance from the hospital. CONCLUSIONS Attendance rates reflect some improvement but remain low. Changes to program infrastructure and design and minimizing barriers affecting access to care are essential components for improving neurodevelopmental care and outcomes for children with congenital heart disease.
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Affiliation(s)
- Cynthia M. Ortinau
- Department of Pediatrics, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - David Wypij
- Department of Cardiology, Boston Children’s Hospital, Boston, Massachusetts, United States; Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, United States; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States
| | - Dawn Ilardi
- Department of Neuropsychology, Children’s Healthcare of Atlanta, Atlanta, Georgia, United States; Department of Rehabilitation Medicine, Emory University, Atlanta, Georgia, United States
| | - Valerie Rofeberg
- Department of Cardiology, Boston Children’s Hospital, Boston, Massachusetts, United States
| | - Thomas A. Miller
- Division of Cardiology, Maine Medical Center, Portland, Maine, United States
| | - Janet Donohue
- Department of Pediatrics, C.S. Mott Children’s Hospital, University of Michigan, Ann Arbor, Michigan, United States
| | - Garrett Reichle
- Department of Pediatrics, C.S. Mott Children’s Hospital, University of Michigan, Ann Arbor, Michigan, United States
| | - Mike Seed
- Department of Paediatrics, Division of Paediatric Cardiology, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Justin Elhoff
- Department of Pediatrics, Division of Critical Care Medicine, Baylor School of Medicine, Houston, Texas, United States
| | - Nneka Alexander
- Department of Neuropsychology, Children’s Healthcare of Atlanta, Atlanta, Georgia, United States
| | - Kiona Allen
- Department of Pediatrics, Division of Cardiology, Ann & Robert H. Lurie Children’s Hospital of Chicago, Northwestern Feinberg School of Medicine, Chicago, Illinois, United States
| | - Corinne Anton
- Department of Cardiology, Children’s Health, Dallas, Texas, United States; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, Texas, United States
| | - Laurel Bear
- Department of Pediatrics, Medical College of Wisconsin, Milwaukee, Wisconsin, United States
| | - Gina Boucher
- Phoenix Children’s Hospital Heart Center, Phoenix, Arizona, United States
| | - Jennifer Bragg
- Department of Pediatrics, Mount Sinai Hospital, New York, New York, United States
| | - Jennifer Butcher
- Department of Pediatrics, C.S. Mott Children’s Hospital, University of Michigan, Ann Arbor, Michigan, United States
| | - Victoria Chen
- Department of Pediatrics, Division of Developmental-Behavioral Pediatrics, Cohen Children’s Medical Center, New Hyde Park, New York, United States; Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, New York, United States
| | - Kristi Glotzbach
- Department of Pediatrics, Division of Critical Care Medicine, University of Utah, Salt Lake City, Utah, United States
| | - Lyla Hampton
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
| | - Caroline K. Lee
- Department of Pediatrics, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Linh G. Ly
- Department of Paediatrics, Division of Neonatology, The Hospital for Sick Children, University of Toronto, Toronto, Canada
| | - Bradley S. Marino
- Department of Pediatric Cardiology, Cleveland Clinic Children’s, Cleveland, Ohio, United States
| | | | - Sonia Monteiro
- Department of Pediatrics, Baylor School of Medicine, Houston, Texas, United States
| | - Christina Ortega
- Department of Psychology, Joe DiMaggio Children’s Hospital, Hollywood, Florida, United States
| | - Shabnam Peyvandi
- University of California San Francisco Benioff Children’s Hospital, San Francisco, California, United States
| | | | - Caitlin K. Rollins
- Department of Neurology, Boston Children’s Hospital, Boston, Massachusetts, United States; Department of Neurology, Harvard Medical School, Boston, Massachusetts, United States
| | - Anjali Sadhwani
- Department of Psychiatry and Behavioral Sciences, Boston Children’s Hospital, Boston, Massachusetts, United States; Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, United States
| | - Renee Sananes
- Department of Psychology, Division of Cardiology, The Hospital for Sick Children, Department of Pediatrics, University of Toronto, Toronto, Canada
| | - Jacqueline H. Sanz
- Division of Neuropsychology, Children’s National Hospital; Departments of Psychiatry and Behavioral Sciences & Pediatrics, The George Washington University School of Medicine, Washington D.C., United States
| | - Amy H. Schultz
- Division of Cardiology, Seattle Children’s Hospital, University of Washington School of Medicine, Seattle, Washington, United States
| | - Erica Sood
- Nemours Cardiac Center, Nemours Children’s Health, Wilmington, Delaware, United States; Department of Pediatrics, Thomas Jefferson University, Philadelphia, Pennsylvania, United States
| | - Alexander Tan
- Department of Neuropsychology, Children’s Health Orange County, Orange, California, United States
| | - Elizabeth Willen
- Department of Pediatrics, University of Missouri Kansas City School of Medicine, Kansas City, Missouri, United States
| | - Kelly R. Wolfe
- Section of Neurology, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, United States
| | - Caren S. Goldberg
- Department of Pediatrics, C.S. Mott Children’s Hospital, University of Michigan, Ann Arbor, Michigan, United States
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O'Hare CB, Mangin-Heimos KS, Gu H, Edmunds M, Bebbington M, Lee CK, He M, Ortinau CM. Placental delayed villous maturation is associated with fetal congenital heart disease. Am J Obstet Gynecol 2023; 228:231.e1-231.e11. [PMID: 35985515 PMCID: PMC10436378 DOI: 10.1016/j.ajog.2022.08.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/31/2022] [Accepted: 08/07/2022] [Indexed: 01/28/2023]
Abstract
BACKGROUND The placenta is crucial for the overall development and lifelong health of the fetus. Abnormal placental development and function occur in pregnancies with fetal congenital heart disease. However, studies that use standardized diagnostic criteria and incorporate control populations are lacking. This limits the generalizability of current research and the ability to determine the specific placental abnormalities associated with congenital heart disease. OBJECTIVE This study applied consensus statement guidelines (known as the Amsterdam criteria) for placental pathology interpretation to compare the frequency and pattern of abnormalities in pregnancies with fetal congenital heart disease to demographically matched control pregnancies and evaluate for differences in placental abnormalities by cardiac physiology. STUDY DESIGN A single-center retrospective cohort study was conducted from January 2013 to June 2019. Infants with a prenatal diagnosis of moderate-severe congenital heart disease who were born at ≥37 weeks of gestation were included. A control group born at ≥37 weeks of gestation but without fetal congenital heart disease or other major pregnancy complications was matched to the congenital heart disease group on maternal race and ethnicity and infant sex. Using the Amsterdam criteria, placental pathology findings were categorized as delayed villous maturation, maternal vascular malperfusion, fetal vascular malperfusion, and inflammatory lesions. The frequency of placental abnormalities was compared between groups, and logistic regression was performed to evaluate the association of clinical and sociodemographic factors with delayed villous maturation, maternal vascular malperfusion, and fetal vascular malperfusion. RESULTS There were 194 pregnancies with fetal congenital heart disease and 105 controls included, of whom 83% in the congenital heart disease group and 82% in the control group were of non-Hispanic White race and ethnicity. Compared with controls, pregnancies with fetal congenital heart disease had higher rates of delayed villous maturation (6% vs 19%; P<.001) and maternal vascular malperfusion (19% vs 34%; P=.007) but not fetal vascular malperfusion (6% vs 10%; P=.23). Infants with congenital heart disease with 2-ventricle anatomy displayed the highest odds of delayed villous maturation compared with controls (odds ratio, 5.5; 95% confidence interval, 2.2-15.7; P<.01). Maternal vascular malperfusion was 2.2 times higher (P=.02) for infants with 2-ventricle anatomy and 2.9 times higher (P=.02) for infants with single-ventricle physiology with pulmonic obstruction. Within the congenital heart disease group, delayed villous maturation was associated with higher maternal body mass index, polyhydramnios, larger infant birth head circumference, and infant respiratory support in the delivery room, whereas maternal vascular malperfusion was associated with oligohydramnios. In multivariable models adjusting for cardiac diagnosis, associations of delayed villous maturation persisted for infant birth head circumference (odds ratio, 1.2; 95% confidence interval, 1.0-1.5; P=.02) and infant respiratory support in the delivery room (odds ratio, 3.0; 95% confidence interval, 1.3-6.5; P=.007). CONCLUSION Pregnancies with fetal congenital heart disease displayed higher rates of delayed villous maturation and maternal vascular malperfusion than controls, suggesting that placental maldevelopment may relate to maternal factors. Future investigations are needed to determine the association of these abnormalities with postnatal infant outcomes.
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Affiliation(s)
- Clare B O'Hare
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO.
| | - Kathryn S Mangin-Heimos
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Hongjie Gu
- Division of Biostatistics, Washington University School of Medicine in St. Louis, St. Louis, MO
| | | | - Michael Bebbington
- Department of Women's Health, Dell Medical School, The University of Texas at Austin, Austin, TX
| | - Caroline K Lee
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Mai He
- Department of Anatomic and Molecular Pathology, Washington University School of Medicine in St. Louis, St. Louis, MO
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, MO
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Ortinau CM, Smyser CD, Arthur L, Gordon EE, Heydarian HC, Wolovits J, Nedrelow J, Marino BS, Levy VY. Optimizing Neurodevelopmental Outcomes in Neonates With Congenital Heart Disease. Pediatrics 2022; 150:e2022056415L. [PMID: 36317967 PMCID: PMC10435013 DOI: 10.1542/peds.2022-056415l] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/29/2022] [Indexed: 11/05/2022] Open
Abstract
Neurodevelopmental impairment is a common and important long-term morbidity among infants with congenital heart disease (CHD). More than half of those with complex CHD will demonstrate some form of neurodevelopmental, neurocognitive, and/or psychosocial dysfunction requiring specialized care and impacting long-term quality of life. Preventing brain injury and treating long-term neurologic sequelae in this high-risk clinical population is imperative for improving neurodevelopmental and psychosocial outcomes. Thus, cardiac neurodevelopmental care is now at the forefront of clinical and research efforts. Initial research primarily focused on neurocritical care and operative strategies to mitigate brain injury. As the field has evolved, investigations have shifted to understanding the prenatal, genetic, and environmental contributions to impaired neurodevelopment. This article summarizes the recent literature detailing the brain abnormalities affecting neurodevelopment in children with CHD, the impact of genetics on neurodevelopmental outcomes, and the best practices for neonatal neurocritical care, focusing on developmental care and parental support as new areas of importance. A framework is also provided for the infrastructure and resources needed to support CHD families across the continuum of care settings.
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Affiliation(s)
- Cynthia M. Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri
| | - Christopher D. Smyser
- Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
| | - Lindsay Arthur
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, Arkansas
| | - Erin E. Gordon
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Haleh C. Heydarian
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Cardiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Joshua Wolovits
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jonathan Nedrelow
- Department of Neonatology, Cook Children’s Medical Center, Fort Worth, Texas
| | - Bradley S. Marino
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Divisions of Cardiology and Critical Care Medicine, Ann & Robert H. Lurie Children’s Hospital of Chicago
| | - Victor Y. Levy
- Department of Pediatrics, Stanford University School of Medicine, Lucile Packard Children’s Hospital, Palo Alto, California
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Yun HJ, Lee HJ, Lee JY, Tarui T, Rollins CK, Ortinau CM, Feldman HA, Grant PE, Im K. Quantification of sulcal emergence timing and its variability in early fetal life: Hemispheric asymmetry and sex difference. Neuroimage 2022; 263:119629. [PMID: 36115591 PMCID: PMC10011016 DOI: 10.1016/j.neuroimage.2022.119629] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 08/07/2022] [Accepted: 09/12/2022] [Indexed: 12/25/2022] Open
Abstract
Human fetal brains show regionally different temporal patterns of sulcal emergence following a regular timeline, which may be associated with spatiotemporal patterns of gene expression among cortical regions. This study aims to quantify the timing of sulcal emergence and its temporal variability across typically developing fetuses by fitting a logistic curve to presence or absence of sulcus. We found that the sulcal emergence started from the central to the temporo-parieto-occipital lobes and frontal lobe, and the temporal variability of emergence in most of the sulci was similar between 1 and 2 weeks. Small variability (< 1 week) was found in the left central and postcentral sulci and larger variability (>2 weeks) was shown in the bilateral occipitotemporal and left superior temporal sulci. The temporal variability showed a positive correlation with the emergence timing that may be associated with differential contributions between genetic and environmental factors. Our statistical analysis revealed that the right superior temporal sulcus emerged earlier than the left. Female fetuses showed a trend of earlier sulcal emergence in the right superior temporal sulcus, lower temporal variability in the right intraparietal sulcus, and higher variability in the right precentral sulcus compared to male fetuses. Our quantitative and statistical approach quantified the temporal patterns of sulcal emergence in detail that can be a reference for assessing the normality of developing fetal gyrification.
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Affiliation(s)
- Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Hyun Ju Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Joo Young Lee
- Department of Pediatrics, Hanyang University College of Medicine, Seoul 04763, Korea (the Republic of)
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA 02115, United States
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63130, United States
| | - Henry A Feldman
- Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Institutional Centers for Clinical and Translational Research, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States; Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Ave, Boston, MA 02115, United States; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States.
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Sood E, Gramszlo C, Perez Ramirez A, Braley K, Butler SC, Davis JA, Divanovic AA, Edwards LA, Kasparian N, Kelly SL, Neely T, Ortinau CM, Riegel E, Shillingford AJ, Kazak AE. Partnering With Stakeholders to Inform the Co-Design of a Psychosocial Intervention for Prenatally Diagnosed Congenital Heart Disease. J Patient Exp 2022; 9:23743735221092488. [PMID: 35493441 PMCID: PMC9039438 DOI: 10.1177/23743735221092488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Input from diverse stakeholders is critical to the process of designing healthcare interventions. This study applied a novel mixed-methods, stakeholder-engaged approach to co-design a psychosocial intervention for mothers expecting a baby with congenital heart disease (CHD) and their partners to promote family wellbeing. The research team included parents and clinicians from 8 health systems. Participants were 41 diverse parents of children with prenatally diagnosed CHD across the 8 health systems. Qualitative data were collected through online crowdsourcing and quantitative data were collected through electronic surveys to inform intervention co-design. Phases of intervention co-design were: (I) Engage stakeholders in selection of intervention goals/outcomes; (II) Engage stakeholders in selection of intervention elements; (III) Obtain stakeholder input to increase intervention uptake/utility; (IV) Obtain stakeholder input on aspects of intervention design; and (V) Obtain stakeholder input on selection of outcome measures. Parent participants anticipated the resulting intervention, HEARTPrep, would be acceptable, useful, and feasible for parents expecting a baby with CHD. This model of intervention co-design could be used for the development of healthcare interventions across chronic diseases.
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Affiliation(s)
- Erica Sood
- Nemours Cardiac Center, Nemours Children’s Hospital Delaware, Wilmington, DE, USA
- Nemours Center for Healthcare Delivery Science, Nemours Children’s Hospital Delaware, Wilmington, DE, USA
- Department of Pediatrics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Colette Gramszlo
- Nemours Cardiac Center, Nemours Children’s Hospital Delaware, Wilmington, DE, USA
| | - Alejandra Perez Ramirez
- Nemours Center for Healthcare Delivery Science, Nemours Children’s Hospital Delaware, Wilmington, DE, USA
| | - Katherine Braley
- Nemours Cardiac Center, Nemours Children’s Hospital Florida, Orlando, FL, USA
| | | | - Jo Ann Davis
- Department of Pediatrics, Nationwide Children’s Hospital, Columbus, OH, USA
| | - Allison A Divanovic
- Department of Pediatrics, Cincinnati Children’s Hospital, Cincinnati, OH, USA
| | | | - Nadine Kasparian
- Center for Heart Disease and Mental Health, Department of Pediatrics, Cincinnati Children’s Hospital, Cincinnati, OH, USA
| | - Sarah L Kelly
- Departments of Pediatrics and Psychiatry, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
| | - Erin Riegel
- Parent Research Partner, Wilmington, DE, USA
| | | | - Anne E Kazak
- Nemours Center for Healthcare Delivery Science, Nemours Children’s Hospital Delaware, Wilmington, DE, USA
- Department of Pediatrics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
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8
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Sadhwani A, Wypij D, Rofeberg V, Gholipour A, Mittleman M, Rohde J, Velasco-Annis C, Calderon J, Friedman KG, Tworetzky W, Grant PE, Soul JS, Warfield SK, Newburger JW, Ortinau CM, Rollins CK. Fetal Brain Volume Predicts Neurodevelopment in Congenital Heart Disease. Circulation 2022; 145:1108-1119. [PMID: 35143287 PMCID: PMC9007882 DOI: 10.1161/circulationaha.121.056305] [Citation(s) in RCA: 49] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Neurodevelopmental impairment is common in children with congenital heart disease (CHD), but postnatal variables explain only 30% of the variance in outcomes. To explore whether the antecedents for neurodevelopmental disabilities might begin in utero, we analyzed whether fetal brain volume predicted subsequent neurodevelopmental outcome in children with CHD. METHODS Fetuses with isolated CHD and sociodemographically comparable healthy control fetuses underwent fetal brain magnetic resonance imaging and 2-year neurodevelopmental evaluation with the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) and the Adaptive Behavior Assessment System, Third Edition (ABAS-3). Hierarchical regression evaluated potential predictors of Bayley-III and ABAS-3 outcomes in the CHD group, including fetal total brain volume adjusted for gestational age and sex, sociodemographic characteristics, birth measures, and medical history. RESULTS The CHD group (n=52) had lower Bayley-III cognitive, language, and motor scores than the control group (n=26), but fetal brain volumes were similar. Within the CHD group, larger fetal total brain volume correlated with higher Bayley-III cognitive, language, and motor scores and ABAS-3 adaptive functioning scores (r=0.32-0.47; all P<0.05), but this was not noted in the control group. Fetal brain volume predicted 10% to 21% of the variance in neurodevelopmental outcome measures in univariate analyses. Multivariable models that also included social class and postnatal factors explained 18% to 45% of the variance in outcome, depending on developmental domain. Moreover, in final multivariable models, fetal brain volume was the most consistent predictor of neurodevelopmental outcome across domains. CONCLUSIONS Small fetal brain volume is a strong independent predictor of 2-year neurodevelopmental outcomes and may be an important imaging biomarker of future neurodevelopmental risk in CHD. Future studies are needed to support this hypothesis. Our findings support inclusion of fetal brain volume in risk stratification models and as a possible outcome in fetal neuroprotective intervention studies.
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Affiliation(s)
- Anjali Sadhwani
- Department of Psychiatry, Boston Children’s Hospital, Boston, MA
- Department of Psychiatry, Harvard Medical School, Boston, MA
| | - David Wypij
- Department of Cardiology, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics, Harvard Medical School, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Valerie Rofeberg
- Department of Cardiology, Boston Children’s Hospital, Boston, MA
| | - Ali Gholipour
- Department of Radiology, Boston Children’s Hospital, Boston, MA
- Department of Radiology, Harvard Medical School, Boston, MA
| | | | - Julia Rohde
- Department of Neurology, Boston Children’s Hospital, Boston, MA
| | | | - Johanna Calderon
- Department of Psychiatry, Boston Children’s Hospital, Boston, MA
- Department of Psychiatry, Harvard Medical School, Boston, MA
| | - Kevin G. Friedman
- Department of Cardiology, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics, Harvard Medical School, Boston, MA
| | - Wayne Tworetzky
- Department of Cardiology, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics, Harvard Medical School, Boston, MA
| | - P. Ellen Grant
- Department of Radiology, Boston Children’s Hospital, Boston, MA
- Department of Radiology, Harvard Medical School, Boston, MA
| | - Janet S. Soul
- Department of Neurology, Boston Children’s Hospital, Boston, MA
- Department of Neurology, Harvard Medical School, Boston, MA
| | | | - Jane W. Newburger
- Department of Cardiology, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics, Harvard Medical School, Boston, MA
| | | | - Caitlin K. Rollins
- Department of Neurology, Boston Children’s Hospital, Boston, MA
- Department of Neurology, Harvard Medical School, Boston, MA
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9
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Hong J, Yun HJ, Park G, Kim S, Ou Y, Vasung L, Rollins CK, Ortinau CM, Takeoka E, Akiyama S, Tarui T, Estroff JA, Grant PE, Lee JM, Im K. Optimal Method for Fetal Brain Age Prediction Using Multiplanar Slices From Structural Magnetic Resonance Imaging. Front Neurosci 2021; 15:714252. [PMID: 34707474 PMCID: PMC8542770 DOI: 10.3389/fnins.2021.714252] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 09/08/2021] [Indexed: 11/23/2022] Open
Abstract
The accurate prediction of fetal brain age using magnetic resonance imaging (MRI) may contribute to the identification of brain abnormalities and the risk of adverse developmental outcomes. This study aimed to propose a method for predicting fetal brain age using MRIs from 220 healthy fetuses between 15.9 and 38.7 weeks of gestational age (GA). We built a 2D single-channel convolutional neural network (CNN) with multiplanar MRI slices in different orthogonal planes without correction for interslice motion. In each fetus, multiple age predictions from different slices were generated, and the brain age was obtained using the mode that determined the most frequent value among the multiple predictions from the 2D single-channel CNN. We obtained a mean absolute error (MAE) of 0.125 weeks (0.875 days) between the GA and brain age across the fetuses. The use of multiplanar slices achieved significantly lower prediction error and its variance than the use of a single slice and a single MRI stack. Our 2D single-channel CNN with multiplanar slices yielded a significantly lower stack-wise MAE (0.304 weeks) than the 2D multi-channel (MAE = 0.979, p < 0.001) and 3D (MAE = 1.114, p < 0.001) CNNs. The saliency maps from our method indicated that the anatomical information describing the cortex and ventricles was the primary contributor to brain age prediction. With the application of the proposed method to external MRIs from 21 healthy fetuses, we obtained an MAE of 0.508 weeks. Based on the external MRIs, we found that the stack-wise MAE of the 2D single-channel CNN (0.743 weeks) was significantly lower than those of the 2D multi-channel (1.466 weeks, p < 0.001) and 3D (1.241 weeks, p < 0.001) CNNs. These results demonstrate that our method with multiplanar slices accurately predicts fetal brain age without the need for increased dimensionality or complex MRI preprocessing steps.
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Affiliation(s)
- Jinwoo Hong
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Gilsoon Park
- USC Mark and Mary Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States
| | - Seonggyu Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Yangming Ou
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Computational Health Informatics Program, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Lana Vasung
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
| | - Emiko Takeoka
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, United States
| | - Shizuko Akiyama
- Center for Perinatal and Neonatal Medicine, Tohoku University Hospital, Sendai, Japan
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Boston, MA, United States
| | - Judy A Estroff
- Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Patricia Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States.,Division of Newborn Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
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10
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McPherson C, Frymoyer A, Ortinau CM, Miller SP, Groenendaal F. Management of comfort and sedation in neonates with neonatal encephalopathy treated with therapeutic hypothermia. Semin Fetal Neonatal Med 2021; 26:101264. [PMID: 34215538 PMCID: PMC8900710 DOI: 10.1016/j.siny.2021.101264] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Ensuring comfort for neonates undergoing therapeutic hypothermia (TH) after neonatal encephalopathy (NE) exemplifies a vital facet of neonatal neurocritical care. Physiologic markers of stress are frequently present in these neonates. Non-pharmacologic comfort measures form the foundation of care, benefitting both the neonate and parents. Pharmacological sedatives may also be indicated, yet have the potential to both mitigate and intensify the neurotoxicity of a hypoxic-ischemic insult. Morphine represents current standard of care with a history of utilization and extensive pharmacokinetic data to guide safe and effective dosing. Dexmedetomidine, as an alternative to morphine, has several appealing characteristics, including neuroprotective effects in animal models; robust pharmacokinetic studies in neonates with NE treated with TH are required to ensure a safe and effective standard dosing approach. Future studies in neonates treated with TH must address comfort, adverse events, and long-term outcomes in the context of specific sedation practices.
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Affiliation(s)
- Christopher McPherson
- Department of Pediatrics, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO, 63110, USA.
| | - Adam Frymoyer
- Department of Pediatrics, Stanford University, 750 Welch Road, Suite 315, Palo Alto, CA, 94304, USA.
| | - Cynthia M. Ortinau
- Department of Pediatrics, Washington University School of Medicine, 660 South Euclid Ave., St. Louis, MO, 63110, USA
| | - Steven P. Miller
- Department of Pediatrics, The Hospital for Sick Children and the University of Toronto, 555 University Avenue, Toronto, ON, Canada
| | - Floris Groenendaal
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht and Utrecht University, Lundlaan 6, 3584 EA, Utrecht, Netherlands.
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11
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Lean RE, Ortinau CM. Neonatal Brain Structure and Cognitively Stimulating Parenting Differentially Relate to Cognitive and Behavioral Outcomes of Children Born Very Preterm. Biol Psychiatry Glob Open Sci 2021; 1:87-89. [PMID: 36324996 PMCID: PMC9616377 DOI: 10.1016/j.bpsgos.2021.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 12/01/2022] Open
Affiliation(s)
- Rachel E. Lean
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri
| | - Cynthia M. Ortinau
- Department of Pediatrics, Washington University School of Medicine, St. Louis, Missouri
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12
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O’Hare C, Edmunds M, Gu H, He M, Ortinau CM. FREQUENCY AND PATTERN OF PLACENTAL ABNORMALITIES IN PREGNANCIES WITH FETAL CONGENITAL HEART DISEASE. J Am Coll Cardiol 2021. [DOI: 10.1016/s0735-1097(21)01833-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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13
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Dou H, Karimi D, Rollins CK, Ortinau CM, Vasung L, Velasco-Annis C, Ouaalam A, Yang X, Ni D, Gholipour A. A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI. IEEE Trans Med Imaging 2021; 40:1123-1133. [PMID: 33351755 PMCID: PMC8016740 DOI: 10.1109/tmi.2020.3046579] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Fetal cortical plate segmentation is essential in quantitative analysis of fetal brain maturation and cortical folding. Manual segmentation of the cortical plate, or manual refinement of automatic segmentations is tedious and time-consuming. Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation. To reduce the burden of manual refinement of segmentations, we have developed a new and powerful deep learning segmentation method. Our method exploits new deep attentive modules with mixed kernel convolutions within a fully convolutional neural network architecture that utilizes deep supervision and residual connections. We evaluated our method quantitatively based on several performance measures and expert evaluations. Results show that our method outperforms several state-of-the-art deep models for segmentation, as well as a state-of-the-art multi-atlas segmentation technique. We achieved average Dice similarity coefficient of 0.87, average Hausdorff distance of 0.96 mm, and average symmetric surface difference of 0.28 mm on reconstructed fetal brain MRI scans of fetuses scanned in the gestational age range of 16 to 39 weeks (28.6± 5.3). With a computation time of less than 1 minute per fetal brain, our method can facilitate and accelerate large-scale studies on normal and altered fetal brain cortical maturation and folding.
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14
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Hong J, Yun HJ, Park G, Kim S, Laurentys CT, Siqueira LC, Tarui T, Rollins CK, Ortinau CM, Grant PE, Lee JM, Im K. Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation. Front Neurosci 2020; 14:591683. [PMID: 33343286 PMCID: PMC7738480 DOI: 10.3389/fnins.2020.591683] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 11/04/2020] [Indexed: 01/14/2023] Open
Abstract
Fetal magnetic resonance imaging (MRI) has the potential to advance our understanding of human brain development by providing quantitative information of cortical plate (CP) development in vivo. However, for a reliable quantitative analysis of cortical volume and sulcal folding, accurate and automated segmentation of the CP is crucial. In this study, we propose a fully convolutional neural network for the automatic segmentation of the CP. We developed a novel hybrid loss function to improve the segmentation accuracy and adopted multi-view (axial, coronal, and sagittal) aggregation with a test-time augmentation method to reduce errors using three-dimensional (3D) information and multiple predictions. We evaluated our proposed method using the ten-fold cross-validation of 52 fetal brain MR images (22.9-31.4 weeks of gestation). The proposed method obtained Dice coefficients of 0.907 ± 0.027 and 0.906 ± 0.031 as well as a mean surface distance error of 0.182 ± 0.058 mm and 0.185 ± 0.069 mm for the left and right, respectively. In addition, the left and right CP volumes, surface area, and global mean curvature generated by automatic segmentation showed a high correlation with the values generated by manual segmentation (R 2 > 0.941). We also demonstrated that the proposed hybrid loss function and the combination of multi-view aggregation and test-time augmentation significantly improved the CP segmentation accuracy. Our proposed segmentation method will be useful for the automatic and reliable quantification of the cortical structure in the fetal brain.
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Affiliation(s)
- Jinwoo Hong
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Hyuk Jin Yun
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Gilsoon Park
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Seonggyu Kim
- Department of Electronic Engineering, Hanyang University, Seoul, South Korea
| | - Cynthia T. Laurentys
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Leticia C. Siqueira
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, United States
- Department of Pediatrics, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, United States
| | - Caitlin K. Rollins
- Department of Neurology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Cynthia M. Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, United States
| | - P. Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
| | - Jong-Min Lee
- Department of Biomedical Engineering, Hanyang University, Seoul, South Korea
| | - Kiho Im
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
- Division of Newborn Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, MA, United States
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15
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Rollins CK, Ortinau CM, Stopp C, Friedman KG, Tworetzky W, Gagoski B, Velasco-Annis C, Afacan O, Vasung L, Beaute JI, Rofeberg V, Estroff JA, Grant PE, Soul JS, Yang E, Wypij D, Gholipour A, Warfield SK, Newburger JW. Regional Brain Growth Trajectories in Fetuses with Congenital Heart Disease. Ann Neurol 2020; 89:143-157. [PMID: 33084086 DOI: 10.1002/ana.25940] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Revised: 10/14/2020] [Accepted: 10/16/2020] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Congenital heart disease (CHD) is associated with abnormal brain development in utero. We applied innovative fetal magnetic resonance imaging (MRI) techniques to determine whether reduced fetal cerebral substrate delivery impacts the brain globally, or in a region-specific pattern. Our novel design included two control groups, one with and the other without a family history of CHD, to explore the contribution of shared genes and/or fetal environment to brain development. METHODS From 2014 to 2018, we enrolled 179 pregnant women into 4 groups: "HLHS/TGA" fetuses with hypoplastic left heart syndrome (HLHS) or transposition of the great arteries (TGA), diagnoses with lowest fetal cerebral substrate delivery; "CHD-other," with other CHD diagnoses; "CHD-related," healthy with a CHD family history; and "optimal control," healthy without a family history. Two MRIs were obtained between 18 and 40 weeks gestation. Random effect regression models assessed group differences in brain volumes and relationships to hemodynamic variables. RESULTS HLHS/TGA (n = 24), CHD-other (50), and CHD-related (34) groups each had generally smaller brain volumes than the optimal controls (71). Compared with CHD-related, the HLHS/TGA group had smaller subplate (-13.3% [standard error = 4.3%], p < 0.01) and intermediate (-13.7% [4.3%], p < 0.01) zones, with a similar trend in ventricular zone (-7.1% [1.9%], p = 0.07). These volumetric reductions were associated with lower cerebral substrate delivery. INTERPRETATION Fetuses with CHD, especially those with lowest cerebral substrate delivery, show a region-specific pattern of small brain volumes and impaired brain growth before 32 weeks gestation. The brains of fetuses with CHD were more similar to those of CHD-related than optimal controls, suggesting genetic or environmental factors also contribute. ANN NEUROL 2021;89:143-157.
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Affiliation(s)
- Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA.,Departments of Neurology, Harvard Medical School, Boston, MA, USA
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
| | - Christian Stopp
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Kevin G Friedman
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA.,Maternal Fetal Care Center, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Wayne Tworetzky
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA.,Maternal Fetal Care Center, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - Borjan Gagoski
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Lana Vasung
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jeanette I Beaute
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - Valerie Rofeberg
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Judy A Estroff
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA.,Maternal Fetal Care Center, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Janet S Soul
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA.,Departments of Neurology, Harvard Medical School, Boston, MA, USA.,Maternal Fetal Care Center, Boston Children's Hospital, Boston, MA, USA
| | - Edward Yang
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - David Wypij
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jane W Newburger
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA
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16
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Jaimes C, Machado‐Rivas F, Afacan O, Khan S, Marami B, Ortinau CM, Rollins CK, Velasco‐Annis C, Warfield SK, Gholipour A. In vivo characterization of emerging white matter microstructure in the fetal brain in the third trimester. Hum Brain Mapp 2020. [DOI: 10.1002/hbm.25006 32374063] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Affiliation(s)
- Camilo Jaimes
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Fetal‐Neonatal Neuroimaging and Developmental Science CenterBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Fedel Machado‐Rivas
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Onur Afacan
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Shadab Khan
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Bahram Marami
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Cynthia M. Ortinau
- Department of PediatricsWashington University in St. Louis School of Medicine St. Louis Missouri
| | - Caitlin K. Rollins
- Harvard Medical School Boston Massachusetts
- Department of NeurologyBoston Children's Hospital Boston Massachusetts
| | | | - Simon K. Warfield
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
| | - Ali Gholipour
- Department of RadiologyBoston Children's Hospital Boston Massachusetts
- Harvard Medical School Boston Massachusetts
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17
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Ortinau CM, Rollins CK, Gholipour A, Yun HJ, Marshall M, Gagoski B, Afacan O, Friedman K, Tworetzky W, Warfield SK, Newburger JW, Inder TE, Grant PE, Im K. Early-Emerging Sulcal Patterns Are Atypical in Fetuses with Congenital Heart Disease. Cereb Cortex 2020; 29:3605-3616. [PMID: 30272144 DOI: 10.1093/cercor/bhy235] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 08/28/2018] [Indexed: 12/30/2022] Open
Abstract
Fetuses with congenital heart disease (CHD) have third trimester alterations in cortical development on brain magnetic resonance imaging (MRI). However, the intersulcal relationships contributing to global sulcal pattern remain unknown. This study applied a novel method for examining the geometric and topological relationships between sulci to fetal brain MRIs from 21-30 gestational weeks in CHD fetuses (n = 19) and typically developing (TD) fetuses (n = 17). Sulcal pattern similarity index (SI) to template fetal brain MRIs was determined for the position, area, and depth for corresponding sulcal basins and intersulcal relationships for each subject. CHD fetuses demonstrated altered global sulcal patterns in the left hemisphere compared with TD fetuses (TD [SI, mean ± SD]: 0.822 ± 0.023, CHD: 0.795 ± 0.030, P = 0.002). These differences were present in the earliest emerging sulci and were driven by differences in the position of corresponding sulcal basins (TD: 0.897 ± 0.024, CHD: 0.878 ± 0.019, P = 0.006) and intersulcal relationships (TD: 0.876 ± 0.031, CHD: 0.857 ± 0.018, P = 0.033). No differences in cortical gyrification index, mean curvature, or surface area were present. These data suggest our methods may be more sensitive than traditional measures for evaluating cortical developmental alterations early in gestation.
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Affiliation(s)
- Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA.,Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA.,Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Division of Newborn Medicine, Boston Children's Hospital Boston, MA, USA
| | - Mackenzie Marshall
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Borjan Gagoski
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kevin Friedman
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Department of Cardiology, Boston Children's Hospital Boston, MA, USA
| | - Wayne Tworetzky
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Department of Cardiology, Boston Children's Hospital Boston, MA, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jane W Newburger
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Department of Cardiology, Boston Children's Hospital Boston, MA, USA
| | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA.,Department of Radiology, Harvard Medical School, Boston, MA, USA.,Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Division of Newborn Medicine, Boston Children's Hospital Boston, MA, USA
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, USA.,Department of Pediatrics, Harvard Medical School, Boston, MA, USA.,Division of Newborn Medicine, Boston Children's Hospital Boston, MA, USA
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18
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Jaimes C, Rofeberg V, Stopp C, Ortinau CM, Gholipour A, Friedman KG, Tworetzky W, Estroff J, Newburger JW, Wypij D, Warfield SK, Yang E, Rollins CK. Association of Isolated Congenital Heart Disease with Fetal Brain Maturation. AJNR Am J Neuroradiol 2020; 41:1525-1531. [PMID: 32646947 DOI: 10.3174/ajnr.a6635] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 04/30/2020] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND PURPOSE Brain MRI of newborns with congenital heart disease show signs of immaturity relative to healthy controls. Our aim was to determine whether the semiquantitative fetal total maturation score can detect abnormalities in brain maturation in fetuses with congenital heart disease in the second and third trimesters. MATERIALS AND METHODS We analyzed data from a prospective study of fetuses with and without congenital heart disease who underwent fetal MR imaging at 25-35 weeks' gestation. Two independent neuroradiologists blinded to the clinical data reviewed and scored all images using the fetal total maturation score. Interrater reliability was evaluated by the intraclass correlation coefficient using the individual reader scores, which were also used to calculate an average score for each subject. Comparisons of the average and individual reader scores between affected and control fetuses and relationships with clinical variables were evaluated using multivariable linear regression. RESULTS Data from 69 subjects (48 cardiac, 21 controls) were included. High concordance was observed between readers with an intraclass correlation coefficient of 0.98 (95% CI, 0.97-0.99). The affected group had significantly lower fetal total maturation scores than the control group (β-estimate, -0.9 [95% CI, -1.5 to -0.4], P = .002), adjusting for gestational age and sex. Averaged fetal total maturation, germinal matrix, myelination, and superior temporal sulcus scores were significantly delayed in fetuses with congenital heart disease versus controls (P < .05 for each). The fetal total maturation score was not significantly associated with any cardiac, anatomic, or physiologic variables. CONCLUSIONS The fetal total maturation score is sensitive to differences in brain maturation between fetuses with isolated congenital heart disease and healthy controls.
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Affiliation(s)
- C Jaimes
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - V Rofeberg
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts
| | - C Stopp
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts
| | - C M Ortinau
- Pediatrics (C.M.O.), Washington University in St. Louis, St. Louis, Missouri
| | - A Gholipour
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - K G Friedman
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - W Tworetzky
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - J Estroff
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - J W Newburger
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - D Wypij
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts.,Biostatistics (D.W.), Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - S K Warfield
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - E Yang
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts.,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
| | - C K Rollins
- From the Departments of Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Cardiology (V.R., C.S., K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Fetal-Neonatal Neuroimaging and Developmental Science Center (C.J.), Boston Children's Hospital, Boston, Massachusetts .,Radiology (C.J., A.G., J.E., S.K.W., E.Y.), Pediatrics (K.G.F., W.T., J.W.N., D.W.), Neurology (C.K.R.), Harvard Medical School, Boston, Massachusetts
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19
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Ortinau CM, Shimony JS. The Congenital Heart Disease Brain: Prenatal Considerations for Perioperative Neurocritical Care. Pediatr Neurol 2020; 108:23-30. [PMID: 32107137 PMCID: PMC7306416 DOI: 10.1016/j.pediatrneurol.2020.01.002] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 12/21/2019] [Accepted: 01/05/2020] [Indexed: 12/17/2022]
Abstract
Altered brain development has been highlighted as an important contributor to adverse neurodevelopmental outcomes in children with congenital heart disease. Abnormalities begin prenatally and include micro- and macrostructural disturbances that lead to an altered trajectory of brain growth throughout gestation. Recent progress in fetal imaging has improved understanding of the neurobiological mechanisms and risk factors for impaired fetal brain development. The impact of the prenatal environment on postnatal neurological care has also gained increased focus. This review summarizes current data on the timing and pattern of altered prenatal brain development in congenital heart disease, the potential mechanisms of these abnormalities, and the association with perioperative neurological complications.
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Affiliation(s)
- Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, Missouri.
| | - Joshua S Shimony
- Mallinkrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri
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20
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Jaimes C, Machado-Rivas F, Afacan O, Khan S, Marami B, Ortinau CM, Rollins CK, Velasco-Annis C, Warfield SK, Gholipour A. In vivo characterization of emerging white matter microstructure in the fetal brain in the third trimester. Hum Brain Mapp 2020; 41:3177-3185. [PMID: 32374063 PMCID: PMC7375105 DOI: 10.1002/hbm.25006] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 03/26/2020] [Accepted: 04/03/2020] [Indexed: 12/13/2022] Open
Abstract
The third trimester of pregnancy is a period of rapid development of fiber bundles in the fetal white matter. Using a recently developed motion‐tracked slice‐to‐volume registration (MT‐SVR) method, we aimed to quantify tract‐specific developmental changes in apparent diffusion coefficient (ADC), fractional anisotropy (FA), and volume in third trimester healthy fetuses. To this end, we reconstructed diffusion tensor images from motion corrected fetal diffusion magnetic resonance imaging data. With an approved protocol, fetal MRI exams were performed on healthy pregnant women at 3 Tesla and included multiple (2–8) diffusion scans of the fetal head (1–2 b = 0 s/mm2 images and 12 diffusion‐sensitized images at b = 500 s/mm2). Diffusion data from 32 fetuses (13 females) with median gestational age (GA) of 33 weeks 4 days were processed with MT‐SVR and deterministic tractography seeded by regions of interest corresponding to 12 major fiber tracts. Multivariable regression analysis was used to evaluate the association of GA with volume, FA, and ADC for each tract. For all tracts, the volume and FA increased, and the ADC decreased with GA. Associations reached statistical significance for: FA and ADC of the forceps major; volume and ADC for the forceps minor; FA, ADC, and volume for the cingulum; ADC, FA, and volume for the uncinate fasciculi; ADC of the inferior fronto‐occipital fasciculi, ADC of the inferior longitudinal fasciculi; and FA and ADC for the corticospinal tracts. These quantitative results demonstrate the complex pattern and rates of tract‐specific, GA‐related microstructural changes of the developing white matter in human fetal brain.
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Affiliation(s)
- Camilo Jaimes
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Fedel Machado-Rivas
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Shadab Khan
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Bahram Marami
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Caitlin K Rollins
- Harvard Medical School, Boston, Massachusetts.,Department of Neurology, Boston Children's Hospital, Boston, Massachusetts
| | | | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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21
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Yun HJ, Vasung L, Tarui T, Rollins CK, Ortinau CM, Grant PE, Im K. Temporal Patterns of Emergence and Spatial Distribution of Sulcal Pits During Fetal Life. Cereb Cortex 2020; 30:4257-4268. [PMID: 32219376 DOI: 10.1093/cercor/bhaa053] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 01/16/2020] [Accepted: 02/14/2020] [Indexed: 12/23/2022] Open
Abstract
Sulcal pits are thought to represent the first cortical folds of primary sulci during neurodevelopment. The uniform spatial distribution of sulcal pits across individuals is hypothesized to be predetermined by a human-specific protomap which is related to functional localization under genetic controls in early fetal life. Thus, it is important to characterize temporal and spatial patterns of sulcal pits in the fetal brain that would provide additional information of functional development of the human brain and crucial insights into abnormal cortical maturation. In this paper, we investigated temporal patterns of emergence and spatial distribution of sulcal pits using 48 typically developing fetal brains in the second half of gestation. We found that the position and spatial variance of sulcal pits in the fetal brain are similar to those in the adult brain, and they are also temporally uniform against dynamic brain growth during fetal life. Furthermore, timing of pit emergence shows a regionally diverse pattern that may be associated with the subdivisions of the protomap. Our findings suggest that sulcal pits in the fetal brain are useful anatomical landmarks containing detailed information of functional localization in early cortical development and maintaining their spatial distribution throughout the human lifetime.
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Affiliation(s)
- Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Lana Vasung
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Tomo Tarui
- Mother Infant Research Institute, Tufts Medical Center, Tufts University School of Medicine, Boston, MA 02111, USA.,Department of Pediatrics, Tufts Medical Center, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.,Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
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22
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Yun HJ, Chung AW, Vasung L, Yang E, Tarui T, Rollins CK, Ortinau CM, Grant PE, Im K. Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification. Neuroimage 2019; 188:473-482. [PMID: 30553042 PMCID: PMC6452886 DOI: 10.1016/j.neuroimage.2018.12.023] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 11/20/2018] [Accepted: 12/11/2018] [Indexed: 12/28/2022] Open
Abstract
Accurate parcellation and labeling of primary cortical sulci in the human fetal brain is useful for regional analysis of brain development. However, human fetal brains show large spatio-temporal changes in brain size, cortical folding patterns, and relative position/size of cortical regions, making accurate automatic sulcal labeling challenging. Here, we introduce a novel sulcal labeling method for the fetal brain using spatio-temporal gyrification information from multiple fetal templates. First, spatial probability maps of primary sulci are generated on the templates from 23 to 33 gestational weeks and registered to an individual brain. Second, temporal weights, which determine the level of contribution to the labeling for each template, are defined by similarity of gyrification between the individual and the template brains. We combine the weighted sulcal probability maps from the multiple templates and adopt sulcal basin-wise approach to assign sulcal labels to each basin. Our labeling method was applied to 25 fetuses (22.9-29.6 gestational weeks), and the labeling accuracy was compared to manually assigned sulcal labels using the Dice coefficient. Moreover, our multi-template basin-wise approach was compared to a single-template approach, which does not consider the temporal dynamics of gyrification, and a fully-vertex-wise approach. The mean accuracy of our approach was 0.958 across subjects, significantly higher than the accuracies of the other approaches. This novel approach shows highly accurate sulcal labeling and provides a reliable means to examine characteristics of cortical regions in the fetal brain.
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Affiliation(s)
- Hyuk Jin Yun
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Ai Wern Chung
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Lana Vasung
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Edward Yang
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Tomo Tarui
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Mother Infant Research Institute, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, 02111, USA; Department of Pediatrics, Tufts Medical Center, Tufts University School of Medicine, Boston, MA, 02111, USA
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, 63110, USA
| | - P Ellen Grant
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Kiho Im
- Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA; Division of Newborn Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
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23
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Khan S, Vasung L, Marami B, Rollins CK, Afacan O, Ortinau CM, Yang E, Warfield SK, Gholipour A. Fetal brain growth portrayed by a spatiotemporal diffusion tensor MRI atlas computed from in utero images. Neuroimage 2019; 185:593-608. [PMID: 30172006 PMCID: PMC6289660 DOI: 10.1016/j.neuroimage.2018.08.030] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Revised: 07/31/2018] [Accepted: 08/13/2018] [Indexed: 12/17/2022] Open
Abstract
Altered structural fetal brain development has been linked to neuro-developmental disorders. These structural alterations can be potentially detected in utero using diffusion tensor imaging (DTI). However, acquisition and reconstruction of in utero fetal brain DTI remains challenging. Until now, motion-robust DTI methods have been employed for reconstruction of in utero fetal DTIs. However, due to the unconstrained fetal motion and permissible in utero acquisition times, these methods yielded limited success and have typically resulted in noisy DTIs. Consequently, atlases and methods that could enable groupwise studies, multi-modality imaging, and computer-aided diagnosis from in utero DTIs have not yet been developed. This paper presents the first DTI atlas of the fetal brain computed from in utero diffusion-weighted images. For this purpose an algorithm for computing an unbiased spatiotemporal DTI atlas, which integrates kernel-regression in age with a diffeomorphic tensor-to-tensor registration of motion-corrected and reconstructed individual fetal brain DTIs, was developed. Our new algorithm was applied to a set of 67 fetal DTI scans acquired from healthy fetuses each scanned at a gestational age between 21 and 39 weeks. The neurodevelopmental trends in the fetal brain, characterized by the atlas, were qualitatively and quantitatively compared with the observations reported in prior ex vivo and in utero studies, and with results from imaging gestational-age equivalent preterm infants. Our major findings revealed early presence of limbic fiber bundles, followed by the appearance and maturation of projection pathways (characterized by an age related increase in FA) during late 2nd and early 3rd trimesters. During the 3rd trimester association fiber bundles become evident. In parallel with the appearance and maturation of fiber bundles, from 21 to 39 gestational weeks gradual disappearance of the radial coherence of the telencephalic wall was qualitatively identified. These results and analyses show that our DTI atlas of the fetal brain is useful for reliable detection of major neuronal fiber bundle pathways and for characterization of the fetal brain reorganization that occurs in utero. The atlas can also serve as a useful resource for detection of normal and abnormal fetal brain development in utero.
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Affiliation(s)
- Shadab Khan
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Lana Vasung
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bahram Marami
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Caitlin K Rollins
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Onur Afacan
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA
| | - Edward Yang
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
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24
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Ortinau CM, Mangin-Heimos K, Moen J, Alexopoulos D, Inder TE, Gholipour A, Shimony JS, Eghtesady P, Schlaggar BL, Smyser CD. Prenatal to postnatal trajectory of brain growth in complex congenital heart disease. Neuroimage Clin 2018; 20:913-922. [PMID: 30308377 PMCID: PMC6178192 DOI: 10.1016/j.nicl.2018.09.029] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2018] [Revised: 08/21/2018] [Accepted: 09/25/2018] [Indexed: 01/10/2023]
Abstract
Altered brain development is a common feature of the neurological sequelae of complex congenital heart disease (CHD). These alterations include abnormalities in brain size and growth that begin prenatally and persist postnatally. However, the longitudinal trajectory of changes in brain volume from the prenatal to postnatal environment have not been investigated. We aimed to evaluate the trajectory of brain growth in a cohort of patients with complex CHD (n = 16) and healthy controls (n = 15) to test the hypothesis that patients with complex CHD would have smaller total brain volume (TBV) prenatally, which would become increasingly prominent by three months of age. Participants underwent fetal magnetic resonance imaging (MRI) at a mean of 32 weeks gestation, a preoperative/neonatal MRI shortly after birth, a postoperative MRI (CHD only), and a 3-month MRI to evaluate the trajectory of brain growth. Three-dimensional volumetric analysis was applied to the MRI data to measure TBV, as well as tissue-specific volumes of the cortical gray matter (CGM), white matter (WM), subcortical (deep nuclear) gray matter (SCGM), cerebellum, and cerebrospinal fluid (CSF). A random coefficients model was used to investigate longitudinal changes in TBV and demonstrated an altered trajectory of brain growth in the CHD population. The estimated slope for TBV from fetal to 3-month MRI was 11.5 cm3 per week for CHD infants compared to 16.7 cm3 per week for controls (p = 0.0002). Brain growth followed a similar trajectory for the CGM (p < 0.0001), SCGM (p = 0.002), and cerebellum (p = 0.005). There was no difference in growth of the WM (p = 0.30) or CSF (p = 0.085). Brain injury was associated with reduced TBV at 3-month MRI (p = 0.02). After removing infants with brain injury from the model, an altered trajectory of brain growth persisted in CHD infants (p = 0.006). These findings extend the existing literature by demonstrating longitudinal impairments in brain development in the CHD population and emphasize the global nature of disrupted brain growth from the prenatal environment through early infancy.
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Affiliation(s)
- Cynthia M Ortinau
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA.
| | - Kathryn Mangin-Heimos
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Joseph Moen
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Terrie E Inder
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ali Gholipour
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Joshua S Shimony
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Pirooz Eghtesady
- Division of Pediatric Cardiothoracic Surgery, Washington University in St. Louis, St. Louis, MO, USA
| | - Bradley L Schlaggar
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA; Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA; Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA; Department of Neuroscience, Washington University in St. Louis, St. Louis, MO, USA
| | - Christopher D Smyser
- Department of Pediatrics, Washington University in St. Louis, St. Louis, MO, USA; Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA; Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
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Khan S, Rollins CK, Ortinau CM, Afacan O, Warfield SK, Gholipour A. Tract-Specific Group Analysis in Fetal Cohorts Using in utero Diffusion Tensor Imaging. ACTA ACUST UNITED AC 2018; 11072:28-35. [PMID: 32869014 DOI: 10.1007/978-3-030-00931-1_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
Diffusion tensor imaging (DTI) based group analysis has helped uncover the impact of white matter injuries in a wide range of studies involving subjects from preterm neonates to adults. The application of these methods to fetal cohorts, however, has been hampered by the challenging nature of in utero fetal DTI caused by unconstrained fetal motion, limited scan times, and limited signal-to-noise ratio. We present a framework that addresses these issues to systematically evaluate group differences in fetal cohorts. A motion-robust DTI computation approach with a new unbiased DTI template construction method is unified with kernel-regression in age and tensor-specific registration to normalize DTI volumes in an unbiased space. A robust statistical approach is used to map region-specific group differences to the medial representation of the tracts of interest. The proposed approach was applied and showed, for the first time, differences in local white matter fractional anisotropy based on in utero DTI of fetuses with congenital heart disease and age-matched healthy controls. This paper suggests the need for fetal-specific pipelines to be used for DTI-based group analysis involving fetal cohorts.
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Affiliation(s)
- Shadab Khan
- Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA
| | - Caitlin K Rollins
- Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA
| | | | - Onur Afacan
- Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA
| | - Simon K Warfield
- Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA
| | - Ali Gholipour
- Boston Children's Hospital and Harvard Medical School, 360 Longwood Avenue, Boston, MA, USA
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Garcia KE, Robinson EC, Alexopoulos D, Dierker DL, Glasser MF, Coalson TS, Ortinau CM, Rueckert D, Taber LA, Van Essen DC, Rogers CE, Smyser CD, Bayly PV. Dynamic patterns of cortical expansion during folding of the preterm human brain. Proc Natl Acad Sci U S A 2018; 115:3156-3161. [PMID: 29507201 PMCID: PMC5866555 DOI: 10.1073/pnas.1715451115] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
During the third trimester of human brain development, the cerebral cortex undergoes dramatic surface expansion and folding. Physical models suggest that relatively rapid growth of the cortical gray matter helps drive this folding, and structural data suggest that growth may vary in both space (by region on the cortical surface) and time. In this study, we propose a unique method to estimate local growth from sequential cortical reconstructions. Using anatomically constrained multimodal surface matching (aMSM), we obtain accurate, physically guided point correspondence between younger and older cortical reconstructions of the same individual. From each pair of surfaces, we calculate continuous, smooth maps of cortical expansion with unprecedented precision. By considering 30 preterm infants scanned two to four times during the period of rapid cortical expansion (28-38 wk postmenstrual age), we observe significant regional differences in growth across the cortical surface that are consistent with the emergence of new folds. Furthermore, these growth patterns shift over the course of development, with noninjured subjects following a highly consistent trajectory. This information provides a detailed picture of dynamic changes in cortical growth, connecting what is known about patterns of development at the microscopic (cellular) and macroscopic (folding) scales. Since our method provides specific growth maps for individual brains, we are also able to detect alterations due to injury. This fully automated surface analysis, based on tools freely available to the brain-mapping community, may also serve as a useful approach for future studies of abnormal growth due to genetic disorders, injury, or other environmental variables.
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Affiliation(s)
- Kara E Garcia
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130;
| | - Emma C Robinson
- Department of Computer Science, Imperial College London, London SW7 2AZ, United Kingdom
- Department of Biomedical Engineering, Division of Imaging Sciences, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
- Department of Perinatal Imaging and Health, Division of Imaging Sciences, St. Thomas' Hospital, King's College London, London SE1 7EH, United Kingdom
| | - Dimitrios Alexopoulos
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
| | - Donna L Dierker
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Matthew F Glasser
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
- Internal Medicine, St. Luke's Hospital, St. Louis, MO 63017
| | - Timothy S Coalson
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Cynthia M Ortinau
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
| | - Daniel Rueckert
- Department of Computer Science, Imperial College London, London SW7 2AZ, United Kingdom
| | - Larry A Taber
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110
| | - Cynthia E Rogers
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110
| | - Christopher D Smyser
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110
| | - Philip V Bayly
- Department of Mechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO 63130
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