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Vernon LE. Fetal Consultation, Delivery Planning, and Perinatal Transition for Congenital Neurologic Disorders. Clin Perinatol 2025; 52:199-213. [PMID: 40350208 DOI: 10.1016/j.clp.2025.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2025]
Abstract
Anomalies of the central nervous system (CNS) are a frequent referral indication for perinatal evaluation and management through fetal neurology consultation. This multidisciplinary field is evolving quickly to provide adequate care throughout the perinatal continuum. In this article, we will highlight current practice standards in fetal neurology as well as unique challenges, important considerations for fetal and postnatal care of infants with congenital neurologic conditions, and future outlooks for improving the care of patients and families impacted by CNS anomalies.
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Affiliation(s)
- Laura E Vernon
- Division of Pediatric Neurology, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University, 225 East Chicago Avenue, Box 51, Chicago, IL 60611, USA.
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2
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Lerman-Sagie T, Hart AR. The fetal neurologist: Strategies to improve training, practice, and clinical care. Dev Med Child Neurol 2025. [PMID: 40101002 DOI: 10.1111/dmcn.16301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2024] [Revised: 01/31/2025] [Accepted: 02/11/2025] [Indexed: 03/20/2025]
Abstract
Fetal neurology addresses counselling parents on the clinical significance of brain anomalies encountered in their fetus, including disruptive lesions (i.e. stroke, periventricular haemorrhagic infarction, and infection), and genetically based cortical (i.e. hemimegalencephaly, lissencephaly, cobblestone malformation, polymicrogyria, heterotopia) or posterior fossa anomalies (i.e. cerebellar agenesis and hypoplasia, rhombencephalosynapsis, Dandy-Walker syndrome, mega cisterna magna, Blake's pouch cyst). Unlike paediatric neurologists, fetal neurologists cannot examine the infant directly so they diagnose and prognosticate using imaging and other diagnostic studies. The integration of fetal neurologists into fetal multidisciplinary teams is essential for providing expert counselling and cohesive care. This review emphasizes the need for specialized training, multidisciplinary collaboration, and the development of comprehensive service designs to ensure consistent and effective care for families. Additionally, it emphasizes the critical role of fetal neurologists in identifying brain anomalies early and providing thorough counselling to parents, helping them to understand the prognosis, potential interventions, and long-term outcomes for their unborn child.
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Affiliation(s)
- Tally Lerman-Sagie
- Multidisciplinary Fetal Neurology Center, Fetal Brain Research Center, Obstetrics-Gynecology Ultrasound Unit and Pediatric Neurology Unit, Wolfson Medical Center, Holon, Israel
- Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Anthony R Hart
- Department of Paediatric and Perinatal Neurology, King's College Hospital NHS Foundation Trust, London, UK
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Dunbar M, Agarwal S, Venkatesan C, Vollmer B, Scelsa B, Pardo AC, Tarui T, Hart AR, Mulkey SB, Lemmon ME, Gano D. Fetal intracerebral hemorrhage: review of the literature and practice considerations. Pediatr Res 2025:10.1038/s41390-025-04000-5. [PMID: 40097829 DOI: 10.1038/s41390-025-04000-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2024] [Revised: 02/20/2025] [Accepted: 02/25/2025] [Indexed: 03/19/2025]
Abstract
Fetal intracerebral hemorrhage is increasingly recognized on prenatal imaging. In this review, we discuss clinically relevant aspects of fetal intracerebral hemorrhage, including germinal matrix-intraventricular hemorrhage, as well as intraparenchymal hemorrhage. We discuss current clinical practice for prenatal counseling and postnatal management of fetal intracerebral hemorrhage, and offer practical recommendations for clinicians. We propose standardized terminology for classification of fetal intracerebral hemorrhage to be used in future research. We also highlight gaps in the literature and priorities for future research, namely the need for prospective large-scale studies to better understand underlying etiologies and neurodevelopmental outcomes in fetal intracerebral hemorrhage. IMPACT STATEMENT: We discuss the diverse etiologies and outcomes of fetal intracerebral hemorrhage, and propose standardized terminology for classification. We outline current practice and offer practical recommendations for management and counseling of fetal intracerebral hemorrhage, recognizing the need for capacity-building in the newly emerging subspecialty of fetal neurology. We highlight gaps in the literature and research priorities in fetal intracerebral hemorrhage to promote collaborative research, and the development of interventions to improve pregnancy and child outcomes.
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Affiliation(s)
- Mary Dunbar
- Department of Pediatrics, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Sonika Agarwal
- Division of Neurology & Pediatrics, Children's Hospital of Philadelphia; Division of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Charu Venkatesan
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Brigitte Vollmer
- Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton; Paediatric and Neonatal Neurology, Southampton Children's Hospital, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Barbara Scelsa
- Department of Pediatric Neurology, Buzzi Children's Hospital, University of Milan, Milan, Italy
| | - Andrea C Pardo
- Department of Pediatrics, Division of Neurology, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tomo Tarui
- Division of Pediatric Neurology, Hasbro Children's Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Anthony R Hart
- Department of Paediatric Neurology, King's College Hospital NHS Foundation Trust, London, UK
| | - Sarah B Mulkey
- Departments of Neurology and Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, DC, USA
- Zickler Family Prenatal Pediatrics Institute, Children's National Hospital, Washington, DC, USA
| | - Monica E Lemmon
- Department of Pediatrics and Population Health Sciences, Duke University School of Medicine, Durham, NC, England
| | - Dawn Gano
- Department of Neurology and Pediatrics, University of California San Francisco, San Francisco, CA, USA.
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Abadia-Cuchi N, Felici F, Frassanito P, Arulkumaran S, Familiari A, Thilaganathan B. Postnatal outcome of fetal cortical malformations: systematic review. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2024; 64:581-588. [PMID: 39323411 DOI: 10.1002/uog.29105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 08/06/2024] [Accepted: 08/12/2024] [Indexed: 09/27/2024]
Abstract
OBJECTIVE Parental counseling for fetal malformations of cortical development (MCD) is based on data from studies in children and adults undergoing imaging investigation for abnormal neurodevelopment. However, such postnatal findings may not be applicable to prenatally diagnosed cases. The aim of this study was to review the existing data on postnatal neurodevelopmental outcome for fetuses diagnosed with MCD. METHODS A literature search was conducted in PubMed, Web of Science and EMBASE for articles published between 2013 and 2023, using standardized keywords to describe fetal cortical malformations. Full-text articles were accessed for the retrieved citations and data on participant characteristics, imaging findings, and pregnancy and neonatal outcomes were extracted. Fetal MCD was defined as either complex or isolated, according to the presence or absence, respectively, of additional brain or extracranial defects. RESULTS Overall, 30 articles including 371 cases of fetal MCD were reviewed. The cases were classified as complex (n = 324), isolated (n = 21) or unknown (n = 26). There were 144 terminations and four stillbirths, with pregnancy outcome unreported in 149 cases. A total of 108 cases had postnatal magnetic resonance imaging or postmortem examination data available. In nine of these cases, a diagnosis of complex fetal MCD was changed to isolated MCD after birth, and one case was found not to have MCD. There were 74 live births, for which postnatal neurodevelopment data were available in only 30 cases. Normal neurodevelopmental outcome was reported in seven (23.3% (95% CI, 9.9-42.2%)) infants, with the remaining 23 exhibiting various levels of neurodevelopmental delay (three mild, seven moderate and 13 severe) from 6 months to 7 years of age. CONCLUSIONS Most reviewed cases of fetal MCD were complex in nature and underwent termination of pregnancy. There is a paucity of data on postnatal neurological development in fetuses diagnosed with MCD. The available data suggest antenatal overdiagnosis of case severity in about 5% of cases with known outcome, and either normal neurodevelopment or mild neurodevelopmental delay in approximately one-third of liveborn cases with neurological follow-up. © 2024 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- N Abadia-Cuchi
- Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, University of London, London, UK
- Facultad de Medicina de la Universidad de Zaragoza, Zaragoza, Spain
| | - F Felici
- Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, University of London, London, UK
- Department Of Obstetrics and Gynaecology, Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - P Frassanito
- Department Of Obstetrics and Gynaecology, Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - S Arulkumaran
- Department of Neuroradiology, Atkinson Morley Regional Neurosciences Centre, St George's University Hospitals NHS Foundation Trust, London, UK
| | - A Familiari
- Department Of Obstetrics and Gynaecology, Università Cattolica del Sacro Cuore, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - B Thilaganathan
- Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust, University of London, London, UK
- Vascular Biology Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK
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Agarwal S, Venkatesan C, Vollmer B, Scelsa B, Lemmon ME, Pardo AC, Mulkey SB, Tarui T, Dadhwal V, Scher M, Hart AR, Gano D. Fetal Cerebral Ventriculomegaly: A Narrative Review and Practical Recommendations for Pediatric Neurologists. Pediatr Neurol 2024; 156:119-127. [PMID: 38761643 DOI: 10.1016/j.pediatrneurol.2024.04.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 04/19/2024] [Indexed: 05/20/2024]
Abstract
Fetal cerebral ventriculomegaly is one of the most common fetal neurological disorders identified prenatally by neuroimaging. The challenges in the evolving landscape of conditions like fetal cerebral ventriculomegaly involve accurate diagnosis and how best to provide prenatal counseling regarding prognosis as well as postnatal management and care of the infant. The purpose of this narrative review is to discuss the literature on fetal ventriculomegaly, including postnatal management and neurodevelopmental outcome, and to provide practice recommendations for pediatric neurologists.
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Affiliation(s)
- Sonika Agarwal
- Division of Neurology & Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Division of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Charu Venkatesan
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Brigitte Vollmer
- Faculty of Medicine, Clinical Neurosciences, Clinical and Experimental Sciences, University of Southampton, Southampton, UK; Paediatric and Neonatal Neurology, Southampton Children's Hospital, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Barbara Scelsa
- Department of Pediatric Neurology, Buzzi Children's Hospital, University of Milan, Milan, Italy
| | - Monica E Lemmon
- Department of Pediatrics and Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
| | - Andrea C Pardo
- Division of Neurology, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Sarah B Mulkey
- Zickler Family Prenatal Pediatrics Institute, Children's National Hospital, Washington, District of Columbia; Departments of Neurology, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia; Division of Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia
| | - Tomo Tarui
- Division of Pediatric Neurology, Hasbro Children's Hospital, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Vatsla Dadhwal
- Professor, Maternal Fetal Medicine, Department of Obstetrics & Gynecology, All India Institute of Medical Sciences, New Delhi, India
| | - Mark Scher
- Emeritus Full Professor Pediatrics and Neurology, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Anthony R Hart
- Department of Paediatric Neurology, King's College Hospital NHS Foundation Trust, London, UK
| | - Dawn Gano
- Department of Neurology & Pediatrics, University of California San Francisco, San Francisco, California
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6
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Tarui T, Gimovsky AC, Madan N. Fetal neuroimaging applications for diagnosis and counseling of brain anomalies: Current practice and future diagnostic strategies. Semin Fetal Neonatal Med 2024; 29:101525. [PMID: 38632010 PMCID: PMC11156536 DOI: 10.1016/j.siny.2024.101525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Advances in fetal brain neuroimaging, especially fetal neurosonography and brain magnetic resonance imaging (MRI), allow safe and accurate anatomical assessments of fetal brain structures that serve as a foundation for prenatal diagnosis and counseling regarding fetal brain anomalies. Fetal neurosonography strategically assesses fetal brain anomalies suspected by screening ultrasound. Fetal brain MRI has unique technological features that overcome the anatomical limits of smaller fetal brain size and the unpredictable variable of intrauterine motion artifact. Recent studies of fetal brain MRI provide evidence of improved diagnostic and prognostic accuracy, beginning with prenatal diagnosis. Despite technological advances over the last several decades, the combined use of different qualitative structural biomarkers has limitations in providing an accurate prognosis. Quantitative analyses of fetal brain MRIs offer measurable imaging biomarkers that will more accurately associate with clinical outcomes. First-trimester ultrasound opens new opportunities for risk assessment and fetal brain anomaly diagnosis at the earliest time in pregnancy. This review includes a case vignette to illustrate how fetal brain MRI results interpreted by the fetal neurologist can improve diagnostic perspectives. The strength and limitations of conventional ultrasound and fetal brain MRI will be compared with recent research advances in quantitative methods to better correlate fetal neuroimaging biomarkers of neuropathology to predict functional childhood deficits. Discussion of these fetal sonogram and brain MRI advances will highlight the need for further interdisciplinary collaboration using complementary skills to continue improving clinical decision-making following precision medicine principles.
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Affiliation(s)
- Tomo Tarui
- Pediatric Neurology, Pediatrics, Hasbro Children's Hospital, The Warren Alpert Medical School of Brown University, Providence, RI, USA.
| | - Alexis C Gimovsky
- Maternal Fetal Medicine, Obstetrics and Gynecology, Women & Infants Hospital of Rhode Island, The Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Neel Madan
- Neuroradiology, Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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7
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Aviles Verdera J, Story L, Hall M, Finck T, Egloff A, Seed PT, Malik SJ, Rutherford MA, Hajnal JV, Tomi-Tricot R, Hutter J. Reliability and Feasibility of Low-Field-Strength Fetal MRI at 0.55 T during Pregnancy. Radiology 2023; 309:e223050. [PMID: 37847139 PMCID: PMC10623193 DOI: 10.1148/radiol.223050] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 08/20/2023] [Accepted: 09/06/2023] [Indexed: 10/18/2023]
Abstract
Background The benefits of using low-field-strength fetal MRI to evaluate antenatal development include reduced image artifacts, increased comfort, larger bore size, and potentially reduced costs, but studies about fetal low-field-strength MRI are lacking. Purpose To evaluate the reliability and feasibility of low-field-strength fetal MRI to assess anatomic and functional measures in pregnant participants using a commercially available 0.55-T MRI scanner and a comprehensive 20-minute protocol. Materials and Methods This prospective study was performed at a large teaching hospital (St Thomas' Hospital; London, England) from May to November 2022 in healthy pregnant participants and participants with pregnancy-related abnormalities using a commercially available 0.55-T MRI scanner. A 20-minute protocol was acquired including anatomic T2-weighted fast-spin-echo, quantitative T2*, and diffusion sequences. Key measures like biparietal diameter, transcerebellar diameter, lung volume, and cervical length were evaluated by two radiologists and an MRI-experienced obstetrician. Functional organ-specific mean values were given. Comparison was performed with existing published values and higher-field MRI using linear regression, interobserver correlation, and Bland-Altman plots. Results A total of 79 fetal MRI examinations were performed (mean gestational age, 29.4 weeks ± 5.5 [SD] [age range, 17.6-39.3 weeks]; maternal age, 34.4 years ± 5.3 [age range, 18.4-45.5 years]) in 47 healthy pregnant participants (control participants) and in 32 participants with pregnancy-related abnormalities. The key anatomic two-dimensional measures for the 47 healthy participants agreed with large cross-sectional 1.5-T and 3-T control studies. The interobserver correlations for the biparietal diameter in the first 40 consecutive scans were 0.96 (95% CI: 0.7, 0.99; P = .002) for abnormalities and 0.93 (95% CI: 0.86, 0.97; P < .001) for control participants. Functional features, including placental and brain T2* and placental apparent diffusion coefficient values, strongly correlated with gestational age (mean placental T2* in the control participants: 5.2 msec of decay per week; R2 = 0.66; mean T2* at 30 weeks, 176.6 msec; P < .001). Conclusion The 20-minute low-field-strength fetal MRI examination protocol was capable of producing reliable structural and functional measures of the fetus and placenta in pregnancy. Clinical trial registration no. REC 21/LO/0742 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Gowland in this issue.
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Affiliation(s)
- Jordina Aviles Verdera
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Lisa Story
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Megan Hall
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Tom Finck
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Alexia Egloff
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Paul T. Seed
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Shaihan J. Malik
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Mary A. Rutherford
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Joseph V. Hajnal
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Raphaël Tomi-Tricot
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
| | - Jana Hutter
- From the Centre for the Developing Brain, School of Biomedical
Engineering & Imaging Sciences, King's College London, 1st Floor
South Wing, St Thomas’ Hospital, Westminster Bridge Road SE1 7EH London,
United Kingdom (J.A.V., L.S., M.H., P.T.S., S.J.M., M.A.R., J.V.H, J.H.); Centre
for Medical Biomedical Engineering Department, School of Biomedical Engineering
and Imaging Sciences, King's College London, London, UK (J.A.V., L.S.,
A.E., S.J.M., M.A.R., J.V.H., J.H.); Women's Health, GSTT, London, UK
(L.S., M.H., T.F., P.T.S.); Technical University Munich, Munich, Germany (T.F.);
MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK (R.T.T.);
and Radiological Institute, University Hospital Erlangen, Erlangen, Germany
(J.H.)
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8
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Tarui T, Venkatesan C, Gano D, Lemmon ME, Mulkey SB, Pardo AC, Emrick L, Scher M, Agarwal S. Fetal Neurology Practice Survey: Current Practice and the Future Directions. Pediatr Neurol 2023; 145:74-79. [PMID: 37290231 DOI: 10.1016/j.pediatrneurol.2023.04.016] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/17/2023] [Accepted: 04/20/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND Fetal neurology is a rapidly evolving field. Consultations aim to diagnose, prognosticate, and coordinate prenatal and perinatal management along with other specialists and counsel expectant parents. Practice parameters and guidelines are limited. METHODS A 48-question online survey was administered to child neurologists. Questions targeted current care practices and perceived priorities for the field. RESULTS Representatives from 43 institutions in the United States responded; 83% had prenatal diagnosis centers, and the majority performed on-site neuroimaging. The earliest gestational age for fetal magnetic resonance imaging was variable. Annual consultations ranged from <20 to >100 patients. Fewer than half (n = 17.40%) were subspecialty trained. Most respondents (n = 39.91%) were interested in participating in a collaborative registry and educational initiatives. CONCLUSIONS The survey highlights heterogeneity in clinical practice. Large multisite and multidisciplinary collaborations are essential to gather data that inform outcomes for fetuses evaluated across institutions through registries as well as creation of guidelines and educational material.
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Affiliation(s)
- Tomo Tarui
- Division of Pediatric Neurology, Hasbro Children's Hospital, Warren Alpert Medical School of Brown University, Providence, Rhode Island
| | - Charu Venkatesan
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Dawn Gano
- Department of Neurology & Pediatrics, University of California San Francisco, San Francisco, California
| | - Monica E Lemmon
- Department of Pediatrics and Population Health Sciences, Duke University School of Medicine
| | - Sarah B Mulkey
- Prenatal Pediatrics Institute, Children's National Hospital, Washington, District of Columbia; Departments of Neurology and Pediatrics, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia
| | - Andrea C Pardo
- Division of Neurology, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, Chicago Illinois
| | - Lisa Emrick
- Department of Pediatrics, Neurology and Developmental Neuroscience, Baylor College of Medicine, Texas Children's Hospital, Houston, Texas
| | - Mark Scher
- Emeritus Full Professor Pediatrics and Neurology, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Sonika Agarwal
- Division of Neurology & Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Division of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
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9
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Payette K, Li HB, de Dumast P, Licandro R, Ji H, Siddiquee MMR, Xu D, Myronenko A, Liu H, Pei Y, Wang L, Peng Y, Xie J, Zhang H, Dong G, Fu H, Wang G, Rieu Z, Kim D, Kim HG, Karimi D, Gholipour A, Torres HR, Oliveira B, Vilaça JL, Lin Y, Avisdris N, Ben-Zvi O, Bashat DB, Fidon L, Aertsen M, Vercauteren T, Sobotka D, Langs G, Alenyà M, Villanueva MI, Camara O, Fadida BS, Joskowicz L, Weibin L, Yi L, Xuesong L, Mazher M, Qayyum A, Puig D, Kebiri H, Zhang Z, Xu X, Wu D, Liao K, Wu Y, Chen J, Xu Y, Zhao L, Vasung L, Menze B, Cuadra MB, Jakab A. Fetal brain tissue annotation and segmentation challenge results. Med Image Anal 2023; 88:102833. [PMID: 37267773 DOI: 10.1016/j.media.2023.102833] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 03/16/2023] [Accepted: 04/20/2023] [Indexed: 06/04/2023]
Abstract
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, gray matter, white matter, ventricles, cerebellum, brainstem, deep gray matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.
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Affiliation(s)
- Kelly Payette
- Center for MR Research, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland.
| | - Hongwei Bran Li
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland; Department of Informatics, Technical University of Munich, Munich, Germany
| | - Priscille de Dumast
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; CIBM, Center for Biomedical Imaging, Lausanne, Switzerland
| | - Roxane Licandro
- Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, United States; Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab (CIR), Medical University of Vienna, Vienna, Austria
| | - Hui Ji
- Center for MR Research, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland
| | | | | | | | - Hao Liu
- Shanghai Jiaotong University, China
| | | | | | - Ying Peng
- School of Computer Science, Shaanxi Normal University, Xi'an 710119, China
| | - Juanying Xie
- School of Computer Science, Shaanxi Normal University, Xi'an 710119, China
| | - Huiquan Zhang
- School of Computer Science, Shaanxi Normal University, Xi'an 710119, China
| | - Guiming Dong
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Hao Fu
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - Guotai Wang
- School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu, China
| | - ZunHyan Rieu
- Research Institute, NEUROPHET Inc., Seoul 06247, South Korea
| | - Donghyeon Kim
- Research Institute, NEUROPHET Inc., Seoul 06247, South Korea
| | - Hyun Gi Kim
- Department of Radiology, The Catholic University of Korea, Eunpyeong St. Mary's Hospital, Seoul 06247, South Korea
| | - Davood Karimi
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Ali Gholipour
- Boston Children's Hospital and Harvard Medical School, Boston, MA, United States
| | - Helena R Torres
- Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's - PT Government Associate Laboratory, Braga Guimarães, Portugal
| | - Bruno Oliveira
- Algoritmi Center, School of Engineering, University of Minho, Guimarães, Portugal; Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal; ICVS/3B's - PT Government Associate Laboratory, Braga Guimarães, Portugal
| | - João L Vilaça
- 2Ai - School of Technology, IPCA, Barcelos, Portugal
| | - Yang Lin
- Department of Computer Science, Hong Kong University of Science and Technology, China
| | - Netanell Avisdris
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel; Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Israel
| | - Ori Ben-Zvi
- Sagol Brain Institute, Tel Aviv Sourasky Medical Center, Israel; Sagol School of Neuroscience, Tel Aviv University, Israel
| | - Dafna Ben Bashat
- Sagol School of Neuroscience, Tel Aviv University, Israel; Sackler Faculty of Medicine, Tel Aviv University, Israel
| | - Lucas Fidon
- School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, United Kingdom
| | - Michael Aertsen
- Department of Radiology, University Hospitals Leuven, Leuven 3000, Belgium
| | - Tom Vercauteren
- School of Biomedical Engineering & Imaging Sciences, King's College London, London SE1 7EU, United Kingdom
| | - Daniel Sobotka
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Computational Imaging Research Lab, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Mireia Alenyà
- BCN-MedTech, Department of Information and Communications Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Maria Inmaculada Villanueva
- Department of Information and Communications Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona, Spain
| | - Oscar Camara
- BCN-MedTech, Department of Information and Communications Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Bella Specktor Fadida
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel
| | - Leo Joskowicz
- School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel
| | - Liao Weibin
- School of Computer Science, Beijing Institute of Technology, China
| | - Lv Yi
- School of Computer Science, Beijing Institute of Technology, China
| | - Li Xuesong
- School of Computer Science, Beijing Institute of Technology, China
| | - Moona Mazher
- Department of Computer Engineering and Mathematics, University Rovira i Virgili,Spain
| | | | - Domenec Puig
- Department of Computer Engineering and Mathematics, University Rovira i Virgili,Spain
| | - Hamza Kebiri
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; CIBM, Center for Biomedical Imaging, Lausanne, Switzerland
| | - Zelin Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou, China
| | - Xinyi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou, China
| | | | - Yixuan Wu
- Zhejiang University, Hangzhou, China
| | | | - Yunzhi Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou, China
| | - Li Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Yuquan Campus, Hangzhou, China
| | - Lana Vasung
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, United States; Department of Pediatrics, Harvard Medical School, United States
| | - Bjoern Menze
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Meritxell Bach Cuadra
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; CIBM, Center for Biomedical Imaging, Lausanne, Switzerland
| | - Andras Jakab
- Center for MR Research, University Children's Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich, Zurich, Switzerland; University Research Priority Project Adaptive Brain Circuits in Development and Learning (AdaBD), University of Zürich, Zurich, Switzerland
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10
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Agarwal S, Tarui T, Patel V, Turner A, Nagaraj U, Venkatesan C. Prenatal Neurological Diagnosis: Challenges in Neuroimaging, Prognostic Counseling, and Prediction of Neurodevelopmental Outcomes. Pediatr Neurol 2023; 142:60-67. [PMID: 36934462 DOI: 10.1016/j.pediatrneurol.2023.02.013] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 01/18/2023] [Accepted: 02/20/2023] [Indexed: 02/26/2023]
Abstract
Prenatal diagnosis of fetal brain abnormalities is rapidly evolving with the advancement of neuroimaging techniques, thus adding value to prognostic counseling and perinatal management. However, challenges and uncertainties persist in prenatal counseling due to limitations of prenatal imaging, continued development and maturation of the brain structure, and the heterogeneity and paucity of outcome studies. This topical review of fetal neurological consultations highlights prenatally diagnosed brain abnormalities that challenged prognostic counseling and perinatal management. Representative cases across multiple centers that highlighted diagnostic challenges were selected. Charts were reviewed for neuroimaging, genetic evaluation, prenatal prognostic discussion, postnatal imaging and testing, and infant outcome. We present case studies with prenatal and postnatal information discussing prenatal testing, fetal MRI interpretation, and complexities in the prognostic counseling process. Advocating for large-scale multicenter studies and a national collaborative fetal neurological registry to help guide the ever-expanding world of prenatal diagnostics and prognostic counseling is critical to this field. Study of large-scale outcomes data from such a registry can better guide fetal neurological consultations and facilitate comprehensive multidisciplinary planning and program development for educational curriculum for fetal-neonatal neurology.
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Affiliation(s)
- Sonika Agarwal
- Division of Neurology & Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Division of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Tomo Tarui
- Division of Pediatric Neurology, Department of Pediatrics, Tufts Medical Center, Boston, Massachusetts; Department of Pediatrics, Tufts University School of Medicine, Boston, Massachusetts
| | - Virali Patel
- Division of Neurology & Pediatrics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Abigail Turner
- Department of Neurology, Children's National Medical Center, Washington, District of Columbia
| | - Usha Nagaraj
- Department of Radiology and Medical Imaging, Cincinnati Children's Hospital, Cincinnati, Ohio; Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Charu Venkatesan
- Division of Neurology, Cincinnati Children's Hospital, Cincinnati, Ohio; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
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11
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Cuérel A, Favre G, Vouga M, Pomar L. Monkeypox and Pregnancy: Latest Updates. Viruses 2022; 14:2520. [PMID: 36423129 PMCID: PMC9693336 DOI: 10.3390/v14112520] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 11/07/2022] [Accepted: 11/10/2022] [Indexed: 11/16/2022] Open
Abstract
Monkeypox virus (MPXV) has emerged as a threatening zoonosis. Its spread around the world has been growing fast over the last 2 years, particularly in 2022. The reasons for this sudden spread are probably multifactorial. The R0 values of the two MPXV clades are rather low, and a massive pandemic is considered unlikely, although the increase in the number of single-nucleotide polymorphisms found in the 2022 MPXV strain could indicate an accelerated human adaptation. Very little is known about the risks of an infection during pregnancy for both the mother and the fetus. Further observations must be made to create clear, adapted, evidence-based guidelines. This article summarizes the current knowledge about MPXV infections and similar pregnancy virus infections.
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Affiliation(s)
- Alexandre Cuérel
- Department Woman-Mother-Child, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Guillaume Favre
- Department Woman-Mother-Child, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Manon Vouga
- Department Woman-Mother-Child, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
| | - Léo Pomar
- Department Woman-Mother-Child, Lausanne University Hospital and University of Lausanne, 1011 Lausanne, Switzerland
- School of Health Sciences (HESAV), HES-SO University of Applied Sciences and Arts Western Switzerland, 1011 Lausanne, Switzerland
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12
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Verma D, Agrawal S, Iwendi C, Sharma B, Bhatia S, Basheer S. A Novel Framework for Abnormal Risk Classification over Fetal Nuchal Translucency Using Adaptive Stochastic Gradient Descent Algorithm. Diagnostics (Basel) 2022; 12:2643. [PMID: 36359487 PMCID: PMC9689292 DOI: 10.3390/diagnostics12112643] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/14/2022] [Accepted: 09/22/2022] [Indexed: 11/25/2023] Open
Abstract
In most maternity hospitals, an ultrasound scan in the mid-trimester is now a standard element of antenatal care. More fetal abnormalities are being detected in scans as technology advances and ability improves. Fetal anomalies are developmental abnormalities in a fetus that arise during pregnancy, birth defects and congenital abnormalities are related terms. Fetal abnormalities have been commonly observed in industrialized countries over the previous few decades. Three out of every 1000 pregnant mothers suffer a fetal anomaly. This research work proposes an Adaptive Stochastic Gradient Descent Algorithm to evaluate the risk of fetal abnormality. Findings of this work suggest that proposed innovative method can successfully classify the anomalies linked with nuchal translucency thickening. Parameters such an accuracy, recall, precision, and F1-score are analyzed. The accuracy achieved through the suggested technique is 98.642.%.
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Affiliation(s)
- Deepti Verma
- Department of Computer Application, SAGE University, Indore 452020, India
| | - Shweta Agrawal
- Institute of Advance Computing, SAGE University, Indore 452020, India
| | - Celestine Iwendi
- School of Creative Technologies, University of Bolton, Bolton BL3 5AB, UK
| | - Bhisham Sharma
- Department of Computer Science & Engineering, School of Engineering and Technology, Chitkara University, Baddi 174103, India
| | - Surbhi Bhatia
- Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al Ahsa 36362, Saudi Arabia
| | - Shakila Basheer
- Department of Information Systems, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, P.O. BOX 84428, Riyadh 11671, Saudi Arabia
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13
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Powers AM, White C, Neuberger I, Maloney JA, Stence NV, Mirsky D. Fetal MRI Neuroradiology: Indications. Clin Perinatol 2022; 49:573-586. [PMID: 36113923 DOI: 10.1016/j.clp.2022.05.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Fetal MRI is a safe, noninvasive examination of the fetus and placenta, a complement to ultrasonography. MRI provides detailed CNS evaluation, including depicting parenchymal architecture and posterior fossa morphology, and is key in prenatal assessment of spinal dysraphism, neck masses, and ventriculomegaly. Fetal MRI is typically performed after 22 weeks gestation, and ultrafast T1 and T2-weighted MRI sequences are the core of the exam, with advanced sequences such as diffusion weighted imaging used for specific questions. The fetal brain grows and develops rapidly, and familiarity with gestational age specific norms is essential to MRI interpretation.
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Affiliation(s)
- Andria M Powers
- Children's Hospital and Medical Center, University of Nebraska Medical Center, 8200 Dodge Street, Omaha, NE 68114, USA.
| | - Christina White
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - Ilana Neuberger
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - John A Maloney
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - Nicholas V Stence
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
| | - David Mirsky
- Department of Radiology, Children's Hospital Colorado, University of Colorado, 13123 E. 16th Avenue, Box 125, Aurora, CO, 80045, USA
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14
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Griffiths PD, Jarvis D, Connolly DJ, Mooney C, Embleton N, Hart AR. Predicting neurodevelopmental outcomes in fetuses with isolated mild ventriculomegaly. Arch Dis Child Fetal Neonatal Ed 2022; 107:431-436. [PMID: 34844985 DOI: 10.1136/archdischild-2021-321984] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 10/16/2021] [Indexed: 11/04/2022]
Abstract
BACKGROUND Fetal ventriculomegaly is the the most common intracranial abnormality detected antenatally. When ventriculomegaly is mild and the only, isolated, abnormality detected (isolated mild ventriculomegaly (IMVM)) the prognosis is generally considered to be good. We aim to determine if there are features on in utero MRI (iuMRI) that can identify fetuses with IMVM who have lower risks of abnormal neurodevelopment outcome. METHODS We studied cases recruited into the MRI to enhance the diagnosis of fetal developmental brain abnormalities in utero (MERIDIAN) study, specifically those with: confirmed IMVM, 3D volume imaging of the fetal brain and neurodevelopmental outcomes at 3 years. We explored the influence of sex of the fetus, laterality of the ventriculomegaly and intracranial compartmental volumes in relation to neurodevelopmental outcome. FINDINGS Forty-two fetuses met the criteria (33 male and 9 female). There was no obvious correlation between fetal sex and the risk of poor neurodevelopmental outcome. Unilateral IMVM was present in 23 fetuses and bilateral IMVM in 19 fetuses. All fetuses with unilateral IMVM had normal neurodevelopmental outcomes, while only 12/19 with bilateral IMVM had normal neurodevelopmental outcomes. There was no obvious correlation between measure of intracranial volumes and risk of abnormal developmental outcomes. INTERPRETATION The most important finding is the very high chance of a good neurodevelopmental outcome observed in fetuses with unilateral IMVM, which is a potentially important finding for antenatal counselling. There does not appear to be a link between the volume of the ventricular system or brain volume and the risk of poor neurodevelopmental outcome.
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Affiliation(s)
| | - Deborah Jarvis
- Academic Unit of Radiology, The University of Sheffield, Sheffield, UK
| | - Daniel J Connolly
- Neuroradiology, Sheffield Childrens Hospital NHS Foundation Trust, Sheffield, UK
| | - Cara Mooney
- Clinical Trials Research Unit, School of Health and Related Research, The University of Sheffield, Sheffield, UK
| | - Nicholas Embleton
- Newcastle Neonatal Service, Ward 35 Neonatal Unit, Royal Victoria Infirmary, Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne, UK
| | - Anthony Richard Hart
- Department of Paediatric and Perinatal Neurology, Sheffield Children's NHS Foundation Trust, Sheffield, UK
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15
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Moradi B, Parooie F, Kazemi MA, Hashemi H, Miratashi Yazdi SN. Fetal brain imaging: A comparison between fetal ultrasonography and intra uterine magnetic resonance imaging (a systematic review and meta-analysis). JOURNAL OF CLINICAL ULTRASOUND : JCU 2022; 50:491-499. [PMID: 35266167 DOI: 10.1002/jcu.23158] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 02/05/2022] [Accepted: 02/10/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVE The aim of this study was to compare ultrasound (US) and intra uterine MRI (IUMRI) of the brain in the diagnosis of fetal brain abnormalities. METHODS The present systematic review is done based on guidelines for preferred reporting items for systematic reviews and meta-analysis. All major articles comparing fetal US with IUMRI in fetuses with suspected brain abnormalities were qualified. Articles published before 2010 were excluded from the study. An I2 > 20% was considered as a sign of significant change. The statistical analysis was done using STATA -15 and Meta-Disk 1.4 applications. RESULTS Five articles were considered for meta-analysis. The sensitivity of US and IUMRI in diagnosing fetal abnormalities were 86% and 95%, respectively. The corresponding rates for specificity were 77% and 80%. IUMRI and US were concordant in 72.5% (95% CI: 68%-77%) of diagnoses. However, IUMRI added information in 21.7% of cases, while US added value was only 1.48. CONCLUSION Our results approved the good diagnostic performance of both US and IUMRI in confirming fetal brain normal development and emphasized that US is an appropriate screening technique in pregnancy. In cases of detected abnormalities in US, IUMRI is suggested as it was the most accurate imaging method and added information about the diagnosis in 22.2% of cases.
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Affiliation(s)
- Behnaz Moradi
- Department of Radiology, Women's Yas Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Department of Radiology, Medical Imaging Center, Imam Khomeini Hospital Complex(IKHC), Tehran University of Medical Sciences, Tehran, Iran
| | - Fateme Parooie
- Pediatric Gastroenterology and Hepatology Research Center, Zabol University of Medical Sciences, Zabol, Iran
| | - Mohammad Ali Kazemi
- Department of Radiology, Women's Yas Hospital, Tehran University of Medical Sciences, Tehran, Iran
- Department of Radiology, Amiralam Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Hassan Hashemi
- Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran
| | - Seyedeh Nooshin Miratashi Yazdi
- Department of Radiology, Medical Imaging Center, Imam Khomeini Hospital Complex(IKHC), Tehran University of Medical Sciences, Tehran, Iran
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16
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Pollatou A, Filippi CA, Aydin E, Vaughn K, Thompson D, Korom M, Dufford AJ, Howell B, Zöllei L, Martino AD, Graham A, Scheinost D, Spann MN. An ode to fetal, infant, and toddler neuroimaging: Chronicling early clinical to research applications with MRI, and an introduction to an academic society connecting the field. Dev Cogn Neurosci 2022; 54:101083. [PMID: 35184026 PMCID: PMC8861425 DOI: 10.1016/j.dcn.2022.101083] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/17/2021] [Accepted: 02/04/2022] [Indexed: 12/14/2022] Open
Abstract
Fetal, infant, and toddler neuroimaging is commonly thought of as a development of modern times (last two decades). Yet, this field mobilized shortly after the discovery and implementation of MRI technology. Here, we provide a review of the parallel advancements in the fields of fetal, infant, and toddler neuroimaging, noting the shifts from clinical to research use, and the ongoing challenges in this fast-growing field. We chronicle the pioneering science of fetal, infant, and toddler neuroimaging, highlighting the early studies that set the stage for modern advances in imaging during this developmental period, and the large-scale multi-site efforts which ultimately led to the explosion of interest in the field today. Lastly, we consider the growing pains of the community and the need for an academic society that bridges expertise in developmental neuroscience, clinical science, as well as computational and biomedical engineering, to ensure special consideration of the vulnerable mother-offspring dyad (especially during pregnancy), data quality, and image processing tools that are created, rather than adapted, for the young brain.
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Affiliation(s)
- Angeliki Pollatou
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA
| | - Courtney A Filippi
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA; Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
| | - Ezra Aydin
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Psychology, University of Cambridge, Cambridge, UK
| | - Kelly Vaughn
- Department of Pediatrics, University of Texas Health Sciences Center, Houston, TX, USA
| | - Deanne Thompson
- Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Marta Korom
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA
| | - Alexander J Dufford
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Brittany Howell
- Fralin Biomedical Research Institute at VTC, Virginia Tech, Roanoke, VA, USA; Department of Human Development and Family Science, Virginia Tech, Blacksburg, VA, USA
| | - Lilla Zöllei
- Laboratory for Computational Neuroimaging, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | | | - Alice Graham
- Department of Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Dustin Scheinost
- Department of Psychological and Brain Sciences, University of Delaware, Newark, DE, USA; Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Yale Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | - Marisa N Spann
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, USA; Department of Pediatrics, Columbia University Irving Medical Center, New York, NY, USA.
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17
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Abstract
Structural brain anomalies are relatively common and may be detected either prenatally or postnatally. Brain malformations can be characterized based on the developmental processes that have been perturbed, either by environmental, infectious, disruptive or genetic causes. Fetuses and neonates with brain malformations should be thoroughly surveilled for potential other anomalies, and depending on the nature of the brain malformation, may require additional investigations such as genetic testing, ophthalmological examinations, cardiorespiratory monitoring, and screening laboratory studies.
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Abstract
Brain asymmetry is a hallmark of the human brain. Recent studies report a certain degree of abnormal asymmetry of brain lateralization between left and right brain hemispheres can be associated with many neuropsychiatric conditions. In this regard, some questions need answers. First, the accelerated brain asymmetry is programmed during the pre-natal period that can be called “accelerated brain decline clock”. Second, can we find the right biomarkers to predict these changes? Moreover, can we establish the dynamics of these changes in order to identify the right time window for proper interventions that can reverse or limit the neurological decline? To find answers to these questions, we performed a systematic online search for the last 10 years in databases using keywords. Conclusion: we need to establish the right in vitro model that meets human conditions as much as possible. New biomarkers are necessary to establish the “good” or the “bad” borders of brain asymmetry at the epigenetic and functional level as early as possible.
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Romaniello R, Arrigoni F, De Salvo P, Bonaglia MC, Panzeri E, Bassi MT, Parazzini C, Righini A, Borgatti R. Long-term follow-up in a cohort of children with isolated corpus callosum agenesis at fetal MRI. Ann Clin Transl Neurol 2021; 8:2280-2288. [PMID: 34850608 PMCID: PMC8670314 DOI: 10.1002/acn3.51484] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 12/02/2022] Open
Abstract
Objective This long‐term retrospective follow‐up study aimed to address the knowledge gap between prenatal diagnosis of complete isolated Agenesis of Corpus Callosum (cACC) at fetal MRI and postnatal neurodevelopmental outcome to improve prenatal counseling for parents. Methods Data on fetuses with isolated cACC from a single‐center MRI database built up in two decades were considered. Detailed postnatal clinical, neuropsychological evaluations were performed and descriptions of available neuroradiological and genetic data were provided. Results Following a detailed neuropsychological evaluation and a long‐term follow‐up, the subsequent results emerged: 38 school‐aged children (older than 6 years) of 50 (aged 2.5‐15 years) showed normal intellectual functions (50%), intellectual disability (21%), and borderline intelligence quotient (29%). Deficits in motor functions (58%), executive functions (37%), language (61%), memory abilities (58%), and academic performances (53%) were found. Twenty‐one percent of participants showed behavioral difficulties. Almost half of the participants underwent rehabilitation. Additional findings (21%) were detected at postnatal brain MRI, and a significant association between additional findings at postnatal imaging and abnormal neurodevelopmental outcome was observed. Interpretations This study supports the view that children with prenatal diagnosis of isolated cACC may present with several degrees of neurologic and neuropsychological impairment which become more evident only in their second decade of life. Postnatal MRI and detailed genetic analysis may add crucial information to prenatal data and substantially influence final judgment on the outcome and orient clinical management and counseling.
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Affiliation(s)
- Romina Romaniello
- Neuropsychiatry and Neurorehabilitation Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Filippo Arrigoni
- Neuroimaging Lab, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Patrizia De Salvo
- Neuropsychiatry and Neurorehabilitation Unit, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Maria Clara Bonaglia
- Cytogenetics Laboratory, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Elena Panzeri
- Laboratory of Molecular Biology, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Maria Teresa Bassi
- Laboratory of Molecular Biology, Scientific Institute, IRCCS Eugenio Medea, Bosisio Parini, Lecco, Italy
| | - Cecilia Parazzini
- Radiology and Neuroradiology Department, Children's Hospital V. Buzzi, Milan, Italy
| | - Andrea Righini
- Radiology and Neuroradiology Department, Children's Hospital V. Buzzi, Milan, Italy
| | - Renato Borgatti
- Child Neurology and Psychiatry Unit, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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20
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De Robertis V, Sen C, Timor-Tritsch I, Chaoui R, Volpe P, Galindo A, Achiron R, Pooh R, Khalil A, Volpe N, D'Antonio F, Birnbaum R. WAPM-World Association of Perinatal Medicine Practice Guidelines: Fetal central nervous system examination. J Perinat Med 2021; 49:1033-1041. [PMID: 34087958 DOI: 10.1515/jpm-2021-0183] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 04/24/2021] [Indexed: 11/15/2022]
Abstract
These practice guidelines follow the mission of the World Association of Perinatal Medicine in collaboration with the Perinatal Medicine Foundation, bringing together groups and individuals throughout the world, with the goal of improving the ultrasound assessment of the fetal Central Nervous System (CNS) anatomy. In fact, this document provides further guidance for healthcare practitioners for the evaluation of the fetal CNS during the mid-trimester ultrasound scan with the aim to increase the ability in evaluating normal fetal anatomy. Therefore, it is not intended to establish a legal standard of care. This document is based on consensus among perinatal experts throughout the world, and serves as a guideline for use in clinical practice.
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Affiliation(s)
| | - Cihat Sen
- Perinatal Medicine Foundation, Istanbul, Turkey
| | - Ilan Timor-Tritsch
- Division of Obstetrical and Gynecological Ultrasound, NYU School of Medicine, New York, NY, USA
| | - Rabih Chaoui
- Center for Prenatal Diagnosis and Human Genetics, Berlin, Germany
| | - Paolo Volpe
- Fetal Medicine Unit, Di Venere and Sarcone Hospitals, ASL BA, Bari, Italy
| | - Alberto Galindo
- Department of Obstetrics and Gynaecology, Fetal Medicine Unit, Maternal and Child Health and Development Network, University Hospital 12 de Octubre, Complutense University of Madrid, Madrid, Spain
| | - Reuven Achiron
- Department of Obstetrics and Gynecology, Fetal Medicine Unit, The Chaim Sheba Medical Center Tel-Hashomer, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Ritsuko Pooh
- Fetal Diagnostic Center, CRIFM Clinical Research Institute of Fetal Medicine, Osaka, Japan
| | - Asma Khalil
- Fetal Medicine Unit, St George University Hospital NHS Foundation Trust, London, UK
| | - Nicola Volpe
- Department of Medicine and Surgery, Unit of Surgical Sciences, Obstetrics and Gynecology, University of Parma, Parma, Italy
| | - Francesco D'Antonio
- Department of Obstetrics and Gynecology, Center for Fetal Care and High-Risk Pregnancy, University of Chieti, Chieti, Italy
| | - Roee Birnbaum
- OB-GYN Ultrasound Unit, Lis Maternity Hospital, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
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21
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Fesslova V, Colli AM, Boito S, Fabietti I, Triulzi F, Persico N. Dural Sinus Arteriovenous Malformation in the Fetus. Case Report and Discussion of the Literature. Diagnostics (Basel) 2021; 11:diagnostics11091651. [PMID: 34573993 PMCID: PMC8464898 DOI: 10.3390/diagnostics11091651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/01/2021] [Accepted: 09/05/2021] [Indexed: 11/16/2022] Open
Abstract
Sonographic findings of cerebral arteriovenous malformations in the fetus are uncommon and usually regard aneurysm of the Galen vein. Outcome of arteriovenous malformations is usually severe. We report a case of a fetus at 21 weeks' gestation with a rarer arteriovenous malformation, referred to us for echocardiography on account of a suspicious cardiomegaly at obstetrical scan. Upon examination, we found cardiomegaly, together with an associated moderate tricuspid regurgitation, however, there were no clear features of tricuspid dysplasia. Considering an unusually dilated superior vena cava, we found via color Doppler imaging a systodiastolic flow at Color Doppler progressing. Subsequent MRI of the central nervous system determined the localization in the sinus dura mater. Due to an already evident hemodynamic impact, the parents opted for the termination of the pregnancy. Autopsy confirmed a voluminous arteriovenous malformation of the transverse sinus of the dura mater, severe cardiomegaly, mainly of the ventricles, and hypoplasia of the lungs.
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Affiliation(s)
- Vlasta Fesslova
- Center of Fetal Cardiology, IRCCS Policlinico San Donato, 20097 Milan, Italy
- Correspondence: or
| | - Anna Maria Colli
- U.O. Cardiologia, Fondazione Ca’ Granda, Ospedale Maggiore Policlinico, 20121 Milan, Italy;
| | - Simona Boito
- Fetal Medicine and Surgery Service, Department of Clinical Sciences and Community Health, University of Milan, 20121 Milan, Italy; (S.B.); (I.F.); (N.P.)
| | - Isabella Fabietti
- Fetal Medicine and Surgery Service, Department of Clinical Sciences and Community Health, University of Milan, 20121 Milan, Italy; (S.B.); (I.F.); (N.P.)
| | - Fabio Triulzi
- Department of Radiology, Fondazione Ca’ Granda, Ospedale Maggiore Policlinico, 20121 Milan, Italy;
| | - Nicola Persico
- Fetal Medicine and Surgery Service, Department of Clinical Sciences and Community Health, University of Milan, 20121 Milan, Italy; (S.B.); (I.F.); (N.P.)
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22
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The ENSO Working Group. Role of prenatal magnetic resonance imaging in fetuses with isolated anomalies of corpus callosum: multinational study. ULTRASOUND IN OBSTETRICS & GYNECOLOGY : THE OFFICIAL JOURNAL OF THE INTERNATIONAL SOCIETY OF ULTRASOUND IN OBSTETRICS AND GYNECOLOGY 2021; 58:26-33. [PMID: 33596324 DOI: 10.1002/uog.23612] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 01/27/2021] [Accepted: 02/08/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To assess the performance of fetal magnetic resonance imaging (MRI) in detecting associated anomalies in fetuses diagnosed with isolated corpus callosal (CC) anomaly on multiplanar ultrasound evaluation of the fetal brain (neurosonography). METHODS This was a multicenter, retrospective cohort study involving 14 fetal medicine centers in Italy, UK, Portugal, Canada, Austria and Spain. Inclusion criteria were fetuses with an apparently isolated CC anomaly, defined as an anomaly of the CC and no other additional central nervous system (CNS) or extra-CNS abnormality detected on expert ultrasound, including multiplanar neurosonography; normal karyotype; maternal age ≥ 18 years; and gestational age at diagnosis ≥ 18 weeks. The primary outcome was the rate of additional CNS abnormalities detected exclusively on fetal MRI within 2 weeks following neurosonography. The secondary outcomes were the rate of additional abnormalities according to the type of CC abnormality (complete (cACC) or partial (pACC) agenesis of the CC) and the rate of additional anomalies detected only on postnatal imaging or at postmortem examination. RESULTS A total of 269 fetuses with a sonographic prenatal diagnosis of apparently isolated CC anomalies (207 with cACC and 62 with pACC) were included in the analysis. Additional structural anomalies of the CNS were detected exclusively on prenatal MRI in 11.2% (30/269) of cases, with malformations of cortical development representing the most common type of anomaly. When stratifying the analysis according to the type of CC anomaly, the rate of associated anomalies detected exclusively on MRI was 11.6% (24/207) in cACC cases and 9.7% (6/62) in pACC cases. On multivariate logistic regression analysis, only maternal body mass index was associated independently with the likelihood of detecting associated anomalies on MRI (odds ratio, 1.07 (95% CI, 1.01-1.14); P = 0.03). Associated anomalies were detected exclusively after delivery and were missed on both types of prenatal imaging in 3.9% (8/205) of fetuses with prenatal diagnosis of isolated anomaly of the CC. CONCLUSION In fetuses with isolated anomaly of the CC diagnosed on antenatal neurosonography, MRI can identify a small proportion of additional anomalies, mainly malformations of cortical development, which are not detected on ultrasound. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.
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23
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Sutton D, Miller R. Neurologic Outcomes After Prenatal Treatment of Twin-Twin Transfusion Syndrome. Clin Perinatol 2020; 47:719-731. [PMID: 33153657 DOI: 10.1016/j.clp.2020.08.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Monochorionic twin gestations possess disproportionately higher risk for perinatal morbidity and mortality when compared with dichorionic twin pregnancies due to their potential to develop specific complications attributable to a shared placenta and intertwin placental circulation. Since the advent of fetoscopic laser surgery, outcomes of pregnancies affected by twin-twin transfusion syndrome (TTTS) have improved, with reduced rates of mortality and morbidity when compared with amnioreduction or expectant management. The focus of this article is to review the literature regarding neurologic outcomes among pediatric survivors of fetal intervention for TTTS.
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Affiliation(s)
- Desmond Sutton
- Division of Maternal-Fetal Fetal Medicine, Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, 622 West 168th Street, PH16-66, New York, NY 10032, USA
| | - Russell Miller
- Division of Maternal-Fetal Fetal Medicine, Department of Obstetrics and Gynecology, Columbia University College of Physicians and Surgeons, 622 West 168th Street, PH16-66, New York, NY 10032, USA.
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24
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Wilson M, Muir K, Reddy D, Webster R, Kapoor C, Miller E. Prognostic Accuracy of Fetal MRI in Predicting Postnatal Neurodevelopmental Outcome. AJNR Am J Neuroradiol 2020; 41:2146-2154. [PMID: 32943421 DOI: 10.3174/ajnr.a6770] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 07/06/2020] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND PURPOSE The superior diagnostic accuracy of fetal MR imaging in detecting fetal brain abnormalities has been previously demonstrated; however, the ability of fetal MR imaging to prognosticate postnatal outcome is not well-studied. We performed a retrospective analysis to determine the prognostic accuracy of fetal MR imaging in predicting postnatal neurodevelopmental outcome. MATERIALS AND METHODS We identified all fetal MR imaging performed at the Children's Hospital of Eastern Ontario during a 10-year period and assessed agreement between prenatal prognosis and postnatal outcome. Prenatal prognosis was determined by a pediatric neurologist who reviewed the fetal MR imaging report and categorized each pregnancy as having a favorable, indeterminate, or poor prognosis. Assessment of postnatal neurodevelopmental outcome was made solely on the basis of the child's Gross Motor Function Classification System score and whether the child developed epilepsy. Postnatal outcome was categorized as favorable, intermediate, or poor. We also assessed the diagnostic accuracy of fetal MR imaging by comparing prenatal and postnatal imaging diagnoses. RESULTS We reviewed 145 fetal MR images: 114 were included in the assessment of diagnostic accuracy, and 104 were included in the assessment of prognostic accuracy. There was 93.0% agreement between prenatal and postnatal imaging diagnoses. Prognosis was favorable in 44.2%, indeterminate in 50.0%, and poor in 5.8% of pregnancies. There was 93.5% agreement between a favorable prenatal prognosis and a favorable postnatal outcome. CONCLUSIONS A favorable prenatal prognosis is highly predictive of a favorable postnatal outcome. Further studies are required to better understand the role of fetal MR imaging in prognosticating postnatal development, particularly in pregnancies with indeterminate and poor prognoses.
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Affiliation(s)
- M Wilson
- From the Department of Medical Imaging (M.W., C.K., E.M.).,Department of Neurology (M.W.), Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - K Muir
- Pediatric Neurology (K.M.)
| | - D Reddy
- Research Institute (D.R., R.W.), Children's Hospital of Eastern Ontario, University of Ottawa,Ottawa, Ontario, Canada
| | - R Webster
- Research Institute (D.R., R.W.), Children's Hospital of Eastern Ontario, University of Ottawa,Ottawa, Ontario, Canada
| | - C Kapoor
- From the Department of Medical Imaging (M.W., C.K., E.M.)
| | - E Miller
- From the Department of Medical Imaging (M.W., C.K., E.M.)
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25
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Dierssen M. Top ten discoveries of the year: Neurodevelopmental disorders. FREE NEUROPATHOLOGY 2020; 1:13. [PMID: 37283674 PMCID: PMC10209851 DOI: 10.17879/freeneuropathology-2020-2672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/12/2020] [Indexed: 06/08/2023]
Abstract
Developmental brain disorders, a highly heterogeneous group of disorders with a prevalence of around 3% of worldwide population, represent a growing medical challenge. They are characterized by impaired neurodevelopmental processes leading to deficits in cognition, social interaction, behavior and motor functioning as a result of abnormal development of brain. This can include developmental brain dysfunction, which can manifest as neuropsychiatric problems or impaired motor function, learning, language or non-verbal communication. Several of these phenotypes can often co-exist in the same patient and characterize the same disorder. Here I discuss some contributions in 2019 that are shaking our basic understanding of the pathogenesis of neurodevelopmental disorders. Recent developments in sophisticated in-utero imaging diagnostic tools have raised the possibility of imaging the fetal human brain growth, providing insights into the developing anatomy and improving diagnostics but also allowing a better understanding of antenatal pathology. On the other hand, advances in our understanding of the pathogenetic mechanisms reveal a remarkably complex molecular neuropathology involving a myriad of genetic architectures and regulatory elements that will help establish more rigorous genotype-phenotype correlations.
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Affiliation(s)
- Mara Dierssen
- Centre for Genomic Regulation (CRG); The Barcelona Institute of Science and Technology, and Universitat Pompeu Fabra (UPF), 08003 Barcelona, Spain
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