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Neurocranium thickness mapping in early childhood.
Gajawelli, Niharika; Deoni, Sean; Shi, Jie; Linguraru, Marius George; Porras, Antonio R; Nelson, Marvin D; Tamrazi, Benita; Rajagopalan, Vidya; Wang, Yalin; Lepore, Natasha.
Afiliación
  • Gajawelli N; CIBORG Laboratory, Department of Radiology, Children's Hospital Los Angeles, Los Angeles, CA, USA.
  • Deoni S; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA.
  • Shi J; Voxel Healthcare, LLC, Los Angeles, CA, USA.
  • Linguraru MG; Advanced Baby Imaging Lab, Women & Infants Hospital of RI, Providence, RI, USA.
  • Porras AR; Department of Pediatrics, Warren Alpert Medical School at Brown University, Providence, RI, USA.
  • Nelson MD; Department of Radiology, Warren Alpert Medical School at Brown University, Providence, RI, USA.
  • Tamrazi B; Department of Computer Science, Arizona State University, Tempe, AZ, USA.
  • Rajagopalan V; Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington, DC, USA.
  • Wang Y; Departments of Radiology and Pediatrics, George Washington University, Washington, DC, USA.
  • Lepore N; Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschultz Medical Campus, Aurora, CO, USA.
Sci Rep ; 10(1): 16651, 2020 10 06.
Article en En | MEDLINE | ID: mdl-33024168
The neurocranium changes rapidly in early childhood to accommodate the growing brain. Developmental disorders and environmental factors such as sleep position may lead to abnormal neurocranial maturation. Therefore, it is important to understand how this structure develops, in order to provide a baseline for early detection of anomalies. However, its anatomy has not yet been well studied in early childhood due to the lack of available imaging databases. In hospitals, CT is typically used to image the neurocranium when a pathology is suspected, but the presence of ionizing radiation makes it harder to construct databases of healthy subjects. In this study, instead, we use a dataset of MRI data from healthy normal children in the age range of 6 months to 36 months to study the development of the neurocranium. After extracting its outline from the MRI data, we used a conformal geometry-based analysis pipeline to detect local thickness growth throughout this age span. These changes will help us understand cranial bone development with respect to the brain, as well as detect abnormal variations, which will in turn inform better treatment strategies for implicated disorders.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Postura / Cráneo / Desarrollo Óseo / Enfermedades del Desarrollo Óseo / Encéfalo / Imagen por Resonancia Magnética / Cefalometría / Conjuntos de Datos como Asunto Tipo de estudio: Screening_studies Límite: Child, preschool / Female / Humans / Infant / Male / Newborn Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Postura / Cráneo / Desarrollo Óseo / Enfermedades del Desarrollo Óseo / Encéfalo / Imagen por Resonancia Magnética / Cefalometría / Conjuntos de Datos como Asunto Tipo de estudio: Screening_studies Límite: Child, preschool / Female / Humans / Infant / Male / Newborn Idioma: En Revista: Sci Rep Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido