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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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