R Bruggink1,2, F Baan3,4, G J C Kramer5, T J J Maal4,6, A M Kuijpers-Jagtman3, S J Bergé6,7, E M Bronkhorst8, E M Ongkosuwito3,7. 1. Department of Dentistry, section of Orthodontics and Craniofacial Biology, Radboud University Medical Center, Philips van Leydenlaan 25, 6525 EX, Nijmegen, The Netherlands. orthodontie@radboudumc.nl. 2. Radboudumc 3DLab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. orthodontie@radboudumc.nl. 3. Department of Dentistry, section of Orthodontics and Craniofacial Biology, Radboud University Medical Center, Philips van Leydenlaan 25, 6525 EX, Nijmegen, The Netherlands. 4. Radboudumc 3DLab, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. 5. Department of Orthodontics, Academic Center for Dentistry Amsterdam ACTA, Gustav Mahlerlaan 3004, 1081 LA, Amsterdam, The Netherlands. 6. Department of Oral and Maxillofacial Surgery, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. 7. Amalia Cleft and Craniofacial Centre, Radboud University Medical Centre, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands. 8. Department of Dentistry, section of Preventive and Restorative Dentistry, Radboud University Medical Centre, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands.
Abstract
OBJECTIVES: The aim of this study was to develop an accurate and intuitive semi-automatic segmentation technique to calculate an average maxillary arch and palatal growth profile for healthy newborns in their first year of life. MATERIALS AND METHODS: Seventy babies born between 1985 and 1988 were included in this study. Each child had five impressions made in the first year after birth that were digitalized. A semi-automatic segmentation tool was developed and used to assess the maxillary dimensions. Finally, random effect models were built to describe the growth and build a simulation population of 10,000 newborns. The segmentation was tested for inter- and intra-observer variability. RESULTS: The Pearson correlation coefficient for each of the variables was between 0.94 and 1.00, indicating high inter-observer agreement. The paired sample t test showed that, except for the tuberosity distance, there were small, but significant differences in the landmark placements between observers. Intra-observer repeatability was high, with Pearson correlation coefficients ranging from 0.87 to 1.00 for all measurements, and the mean differences were not significant. A third or second degree growth curve could be successfully made for each parameter. CONCLUSIONS: These findings indicated this method could be used for objective clinical evaluation of maxillary growth. CLINICAL RELEVANCE: The resulting growth models can be used for growth studies in healthy newborns and for growth and treatment outcome studies in children with cleft lip and palate or other craniofacial anomalies.
OBJECTIVES: The aim of this study was to develop an accurate and intuitive semi-automatic segmentation technique to calculate an average maxillary arch and palatal growth profile for healthy newborns in their first year of life. MATERIALS AND METHODS: Seventy babies born between 1985 and 1988 were included in this study. Each child had five impressions made in the first year after birth that were digitalized. A semi-automatic segmentation tool was developed and used to assess the maxillary dimensions. Finally, random effect models were built to describe the growth and build a simulation population of 10,000 newborns. The segmentation was tested for inter- and intra-observer variability. RESULTS: The Pearson correlation coefficient for each of the variables was between 0.94 and 1.00, indicating high inter-observer agreement. The paired sample t test showed that, except for the tuberosity distance, there were small, but significant differences in the landmark placements between observers. Intra-observer repeatability was high, with Pearson correlation coefficients ranging from 0.87 to 1.00 for all measurements, and the mean differences were not significant. A third or second degree growth curve could be successfully made for each parameter. CONCLUSIONS: These findings indicated this method could be used for objective clinical evaluation of maxillary growth. CLINICAL RELEVANCE: The resulting growth models can be used for growth studies in healthy newborns and for growth and treatment outcome studies in children with cleft lip and palate or other craniofacial anomalies.
Authors: Robin Bruggink; Frank Baan; Gem Kramer; Colet Claessens; Anne Marie Kuijpers-Jagtman; Ewald M Bronkhorst; Thomas J J Maal; Edwin Ongkosuwito Journal: PeerJ Date: 2020-07-30 Impact factor: 2.984
Authors: Robin Bruggink; Frank Baan; Sander Brons; Tom G J Loonen; Anne Marie Kuijpers-Jagtman; Thomas J J Maal; Edwin M Ongkosuwito Journal: PeerJ Date: 2022-06-07 Impact factor: 3.061
Authors: R Bruggink; F Baan; G J C Kramer; A M Kuijpers-Jagtman; S J Bergé; T J J Maal; E M Ongkosuwito Journal: Clin Oral Investig Date: 2020-06-24 Impact factor: 3.573