A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients
<i>Background:</i> Skeletal age estimation plays a fundamental role in orthopedic treatments. Since the most reliable methods are based on ionizing radiation, this study aimed to use machine learning techniques to explore a skeletal age assessment method not based on additional radiograp...
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2025-05-01
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| author | Michele Tepedino Rosa Esposito Maurizio Delvecchio Domenico Ciavarella Giuseppe Rofrano Francesco Masedu |
| author_facet | Michele Tepedino Rosa Esposito Maurizio Delvecchio Domenico Ciavarella Giuseppe Rofrano Francesco Masedu |
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| description | <i>Background:</i> Skeletal age estimation plays a fundamental role in orthopedic treatments. Since the most reliable methods are based on ionizing radiation, this study aimed to use machine learning techniques to explore a skeletal age assessment method not based on additional radiographies. <i>Methods</i>: Patients aged between 6 and 16 years old whose clinical records included orthopantomography, radiographs of the second phalanx of the third finger, and biometric data were enrolled for the study. The radiographs were analyzed to estimate the maturation degree of the left lower first premolars, the midpalatal suture, and the second phalanx of the third finger. Both an explicative data analysis and a multivariate analysis were performed. <i>Results</i>: The sample comprised 111 subjects. The multivariate analysis revealed an explanatory role for sex (<i>p</i> < 0.01) and chronological age (<i>p</i> < 0.01). The ordinal tool showed how the use of height (<i>p</i> = 0.02) and weight (<i>p</i> = 0.03) was explicative of skeletal age against a loss of statistical significance corresponding to the use of body mass index (<i>p</i> = 0.6). The median palatine suture (<i>p</i> = 0.01) was explicative. <i>Conclusions</i>: The combined evaluation of weight, height, sex, chronological age, and grade of maturation of the midpalate suture provides an explicative tool for assessing skeletal age without additional radiographic exams, besides a routine orthopantomography. |
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| spelling | doaj-art-4be90185e6a8412ea190c86380e326e92025-08-20T01:56:17ZengMDPI AGApplied Sciences2076-34172025-05-011510559310.3390/app15105593A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing PatientsMichele Tepedino0Rosa Esposito1Maurizio Delvecchio2Domenico Ciavarella3Giuseppe Rofrano4Francesco Masedu5Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, ItalyDepartment of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, ItalyDepartment of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, ItalyDepartment of Clinical and Experimental Medicine, School of Dentistry, University of Foggia, 71122 Foggia, ItalyExperimental Zooprophylactic Institute of the South, National Reference Center for the Analysis and Study of the Correlation Between Environment, Animals and Humans, 80055 Portici, ItalyDepartment of Biotechnological and Applied Clinical Sciences, University of L’Aquila, 67100 L’Aquila, Italy<i>Background:</i> Skeletal age estimation plays a fundamental role in orthopedic treatments. Since the most reliable methods are based on ionizing radiation, this study aimed to use machine learning techniques to explore a skeletal age assessment method not based on additional radiographies. <i>Methods</i>: Patients aged between 6 and 16 years old whose clinical records included orthopantomography, radiographs of the second phalanx of the third finger, and biometric data were enrolled for the study. The radiographs were analyzed to estimate the maturation degree of the left lower first premolars, the midpalatal suture, and the second phalanx of the third finger. Both an explicative data analysis and a multivariate analysis were performed. <i>Results</i>: The sample comprised 111 subjects. The multivariate analysis revealed an explanatory role for sex (<i>p</i> < 0.01) and chronological age (<i>p</i> < 0.01). The ordinal tool showed how the use of height (<i>p</i> = 0.02) and weight (<i>p</i> = 0.03) was explicative of skeletal age against a loss of statistical significance corresponding to the use of body mass index (<i>p</i> = 0.6). The median palatine suture (<i>p</i> = 0.01) was explicative. <i>Conclusions</i>: The combined evaluation of weight, height, sex, chronological age, and grade of maturation of the midpalate suture provides an explicative tool for assessing skeletal age without additional radiographic exams, besides a routine orthopantomography.https://www.mdpi.com/2076-3417/15/10/5593orthodonticsskeletal age assessmentpubertal growth spurtradiographic evaluationmiddle phalanx maturation |
| spellingShingle | Michele Tepedino Rosa Esposito Maurizio Delvecchio Domenico Ciavarella Giuseppe Rofrano Francesco Masedu A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients Applied Sciences orthodontics skeletal age assessment pubertal growth spurt radiographic evaluation middle phalanx maturation |
| title | A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients |
| title_full | A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients |
| title_fullStr | A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients |
| title_full_unstemmed | A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients |
| title_short | A Statistical Procedure for Exploring a Skeletal Age-Explicative Tool for Growing Patients |
| title_sort | statistical procedure for exploring a skeletal age explicative tool for growing patients |
| topic | orthodontics skeletal age assessment pubertal growth spurt radiographic evaluation middle phalanx maturation |
| url | https://www.mdpi.com/2076-3417/15/10/5593 |
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