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Age estimation by multidetector computed tomography of cranial sutures in Chinese male adults

Bibliographic Data

ID8314231
AuthorsFei Fan (0000-0002-9955-1683, West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China), Meng Tu (West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China), Rui Li (0000-0001-9744-7965, College of Computer Science Sichuan University Chengdu China), Xinhua Dai (0000-0002-0248-9554, West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China), Kui Zhang (0000-0003-2769-1940, West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China), Hu Chen (0000-0002-5958-9361, College of Computer Science Sichuan University Chengdu China, corresponding author), Feijun Huang (0000-0003-0313-7320, West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China, corresponding author), Zhenhua Deng (0000-0002-6412-7399, West China School of Basic Medical Sciences & Forensic Medicine Sichuan University Chengdu China, corresponding author)
Year2020
Volume171
Issue3
Pages550-558
Publication date2020-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueAmerican Journal of Physical Anthropology (JOURNAL)
Journal identifiersISSN: 0002-9483 • E-ISSN: 1096-8644
PublisherWiley (PUBLISHER • GB)
DOI10.1002/ajpa.23998
PMID31891181
OpenAlexW2997182476
LanguageEN
References cited36

OBJECTIVES: This study aimed to explore whether computed tomography (CT) images of cranial sutures can contribute to adult age estimation in Chinese Han individuals. MATERIALS AND METHODS: This study was based on cranial CT scans of 230 Chinese Han males aged 23.33-76.93 years. A total of 160 images from 16 suture segments were scored after volume reformation and multiplanar reconstruction in each individual. Decision tree regression, linear support vector regression, Bayesian ridge regression, and gradient boosting regression were developed for adult age estimation by a training set using leave-one-out cross-validation and further evaluated by the test set. The inaccuracy and bias were calculated to evaluate the four models and the previously used models from the literature. RESULTS: The degree of suture closure was associated with adult age. The minimum inaccuracy of the test set was 7.73 years obtained by linear support vector regression, while the inaccuracy of previous simple linear regression models was 13.09 and 10.97 years. The accuracy was higher in the age group from 40.00 to 59.99 years compared to the other age groups. DISCUSSION: The accuracy of our models for adult age estimation was superior to those in previous studies based on cranial sutures. Hence, the application of novel statistical data mining tools helps to improve aging issues. Nevertheless, age estimation of adults should be combined with other methods, since the accuracy level is still not satisfactory

Bayesian multivariate linear regression · Computed tomography · Estimation · Fibrous joint · Linear regression · Regression · Regression analysis · Statistics · Craniofacial Disorders and Treatments · Forensic Anthropology and Bioarchaeology Studies · Mathematics · Medicine · Orthodontics and Dentofacial Orthopedics · Surgery

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