Jannick De Tobel1, Steffen Fieuws2, Elke Hillewig3, Inès Phlypo4, Mayonne van Wijk5, Michiel Bart de Haas6, Constantinus Politis7, Koenraad Luc Verstraete8, Patrick Werner Thevissen9. 1. Department of Diagnostic Sciences - Radiology, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Department of Imaging and Pathology - Forensic Odontology, KU Leuven, Kapucijnenvoer 7 blok a bus 7001, 3000 Leuven, Belgium; Department of Oral and Maxillofacial Surgery, Leuven University Hospitals, Kapucijnenvoer 33, 3000 Leuven, Belgium. Electronic address: jannick.detobel@ugent.be. 2. KU Leuven - Leuven University & Hasselt University, Department of Public Health and Primary Care, l-BioStat, Leuven, Kapucijnenvoer 35 blok d bus 7001, 3000 Leuven, Belgium. Electronic address: steffen.fieuws@kuleuven.be. 3. Department of Diagnostic Sciences - Radiology, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium. Electronic address: elke.hillewig@gmail.com. 4. Department of Oral Health Sciences - Special Needs in Dentistry, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium. Electronic address: ines.phlypo@ugent.be. 5. Division of Special Services and Expertise, Section of Forensic Anthropology, Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB The Hague, the Netherlands. Electronic address: m.van.wijk@nfi.minvenj.nl. 6. Division of Special Services and Expertise, Section of Forensic Anthropology, Netherlands Forensic Institute, Laan van Ypenburg 6, 2497 GB The Hague, the Netherlands. Electronic address: m.de.haas@nfi.minvenj.nl. 7. Department of Oral and Maxillofacial Surgery, Leuven University Hospitals, Kapucijnenvoer 33, 3000 Leuven, Belgium. Electronic address: constantinus.politis@uzleuven.be. 8. Department of Diagnostic Sciences - Radiology, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium. Electronic address: koenraad.verstraete@ugent.be. 9. Department of Imaging and Pathology - Forensic Odontology, KU Leuven, Kapucijnenvoer 7 blok a bus 7001, 3000 Leuven, Belgium. Electronic address: patrick.thevissen@kuleuven.be.
Abstract
PURPOSE: To study age estimation performance of combined magnetic resonance imaging (MRI) data of all four third molars, the left wrist and both clavicles in a reference population of females and males. To study the value of adding anthropometric and sexual maturation data. MATERIALS AND METHODS: Three Tesla MRI of the three anatomical sites was prospectively conducted from March 2012 to May 2017 in 14- to 26-year-old healthy Caucasian volunteers (160 females, 138 males). Development was assessed by allocating stages, anthropometric measurements were taken, and self-reported sexual maturation data were collected. All data was incorporated in a continuation-ratio model to estimate age, applying Bayes' rule to calculate point and interval predictions. Two performance aspects were studied: (1) accuracy and uncertainty of the point prediction, and (2) diagnostic ability to discern minors from adults (≥18 years). RESULTS: Combining information from different anatomical sites decreased the mean absolute error (MAE) compared to incorporating only one site (P<0.0001). By contrast, adding anthropometric and sexual maturation data did not further improve MAE (P=0.11). In females, combining all three anatomical sites rendered a MAE equal to 1.41 years, a mean width of the 95% prediction intervals of 5.91 years, 93% correctly classified adults and 91% correctly classified minors. In males, the corresponding results were 1.36 years, 5.49 years, 94%, and 90%, respectively. CONCLUSION: All aspects of age estimation improve when multi-factorial MRI data of the three anatomical sites are incorporated. Anthropometric and sexual maturation data do not seem to add relevant information.
PURPOSE: To study age estimation performance of combined magnetic resonance imaging (MRI) data of all four third molars, the left wrist and both clavicles in a reference population of females and males. To study the value of adding anthropometric and sexual maturation data. MATERIALS AND METHODS: Three Tesla MRI of the three anatomical sites was prospectively conducted from March 2012 to May 2017 in 14- to 26-year-old healthy Caucasian volunteers (160 females, 138 males). Development was assessed by allocating stages, anthropometric measurements were taken, and self-reported sexual maturation data were collected. All data was incorporated in a continuation-ratio model to estimate age, applying Bayes' rule to calculate point and interval predictions. Two performance aspects were studied: (1) accuracy and uncertainty of the point prediction, and (2) diagnostic ability to discern minors from adults (≥18 years). RESULTS: Combining information from different anatomical sites decreased the mean absolute error (MAE) compared to incorporating only one site (P<0.0001). By contrast, adding anthropometric and sexual maturation data did not further improve MAE (P=0.11). In females, combining all three anatomical sites rendered a MAE equal to 1.41 years, a mean width of the 95% prediction intervals of 5.91 years, 93% correctly classified adults and 91% correctly classified minors. In males, the corresponding results were 1.36 years, 5.49 years, 94%, and 90%, respectively. CONCLUSION: All aspects of age estimation improve when multi-factorial MRI data of the three anatomical sites are incorporated. Anthropometric and sexual maturation data do not seem to add relevant information.
Authors: Jannick De Tobel; Mayonne van Wijk; Ivo Alberink; Elke Hillewig; Inès Phlypo; Rick R van Rijn; Patrick Werner Thevissen; Koenraad Luc Verstraete; Michiel Bart de Haas Journal: Int J Legal Med Date: 2020-03 Impact factor: 2.686
Authors: Markus Auf der Mauer; Eilin Jopp-van Well; Jochen Herrmann; Michael Groth; Michael M Morlock; Rainer Maas; Dennis Säring Journal: Int J Legal Med Date: 2020-12-17 Impact factor: 2.686
Authors: Matthias Zirk; Joachim E Zoeller; Max-Philipp Lentzen; Laura Bergeest; Johannes Buller; Max Zinser Journal: Sci Rep Date: 2021-04-27 Impact factor: 4.379