Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

Mai Britt Bjørk; Sigrid Ingeborg Kvaal; Øyvind Bleka; Tomas Sakinis; Frode Alexander Tuvnes; Mari-Ann Haugland; Heidi Beate Eggesbø; Peter Mæhre Lauritzen

doi:10.1007/s00414-023-03055-5

Prediction of Age Older than 18 Years in Sub-adults by MRI Segmentation of 1st and 2nd Molars

Int J Legal Med. 2023 Sep;137(5):1515-1526. doi: 10.1007/s00414-023-03055-5. Epub 2023 Jul 4.

Authors

Affiliations

¹ Institute of Clinical Dentistry, Faculty of Dentistry, University of Oslo, Postboks 1109, Blindern, N-00317, Oslo, Norway. m.b.bjork@odont.uio.no.
² Institute of Clinical Dentistry, Faculty of Dentistry, University of Oslo, Postboks 1109, Blindern, N-00317, Oslo, Norway.
³ Department of Forensic Sciences, Oslo University Hospital, Postboks 4950 Nydalen, OUS, Rikshospitalet, 0424, Oslo, Norway.
⁴ Division of Radiology and Nuclear Medicine, Oslo University Hospital, Postboks 4950 Nydalen, OUS, Ullevål, 0424, Oslo, Norway.
⁵ Institute of Clinical Medicine, Faculty of medicine, University of Oslo, Postboks 4950 Nydalen, OUS, 0424, Oslo, Norway.
⁶ Faculty of Health Sciences, Department of Life Sciences and Health. Oslo Metropolitan University, Postboks 4, St. Olavs plass, 0130, Oslo, Norway.

^# Contributed equally.

Abstract

Purpose: To investigate prediction of age older than 18 years in sub-adults using tooth tissue volumes from MRI segmentation of the entire 1st and 2nd molars, and to establish a model for combining information from two different molars.

Materials and methods: We acquired T2 weighted MRIs of 99 volunteers with a 1.5-T scanner. Segmentation was performed using SliceOmatic (Tomovision©). Linear regression was used to analyse the association between mathematical transformation outcomes of tissue volumes, age, and sex. Performance of different outcomes and tooth combinations were assessed based on the p-value of the age variable, common, or separate for each sex, depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach using information from the 1st and 2nd molars both separately and combined.

Results: 1st molars from 87 participants, and 2nd molars from 93 participants were included. The age range was 14-24 years with a median age of 18 years. The transformation outcome (high signal soft tissue + low signal soft tissue)/total had the strongest statistical association with age for the lower right 1st (p= 7.1*10^-4 for males) and 2nd molar (p=9.44×10^-7 for males and p=7.4×10^-10 for females). Combining the lower right 1st and 2nd molar in males did not increase the prediction performance compared to using the best tooth alone.

Conclusion: MRI segmentation of the lower right 1st and 2nd molar might prove useful in the prediction of age older than 18 years in sub-adults. We provided a statistical framework to combine the information from two molars.

Keywords: 1st and 2nd molars; Age estimation; Magnetic resonance imaging; Segmentation; Sub-adults.

MeSH terms

Adolescent
Adult
Bayes Theorem
Female
Humans
Linear Models
Magnetic Resonance Imaging*
Male
Molar* / diagnostic imaging
Probability
Young Adult