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

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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00414-023-03055-5.