Age prediction in sub-adults based on MRI segmentation of 3rd molar tissue volumes

Abstract

Purpose Our aim was to investigate tissue volumes measured by MRI segmentation of the entire 3rd molar for prediction of a sub-adult being older than 18 years. Material and method We used a 1.5-T MR scanner with a customized high-resolution single T2 sequence acquisition with 0.37 mm iso-voxels. Two dental cotton rolls drawn with water stabilized the bite and delineated teeth from oral air. Segmentation of the different tooth tissue volumes was performed using SliceOmatic (Tomovision©). Linear regression was used to analyze the association between mathematical transformation outcomes of the tissue volumes, age, and sex. Performance of different transformation outcomes and tooth combinations were assessed based on the p value of the age variable, combined or separated for each sex depending on the selected model. The predictive probability of being older than 18 years was obtained by a Bayesian approach. Results We included 67 volunteers (F/M: 45/22), range 14–24 years, median age 18 years. The transformation outcome (pulp + predentine)/total volume for upper 3rd molars had the strongest association with age (p = 3.4 × 10−9). Conclusion MRI segmentation of tooth tissue volumes might prove useful in the prediction of age older than 18 years in sub-adults.

MRI segmentation of tooth tissue in age prediction of sub-adults — a new method for combining data from the 1st, 2nd, and 3rd molars

“…This result matches the results in our previous research where tooth 46, 47 and 18 were the best performing single teeth in males [ 6 , 7 ]. The prediction performance was mostly driven by the 3rd molars, and all combinations involving the 3rd molar consistently demonstrated smaller IQR values, regardless of the quadrant of the 3rd molar.…”

“…The upper and lower prior were identical to our two prior studies [ 6 , 7 ]. The lower age prior was dictated by the 3rd molar development, as the 3rd molar is less suitable for age prediction in individuals below 14 years of age.…”

“…We included the same cohort of 99 healthy volunteers (F/M 65/34, age range 14–24 years, median 18 years) from sports clubs and universities in the period of 2018–2021, including the same imaging and segmentation data set as in two previous studies [ 6 , 7 ].…”

“…We have previously shown that the ratio (high signal soft tissue + low signal soft tissue)/total from full volume MRI-segmentation of the 3rd molars may be a valuable parameter in age estimation [ 6 ]. In a follow-up study using the same material, we found the same ratio in the 1st and 2nd molars to be valuable and provided a novel method that managed to combine the information from the two molars [ 7 ].…”

“…In this study, we expand the methodology to enable the combination of all three different molars (1st, 2nd and 3rd) to provide age assessment [ 6 , 7 ].…”