Age-dependent decrease in dental pulp cavity volume as a feature for age assessment: a comparative in vitro study using 9.4-T UTE-MRI and CBCT 3D imaging

Timme, Maximilian; Borkert, Jens; Nagelmann, Nina; Streeter, Adam; Karch, André; Schmeling, Andreas

doi:10.1007/s00414-021-02603-1

Cited by 5 publications

(1 citation statement)

References 59 publications

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“…Two studies including extracted teeth, using a 9.4-T ultrashort echo time MRI, managed to determine pulp cavity volume, but the field of view and spatial resolution had to be adjusted for each different type of tooth [ 29 , 30 ].…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2023

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A potential novel technique for measurement of pulp volume on periapical radiography: A pilot study

Şatır,

Özel,

Orhan

2024

The Kaohsiung J of Med Scie

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Pulp volume can be assessed during dental treatment. Three‐dimensional imaging techniques are not routinely used for this purpose because of high radiation doses. This study aimed to develop a novel method to measure pulp volume using periapical radiography. In this study, cone‐beam computed tomography (CBCT) was used as a reference method. Periapical radiography and CBCTs obtained from the same patients (n = 32) were recorded. Pulp volume was determined by observing the density differences between the pulp and peripheral structures using ImageJ. A method of graph and volume calculation was developed for each tooth. The Shapiro–Wilk test and Mann–Whitney U test were used to show normality and non‐normal distributions. The Bland–Altman plot was used to show the scattering of the mean versus difference values of the measurements of the two methods used to calculate the pulp volume. Normality was evaluated using the Shapiro–Wilk test. CBCT measurements are normally distributed (p = 0.307), while ImageJ is not normally distributed (p = 0.027). Therefore, the mean difference between the two groups was analyzed using the nonparametric Mann–Whitney U test. There was a statistically significant difference between the CBCT and ImageJ measurements (p = 0.01). According to Spearman's correlation analysis, the results obtained from the novel method were moderately correlated with those obtained from the reference method (r = 0.444). The results of this study indicated that a novel method‐based Java software can be used to calculate pulp volume using low‐dose radiation containing periapical radiography.

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

et al. 2023

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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.

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Age-dependent decrease in dental pulp cavity volume as a feature for age assessment: a comparative in vitro study using 9.4-T UTE-MRI and CBCT 3D imaging

Cited by 5 publications

References 59 publications

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

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

A potential novel technique for measurement of pulp volume on periapical radiography: A pilot study

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

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