Automated age-at-death estimation by cementochronology: Essential application or additional complication?

Abstract

It has been repeatedly acknowledged that age-at-death estimation based on dental cementum represents a partial and time-consuming method that hinders adoption of this histological approach. User-friendly micrograph analysis represents a growing request of cementochronology. This article evaluates the feasibility of using a module to accurately quantify cementum deposits and compares the module's performance to that of a human expert. On a dental collection (n = 200) of known-age individuals, precision and accuracy of estimates performed by a developed program (101 count/tooth; n = 20,200 counts) were compared to counts performed manually (5 counts/tooth; n = 975 counts). Reliability of the software and agreement between the two approaches were assessed by intraclass correlation coefficient and Bland Altman analysis. The automated module produced reliable and reproducible counts with a higher global precision than the human expert. Although the software is slightly more precise, it shows higher sensitivity to taphonomic damages and does not avoid the trajectory effect described for age-at-death estimation in adults. Likewise, for human counts, global accuracy is acceptable, but underestimations increase with age. The quantification of the agreement between the two approaches shows a minor bias, and 94% of individuals fall within the intervals of agreement. Automation gives an impression of objectivity even though the region of interest, profile position and parameters are defined manually. The automated system may represent a time-saving module that can allow an increase in sample size, which is particularly stimulating for population-based studies.

Keywords: age‐at‐death; automation; cementochronology; dental cementum.

FIGURE 1

Bar chart showing the distribution by age and sex of the dental reference sample grouped by five‐years intervals

FIGURE 2

Micrograph imported in the image analysis software for automated detection of cementum deposits. The group of parallel segments is drawn by the operator and symbolizes the central segment surrounded by two external segments. Detection can be performed along a single group of segments (a) or from concatenated profiles (b). Intensity profile achieved from one profile along cementum width (c). The scale is 100 μm

FIGURE 3

Bland–Altman plot showing the concordance between annuli automated counts with an interval of six months (a) compared to an identical approach for manual counts (b) (Bertrand, 2019). The solid line represents the mean difference, and the dotted lines represent the 95% limits of agreement

FIGURE 4

Descriptive statistics of the absolute precision and the relative precision of the counts for the automated approach in cementochronology. a‐b: Histograms representing the distribution of the global precision; c‐d: Scatter plots displaying the relationship between precision and chronological age; e‐f: Error‐bar charts indicating 95% confidence intervals of precision by age classes.

FIGURE 5

Descriptive statistics of the absolute accuracy and the relative accuracy of ages estimates for the automated approach in cementochronology. a‐b: Histograms representing the distribution of the global accuracy; c‐d: Scatter plots displaying the relationship between accuracy and chronological age; e‐f: Error‐bar charts indicating 95% confidence intervals of accuracy by age classes.

FIGURE 6

Bland–Altman plot (a) and accompanying histogram (b) showing the distribution of mean differences between automated and manual counts

FIGURE 7

Transverse section of a canine extracted from one of the WWI soldiers showing taphonomic alteration (iron oxide infiltration). The scale is 50 μm