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Conventional microscopy makes perikymata count and spacing data feasible for large samples
Author(s) -
Edgar Heather J. H.,
Moes Emily,
Willermet Cathy,
S. Ragsdale Corey
Publication year - 2021
Publication title -
american journal of physical anthropology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.146
H-Index - 119
eISSN - 1096-8644
pISSN - 0002-9483
DOI - 10.1002/ajpa.24369
Subject(s) - percentile , microscopy , human tooth , population , enamel paint , materials science , mathematics , statistics , optics , medicine , physics , environmental health , composite material
Objectives Current methods of quantifying defects of dental enamel (DDE) include either gross or low‐level examination for linear enamel hypoplasia, histological analysis of striae of Retzius, or scanning electron microscopy (SEM) of a tooth or a tooth cast. Gross examination has been shown to miss many defects. Other methods can be destructive, require transporting samples, and are expensive. Here, we show that digital light microscopy (DLM) can be used for the analysis of DDE as indicated by widened perikymata spacing (WPS). This method takes advantage of high‐power (100×) microscopy, but is non‐destructive, can be implemented almost anywhere, and is inexpensive. Materials and Methods As proof of concept, we created photomontages of labial surfaces of five human canines from images made using DLM and SEM. We counted and measured the widths of all visible perikymata for each imaging modality and fit measurements to a negative curve representing the expected values for each tooth. We calculated residuals for each measurement. WPS were defined when R 2 was in the 90th percentile, and were considered matched in DLM and SEM images when observed within the same decile of the tooth surface. Results There were more WPS detected in the images derived from DLM than from SEM. Overall, the data derived from the two imaging modalities provided similar information about the frequency and timing of stress during dental development. Conclusions The method described here allows for DDE data acquisition as WPS from large samples, making feasible population‐level studies that reflect sophisticated understanding of dental development.