An automated method to analyze root filling voids and gaps using confocal microscopy images

[Abstract] This study evaluated the feasibility of an automated method to delimit the required area to quantitatively analyze root filling voids and gaps from cross-sectional confocal laser scanning microscopy (CLSM) images. Root canals of maxillary canines were prepared with rotary instruments and...

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Bibliographic Details
Published in:Odontology 2024-04, Vol.112 (2), p.546-551
Main Authors: Brito-Júnior, Manoel, Silva-Sousa, Yara Teresinha Correa, Pereira, Rodrigo Dantas, Camilo, Carla Cristina, Mazzi-Chaves, Jardel Francisco, Lopes-Olhê, Fabiane Carneiro, Sousa-Neto, Manoel D.
Format: Article
Language:English
Subjects:
Automation
Confocal microscopy
Dentistry
Feasibility studies
Medicine
Microscopy
Oral and Maxillofacial Surgery
Original Article
Root canals
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Summary:[Abstract] This study evaluated the feasibility of an automated method to delimit the required area to quantitatively analyze root filling voids and gaps from cross-sectional confocal laser scanning microscopy (CLSM) images. Root canals of maxillary canines were prepared with rotary instruments and filled by lateral compaction technique using gutta-percha and AH Plus sealer. The roots were stored (100% humidity, 37 ℃) for a period of 24 h and then transversally sectioned to obtain 2-mm-thick slices from the apical and middle thirds. The areas corresponding to filling materials, gaps, and voids were manually delimited or automatically demarked by ImageJ software after converting the images to the RGB color system. Based on manual and automatic delimitations, the percentages of voids and gaps were calculated. Data of voids and gaps between middle and apical thirds were individually compared by paired t-test. Pearson's correlation test was used to assess the correlation of data between the methods. Irrespective of the method of area delimitation, no difference was observed between the root thirds for both voids and gaps, while the p-values calculated for each method were similar. Almost perfect correlations between the methods were observed for both outcomes. The proposed method to automatically delimit the areas corresponding to filling material, voids, and gaps appears to be a valid method to facilitate the quantitative analysis of defects in root canal fillings using topographic CSLM images.
ISSN:1618-1247
1618-1255
DOI:10.1007/s10266-023-00859-0