Non-invasive assessment of peri-implant mucosal thickness: A cross-sectional study.

Couso-Queiruga, Emilio; Raabe, Clemens; Belser, Urs C; Buser, Daniel; Avila-Ortiz, Gustavo; Rodrigues, Diogo Moreira; Chappuis, Vivianne (2023). Non-invasive assessment of peri-implant mucosal thickness: A cross-sectional study. Journal of periodontology, 94(11), pp. 1315-1323. Wiley 10.1002/JPER.23-0102

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BACKGROUND

This study aimed to evaluate the reliability and reproducibility of different non-invasive methods for the assessment of peri-implant mucosal thickness.

METHODS

Subjects with two adjacent dental implants in the central maxillary region were included in this study. Three different methods to assess facial mucosal thickness (FMT) were compared: digital file superimposition using Digital Imaging and Communication in Medicine (DICOM) and stereolithography (STL) files of the arch of interest (DICOM-STL), DICOM files alone, and non-ionizing ultrasound (US). Inter-rater reliability agreements between different assessment methods were analyzed using inter-class correlation coefficients (ICCs).

RESULTS

A total of 50 subjects with 100 bone-level implants constituted the study population. Assessment of FMT using STL and DICOM files demonstrated excellent inter-rater reliability agreement. Mean ICC values of 0.97 and 0.95 were observed in the DICOM-STL and DICOM groups, respectively. Comparison between the DICOM-STL and US revealed good agreement, with an ICC of 0.82 (95% CI: 0.74 to 0.88) and a mean difference of -0.13 ± 0.50 mm (-1.13 to 0.86). Comparison between DICOM files alone versus US showed good agreement, with an ICC of 0.81 (95% CI: 0.73 to 0.89) and a mean difference of -0.23 ± 0.46 mm (-1.12 to 0.67). Comparison between DICOM-STL and DICOM files revealed excellent agreement, with an ICC of 0.94 (95% CI: 0.91 to 0.96) and a mean difference of 0.1 ± 0.29 mm (LOA -0.47 to 0.46).

CONCLUSIONS

Quantification of peri-implant mucosal thickness via analysis of DICOM-STL files, DICOM files, or US assessment are comparably reliable and reproducible methods.

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