Accurate gingival recession quantification using 3D digital dental models

Autor: Mohammed Ghamri, Christos Katsaros, Konstantinos Dritsas, Demetrios Halazonetis, Nikolaos Gkantidis, Anton Sculean
Rok vydání: 2022
Předmět:
Zdroj: Dritsas, Konstantinos; Halazonetis, Demetrios; Ghamri, Mohammed; Sculean, Anton; Katsaros, Christos; Gkantidis, Nikolaos (2023). Accurate gingival recession quantification using 3D digital dental models. Clinical oral investigations, 27(4), pp. 1697-1705. Springer 10.1007/s00784-022-04795-1
ISSN: 1436-3771
DOI: 10.1007/s00784-022-04795-1
Popis: Objectives To develop and validate a method for accurate quantitative assessment of gingival recessions based on superimposition of serial 3D digital models. Materials and methods Gingival recessions of mild (0.5–2 mm) and increased (3–7 mm) severity were simulated on stone casts and surface models were created. The outlines of the gingival margins of the mild (A) and severe recessions (B) were compared to the original gingival margins following 3D best fit superimposition through a gold standard technique (GS), which used intact adjacent structures, and the tested method (CC), which used single tooth crowns at the position of recessions, as superimposition reference. The primary outcome was the distance between the most apical point of each corresponding gingival margin along the respective tooth long axis. Results For mild recessions, the median difference of the test methods (CC_A) from the reference method (GS_A) was 0.008 mm (IQR: 0.093; range: − 0.143, 0.147). For severe recessions, the median difference of the test method (CC_B) from the reference method (GS_B) was 0.009 mm (IQR: 0.091; range: − 0.170, 0.198). The proposed method (CC) showed very high intra- and inter-operator reproducibility (median: 0.025 and 0.033 mm, respectively). Conclusions The suggested method offers highly accurate monitoring of gingival margin changes and diagnosis of gingival recessions using 3D digital dental models. The method is applicable irrespective of changes in tooth position or form, allowing for assessments over any time span. Clinical relevance The accurate detection and visualization of gingival margin changes in 3D will enhance diagnosis and patient-doctor communication.
Databáze: OpenAIRE
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