Clinical oral investigations · 2026
A novel classification of periodontal phenotype integrating hard and soft tissue parameters using data-driven clustering.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Al-Sosowa Abeer A, Abdulghani Ehab A, Dai Anna, Huang Jia-Ping, Meng Wang, Zhu Jiajun, Ding Pei-Hui
Аннотация
OBJECTIVE: To combine quantitative measures of gingival thickness (GT), keratinized tissue width (KTW), and alveolar buccal bone thickness (ABT) for developing a novel classification of periodontal phenotype through a clustering analysis, using two digital images.
MATERIALS AND METHODS: This cross-sectional study comprised 180 subjects with a total of 1080 maxillary anterior teeth. GT and ABT were assessed utilizing superimposed Cone Beam Computed Tomography (CBCT) and intraoral scan data, while KTW was obtained from intraoral images employing a correction factor. Hierarchical cluster analysis (HCA) was conducted to discern phenotypic categories. Cutoff values for GT, KTW, and ABT were derived from cluster boundaries to provide a clinically applicable scoring system.
RESULTS: Cluster analysis identified four statistically significant phenotypic groupings (p < 0.001). Only 48.9% of instances accounted for conventional "thin" or "thick" phenotypes, while 51.1% exhibited mixed characteristics. Cutoff values were established as GT = 0.85 mm, KTW = 3.0 mm, and ABT = 1.0 mm. Based on these cutoffs, a scoring system (0-3) was developed to classify individuals as fully thin, majority-thin (gingival thin/ bone thick)" and "majority-thick (gingival thick/ bone thin), or fully thick. This system demonstrated good internal consistency, with moderate to high coefficients of determination (R²) across parameters.
CONCLUSION: This study presents a comprehensive, data-driven classification of periodontal phenotype using quantitative evaluations of GT, KTW, and ABT, providing an innovative viewpoint on phenotype-based diagnostics. The proposed system offers a clinically relevant framework for phenotype-based diagnostics, risk evaluation, and individualized treatment planning.
CLINICAL RELEVANCE: By combining soft (GT, KTW) and hard (ABT) tissue parameters with 3D imaging and clustering analysis, this classification provides clinicians with a practical and quantitative tool for assessing periodontal phenotype, thereby supporting accurate diagnosis and evidence-based decision-making across multiple dental disciplines.
MATERIALS AND METHODS: This cross-sectional study comprised 180 subjects with a total of 1080 maxillary anterior teeth. GT and ABT were assessed utilizing superimposed Cone Beam Computed Tomography (CBCT) and intraoral scan data, while KTW was obtained from intraoral images employing a correction factor. Hierarchical cluster analysis (HCA) was conducted to discern phenotypic categories. Cutoff values for GT, KTW, and ABT were derived from cluster boundaries to provide a clinically applicable scoring system.
RESULTS: Cluster analysis identified four statistically significant phenotypic groupings (p < 0.001). Only 48.9% of instances accounted for conventional "thin" or "thick" phenotypes, while 51.1% exhibited mixed characteristics. Cutoff values were established as GT = 0.85 mm, KTW = 3.0 mm, and ABT = 1.0 mm. Based on these cutoffs, a scoring system (0-3) was developed to classify individuals as fully thin, majority-thin (gingival thin/ bone thick)" and "majority-thick (gingival thick/ bone thin), or fully thick. This system demonstrated good internal consistency, with moderate to high coefficients of determination (R²) across parameters.
CONCLUSION: This study presents a comprehensive, data-driven classification of periodontal phenotype using quantitative evaluations of GT, KTW, and ABT, providing an innovative viewpoint on phenotype-based diagnostics. The proposed system offers a clinically relevant framework for phenotype-based diagnostics, risk evaluation, and individualized treatment planning.
CLINICAL RELEVANCE: By combining soft (GT, KTW) and hard (ABT) tissue parameters with 3D imaging and clustering analysis, this classification provides clinicians with a practical and quantitative tool for assessing periodontal phenotype, thereby supporting accurate diagnosis and evidence-based decision-making across multiple dental disciplines.