Evaluation of Alveolar Bone Loss With ECR Using Cone-Beam Computed Tomography: A Cross-Sectional Study.

Authors

Ana Paula de Medeiros Silva, Thalles Gabriel Germano Lima, Ana Beatriz Leitão de Albuquerque Wanderley, Monikelly do Carmo Chagas Nascimento, Daniela Siqueira Lopes

Published in

International journal of dentistry. Volume 2026. Pages 5186337. Epub Sep 12, 2026.

Abstract

Alveolar bone loss (ABL) and external cervical resorption (ECR) are destructive processes that can coexist and compromise periodontal prognosis. Cone-beam computed tomography (CBCT), enables assessment of resorption severity and bone loss patterns, overcoming the limitations of two-dimensional radiography. This study aimed to evaluate ABL and its correlation with ECR using CBCT. This analytical, cross-sectional, observational study used images to database spanning January 2019 to April 2025, acquired with a CBCT scanner. A total of 9208 examinations were screened. After applying the inclusion criteria, 64 patients were enrolled, comprising 75 teeth diagnosed with ECR. Sociodemographic and clinical data, ECR characteristics, and ABL patterns and classification were analyzed. The findings demonstrated a statistically significant correlation between ABL and ECR according to tooth groups, with stronger associations observed in premolars and molars (10.7%), subcrestal lesion height (41.3%), and circumferential distribution 90° to 180° (44.0%). ABL was associated with age group and lesion circumferential distribution (p  < 0.05). The horizontal pattern of bone loss was the most prevalent (54.7%), with significant associations between severity and age group (p = 0.022) and lesion height (p = 0.007). An association was also observed between lesion height and periodontal condition (p = 0.043). In conclusion, ECR performed a significant correlation with ABL in the studied population (p  < 0.05). Three-dimensional characterization of ECR lesions and their relationship with bone loss patterns and periodontal status underscores the critical role of imaging in the early detection of potentially progressive lesions.

PMID:
42732374
Bibliographic data and abstract were imported from PubMed on 13 Sep 2026.

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