Histopathological patterns of periapical lesions in root canal treated teeth: A systematic review
Bibliographic record
Abstract
INTRODUCTION. Periapical lesions are common sequelae of pulpal necrosis and endodontic infections, presenting significant diagnostic challenges in clinical practice. Accurate histopathological characterization is essential for appropriate treatment planning and prognostic assessment. AIM. To systematically evaluate and summarize the histopathological features, prevalence patterns, and diagnostic concordance of periapical lesions in root canal treated teeth. MATERIALS AND METHODS. A systematic review was conducted following PRISMA 2020 guidelines. Electronic databases including PubMed, Scopus, Web of Science, and Google Scholar were searched for studies published between 2000–2024. Inclusion criteria encompassed histopathological studies of periapical lesions from root canal treated teeth. Quality assessment was performed using the Newcastle-Ottawa Scale and QUADAS-2 tools. RESULTS. Twelve studies involving 1,847 periapical lesion specimens were included. Histopathological analysis revealed periapical granulomas as the most prevalent lesions (50–84.2%), followed by radicular cysts (15–42%) and periapical abscesses (5–35%). Clinical-histopathological concordance was poor, with overall agreement ranging from 51.4–55.8% (Cohen’s kappa κ = 0.059). Larger lesions (> 200 mm²) showed higher prevalence of radicular cysts (92–100%). Periapical scars represented 1–6% of cases. DISCUSSION. Significant discrepancies between clinical and histopathological diagnoses highlight limitations of radiographic assessment alone. Lesion size, location, and duration influence histopathological patterns. The predominance of granulomatous tissue suggests ongoing inflammatory processes despite endodontic intervention. CONCLUSIONS. Histopathological examination remains the gold standard for definitive diagnosis of periapical lesions. The poor clinical-histopathological concordance emphasizes the necessity of biopsy examination for accurate diagnosis and appropriate treatment planning in endodontic practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".