Evidence map›Paper›PMID 40119363›Full record

ArticleBMC oral health2025

Development and validation of a polyfit approach for assessing alveolar bone loss using panoramic radiography.

Erkang Tian, Jiawei Hong, Zihua Tang, Ruiting Ren, Shuoshun Li, Abbas Ahmed Abdulqader, Mingshan Li, Chaoran Xue, Xianglong Han, Juan Li

Abstract readValidation Study
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Erkang Tian *State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.ORCID http://orcid.org/0009-0006-4685-1005
Jiawei Hong *State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.ORCID http://orcid.org/0009-0008-6670-7566
Zihua TangState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Ruiting RenState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Shuoshun LiState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Abbas Ahmed AbdulqaderState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Mingshan LiState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Chaoran XueState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Xianglong HanState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China. xhan@scu.edu.cn.ORCID http://orcid.org/0000-0001-7650-8204
Juan LiState Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China. lijuan@scu.edu.cn.ORCID http://orcid.org/0000-0001-8320-2406

Funding

Angelalign Scientific Research Fund SDTS21-4-01Clinical Research Project of West China Hospital of Stomatology, Sichuan University LCYJ2019-22Major Special Science and Technology Project of Sichuan Province 2022ZDZX0031National Natural Science Foundation of China 32271364
6 · The paper itself

Abstract

backgroundPanoramic radiographs (PAN) are one of the most common diagnostic tools in clinical practice. Periodontal disease, the second most prevalent oral disease, significantly impacts patients' quality of life. However, there is currently no standardized and quantitative image analysis method for periodontal diagnosis. This study aims to estimate alveolar bone loss in six sextants of the mouth using the Polyfit approach on panoramic radiography. This approach utilizes ratio and proportional measurements based on fixed anatomical points to improve the accuracy of assessing bone loss.

methodsIn this retrospective clinical study, we assessed alveolar bone loss (ABL) in 290 subjects. The subjects were divided into two groups, the resorption group (abbreviated to ABL) and non-resorption group (abbreviated to non-ABL), based on the presence of any ABL sextants. Each tooth was manually marked with reference anatomical landmarks using Anaconda-Labelme 5.2.1 software. To evaluate the proportionate bone resorption for each tooth, we employed the PAN-POL model based on the polyfit function to quantify bone loss across six dental sextants and the entire dental arch. For the reliability of measurements, Cone Beam Computed Tomography (CBCT) data from 30 patients were selected. Measurements were conducted in Mimics 21.0 and compared with the model's results to validate the ABL assessment. An independent sample t-test or the intergroup rank-sum test was used to evaluate the difference between resorption data from both classification methods, and ABL and non-ABL groups in each classification. Pearson's correlation analysis and linear regression analysis were used to test and verify the correlation between CBCT and panoramic radiography. P values of > 0.05 were considered not statistically significant.

resultsThe PAN-POL model demonstrated effective differentiation between resorption and non-resorption groups, and the groups based on two classification achieving statistical significance (P < 0.05), and the ratio results were consistent with those from CBCT (P > 0.05), indicating no significant difference. The Intraclass Correlation Coefficient (ICC) results for reliability testing among two experts for both PAN and CBCT were steadily 0.83 ± 0.06 and 0.93 ± 0.06 (ICC>0.75).

conclusionIn this study, the PAN-POL model accurately measured ABL in panoramic images by incorporating standard anatomical landmarks. This model aids in Periodontal Screening and Recording, serving as a novel, valuable and intuitive tool for initial periodontal diagnosis.

Indexed as

Alveolar Bone LossRadiography, PanoramicAdultAgedCone-Beam Computed TomographyFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesAlveolar bone lossDiagnostic imagingPanoramic radiographyPeriodontitis

Identifiers

PMID40119363
PMCPMC11929333

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