Evidence map›Paper›PMID 39130491›Full record

ArticleFrontiers in oral health2024

Precision and accuracy of craniofacial growth and orthodontic treatment evaluation by digital image correlation: a prospective cohort study.

Jan Christian Danz, Simone Stöckli, Christian Per Rank

Abstract read
In one paragraph

Article in Frontiers in oral health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

3 authors.

Jan Christian DanzDepartment of Orthodontics and Dentofacial Orthopedics, School of Dental Medicine ZMK, University of Bern, Bern, Switzerland.
Simone StöckliDepartment of Orthodontics and Dentofacial Orthopedics, School of Dental Medicine ZMK, University of Bern, Bern, Switzerland.
Christian Per RankOrthodontics and Dentofacial Orthopedics, Odense, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A precise and accurate method for structural superimposition is essential for analyzing dentofacial growth and orthodontic or surgical treatment in longitudinal studies. The errors associated with different superimposition methods have not yet been assessed in high-quality studies. Objectives: This study aimed to assess the precision and accuracy of digital image correlation (DIC) for structural superimposition. Methods: Two cephalometric images from 30 consecutive patients were superimposed using three DIC methods, each measured twice by two examiners. Areas including the contours of the sella, the whole cranial base (CB), and Walker's point and lamina cribrosa (WPLC) were compared using a random coefficient model. Inter-rater and intra-rater errors were assessed for each method. Results: WPLC provided the best precision for image rotation and cephalometric landmarks. Systematic bias was observed between the WPLC and CB methods for image rotation and most landmarks. The intra-rater error in image rotation during DIC was strongly correlated with the intra-rater error in the landmarks of the anterior nasal spine, articulare, and pogonion. Conclusion: Structural superimposition using DIC with WPLC is a precise method for analyzing dentofacial growth and orthodontic or surgical treatment. Moreover, the best method is the measurement of longitudinal dental and craniofacial changes on structurally superimposed cephalometric radiographs with WPLC and a reference grid including the true vertical and horizontal lines from Walker's point.

Indexed as

digital image correlationgrowth and developmentmaxillofacial surgeryorthodontic treatmentstructural superimposition

Identifiers

PMID39130491
PMCPMC11310159

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.