Evidence map›Paper›PMID 40868305›Full record

ArticleBioengineering (Basel, Switzerland)2025

Evaluating Accuracy of Smartphone Facial Scanning System with Cone-Beam Computed Tomography Images.

Konstantinos Megkousidis, Elie Amm, Melih Motro

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  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

3 authors.

Konstantinos MegkousidisDepartment of Orthodontics and Dentofacial Orthopedics, Henry Goldman School of Dental Medicine, Boston University, Boston, MA 02118, USA.
Elie AmmDepartment of Orthodontics and Dentofacial Orthopedics, Henry Goldman School of Dental Medicine, Boston University, Boston, MA 02118, USA.ORCID 0000-0003-1452-6778
Melih MotroDepartment of Orthodontics and Dentofacial Orthopedics, Henry Goldman School of Dental Medicine, Boston University, Boston, MA 02118, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesFacial soft tissue imaging is crucial in orthodontic treatment planning, and the structured light scanning technology found in the latest iPhone models constitutes a promising method. Currently, studies which evaluate the accuracy of smartphone-based three-dimensional (3D) facial scanners are scarce. This study compares smartphone scans with cone-beam computed tomography (CBCT) images. MATERIALS AND

methodsThree-dimensional images of 23 screened patients were captured with the camera of an iPhone 13 Pro Max and processed with the Scandy Pro application; CBCT scans were also taken as a standard of care. After establishing unique image pairs of the same patient, linear and angular measurements were compared between the images to assess the scanner's two-dimensional trueness. Following the co-registration of the virtual models, a heat map was generated, and root mean square (RMS) deviations were calculated for quantitative assessment of 3D trueness. Precision was determined by comparing consecutive 3D facial scans of five participants, while intraobserver reliability was assessed by repeating measurements on five subjects after a two-week interval.

resultsThis study found no significant difference in soft tissue measurements between smartphone and CBCT images (

conclusionsSmartphone facial scanners offer an accurate and reliable alternative to stereophotogrammetry systems, though clinicians should exercise caution when examining the lateral sections of those images due to inherent inaccuracies.

Indexed as

cone-beam computed tomographyfacial scanningstereophotogrammetrythree-dimensional imaging

Identifiers

PMID40868305
PMCPMC12383923

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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.