Evidence map›Paper›PMID 38729983›Full record

ArticleScientific reports2024

A three-dimensional algorithm for precise measurement of human auricle parameters.

Yangyang Lin, Johannes G G Dobbe, Nadia Lachkar, Elsa M Ronde, Theo H Smit, Corstiaan C Breugem, Geert J Streekstra

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. An Overview of the Currently Used Congenital Auricular Anomalies (CAA) Classifications for Surgical Reconstruction: A Scoping Review.The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association · 2026
    Article
  3. Observational
  4. 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

7 authors.

Yangyang LinDepartment of Plastic, Reconstructive and Hand Surgery, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
Johannes G G DobbeDepartment of Biomedical Engineering and Physics, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
Nadia LachkarDepartment of Plastic, Reconstructive and Hand Surgery, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
Elsa M RondeDepartment of Plastic, Reconstructive and Hand Surgery, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
Theo H SmitDepartment of Orthopedic Surgery and Sports Medicine, Amsterdam Movement Sciences, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Corstiaan C BreugemDepartment of Plastic, Reconstructive and Hand Surgery, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands.
Geert J StreekstraDepartment of Biomedical Engineering and Physics, Amsterdam UMC Location University of Amsterdam, Amsterdam, The Netherlands. g.j.streekstra@amsterdamumc.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measurement of auricle parameters for planning and post-operative evaluation presents substantial challenges due to the complex 3D structure of the human auricle. Traditional measurement methods rely on manual techniques, resulting in limited precision. This study introduces a novel automated surface-based three-dimensional measurement method for quantifying human auricle parameters. The method was applied to virtual auricles reconstructed from Computed Tomography (CT) scans of a cadaver head and subsequent measurement of important clinically relevant aesthetical auricular parameters (length, width, protrusion, position, auriculocephalic angle, and inclination angle). Reference measurements were done manually (using a caliper and using a 3D landmarking method) and measurement precision was compared to the automated method. The CT scans were performed using both a contemporary high-end and a low-end CT scanner. Scans were conducted at a standard scanning dose, and at half the dose. The automatic method demonstrated significantly higher precision in measuring auricle parameters compared to manual methods. Compared to traditional manual measurements, precision improved for auricle length (9×), width (5×), protrusion (5×), Auriculocephalic Angle (5-54×) and posteroanterior position (23×). Concerning parameters without comparison with a manual method, the precision level of supero-inferior position was 0.489 mm; and the precisions of the inclination angle measurements were 1.365 mm and 0.237 mm for the two automated methods investigated. Improved precision of measuring auricle parameters was associated with using the high-end scanner. A higher dose was only associated with a higher precision for the left auricle length. The findings of this study emphasize the advantage of automated surface-based auricle measurements, showcasing improved precision compared to traditional methods. This novel algorithm has the potential to enhance auricle reconstruction and other applications in plastic surgery, offering a promising avenue for future research and clinical application.

Indexed as

AlgorithmsEar AuricleImaging, Three-DimensionalTomography, X-Ray ComputedCadaverHumansMale3D Image analysisAuricle parametersCT-imagingObjective measurementPrecision

Identifiers

PMID38729983
PMCPMC11087560

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.