Evidence map›Paper›PMID 33880282›Full record

ArticleCureus2021

Mobile Application for Scoliosis Screening Using a Standard 2D Digital Camera.

Tsutomu Akazawa, Yoshiaki Torii, Jun Ueno, Asako Saito, Hisateru Niki

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 19% of its field
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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Cobb angle estimation without X-ray using angle of trunk rotation and characteristics of unpredictable cases.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Scoliosis Management through Apps and Software Tools.International journal of environmental research and public health · 2023
    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

5 authors at 1 institution in 1 country.

Tsutomu AkazawaDepartment of Orthopaedic Surgery, St. Marianna University School of Medicine, Kawasaki, JPN.
Yoshiaki ToriiDepartment of Orthopaedic Surgery, St. Marianna University School of Medicine, Kawasaki, JPN.
Jun UenoDepartment of Orthopaedic Surgery, St. Marianna University School of Medicine, Kawasaki, JPN.
Asako SaitoDepartment of Orthopaedic Surgery, St. Marianna University School of Medicine, Kawasaki, JPN.
Hisateru NikiDepartment of Orthopaedic Surgery, St. Marianna University School of Medicine, Kawasaki, JPN.
St. Marianna University School of Medicine · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several scoliosis detection systems, using three-dimensional (3D) cameras or sensors, have been developed in recent years. Because these systems require specific 3D digital cameras or sensors, and the equipment is expensive, they are rarely used in many countries and regions. The development of a scoliosis screening system that uses standard two-dimensional (2D) digital cameras that come with tablet personal computers (PCs) and smartphones will facilitate the efforts made to detect scoliosis patients on a global scale. The aim of this technical note was to report on a mobile application for scoliosis screening that uses a standard 2D digital camera. The subjects were patients aged 10 years or older who visited our outpatient clinic for scoliosis or suspected scoliosis and underwent whole-spine radiography. Photographs of subjects were obtained using a standard 2D digital camera connected to a tablet PC. For analysis, we used the simplified scoliosis diagnosis support application (Cobb First, Its Corporation, Kawasaki, Japan) which operates on Windows 10 operating system (OS). When an image was imported into the application, it was displayed within a grid. The grid consisted of four columns and 40 rows and was divided into 160 areas. Each image was converted into binarized image data by demarcating skin and background color. The image of the subject was displayed as a black subject on a white background. Two types of conditions were presented to process differences in the environment versus skin color. A binarized image with a clear outline was selected. The determination was displayed as a percentage of the black area in each grid. In each row of the grid, the left and right sides of the black area were compared, and the part with the larger area with respect to the opposite side was colored and displayed. Depending on the ratio of the difference, it was possible to display green, yellow, and red. If this mobile application is available for clinical use, it has the potential to improve the accuracy of screening by physicians and nurses. Furthermore, it may also be used globally to check for possible evidence of scoliosis at home to facilitate the early detection of patients who require a medical checkup for scoliosis. Although it is essential to perform a radiographic examination for the definitive diagnosis of scoliosis, our future goal is to limit radiation exposure and replace a radiologic method with one based on a tablet PC or smartphone. A mobile application using a standard 2D digital camera may improve the accuracy of screening scoliosis by physicians and may have global application in home environments.

Indexed as

scoliosis screening

Identifiers

PMID33880282
PMCPMC8051536
OpenAlexW3139000106

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.