Evidence map›Paper›PMID 39856516›Full record

ArticleBeijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences2025

[Evaluation of the accuracy of three-dimensional data acquisition from liquid- interference surfaces assisted by a scanner head with a compressed airflow system].

Xinkai Xu, Jianjiang Zhao, Sukun Tian, Zhongning Liu, Xiaoyi Zhao, Xiaobo Zhao, Tengfei Jiang, Xiaojun Chen, Chao Ma, Yuchun Sun

Abstract readEnglish Abstract
PubMed Full text at PMC
In one paragraph

Article in Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xinkai XuInstitute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.
Jianjiang ZhaoCenter of Digital Dentistry, Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & NHC Key Laboratory of Digital Stomatology & Beijing Key Laboratory of Digital Stomatology & Key Laboratory of Digital Stomatology, Chinese Academy of Medical Sciences, Beijing 100081, China.
Sukun TianCenter of Digital Dentistry, Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & NHC Key Laboratory of Digital Stomatology & Beijing Key Laboratory of Digital Stomatology & Key Laboratory of Digital Stomatology, Chinese Academy of Medical Sciences, Beijing 100081, China.
Zhongning LiuCenter of Digital Dentistry, Department of Prosthodontics, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & NHC Key Laboratory of Digital Stomatology & Beijing Key Laboratory of Digital Stomatology & Key Laboratory of Digital Stomatology, Chinese Academy of Medical Sciences, Beijing 100081, China.
Xiaoyi ZhaoDepartment of General Dentistry, Peking University School and Hospital of Stomatology, Beijing 100081, China.
Xiaobo ZhaoShining 3D, Hangzhou 311258, China.
Tengfei JiangShining 3D, Hangzhou 311258, China.
Xiaojun ChenShining 3D, Hangzhou 311258, China.
Chao MaShining 3D, Hangzhou 311258, China.
Yuchun SunInstitute of Medical Technology, Peking University Health Science Center, Beijing 100191, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo quantitatively evaluate the accuracy of data obtained from liquid-interference surfaces using an intraoral 3D scanner (IOS) integrated with a compressed airflow system, so as to provide clinical proof of accuracy for the application of the compressed airflow system-based scanning head in improving data quality on liquid-interference surfaces.

methodsThe study selected a standard model as the scanning object, adhering to the "YY/T 1818-2022 Dental Science Intraoral Digital Impression Scanner" guidelines, a standard that defined parameters for intraoral scanning. To establish a baseline for accuracy, the ATOS Q 12M scanner, known for its high precision, was used to generate true reference values. These true values served as the benchmark for evaluating the IOS performance. Building on the design of an existing scanner, a new scanning head was developed to integrate with a compressed airflow system. This new design aimed to help the IOS capture high-precision data on surfaces where liquid-interference, such as saliva, might otherwise degrade scanning accuracy. The traditional scanning method, without airflow assistance, was employed as a control group for comparison. The study included five groups in total, one control group and four experimental groups, to investigate the effects of scanning lens obstruction, airflow presence, liquid media, and the use of the new scanning head on scanning process and accuracy. Each group underwent 15 scans, generating ample data for a robust statistical comparison. By evaluating trueness and precision in each group, the study assessed the impact of the compressed airflow system on the accuracy of IOS data collected from liquid-interference surfaces. Additionally, we selected Elite and Primescan scanners as references for numerical accuracy values.

resultsThe scanning accuracy on liquid-interference surfaces was significantly reduced in terms of both trueness and precision [Trueness: 18.5 (6.5)

conclusionThe scanning head based on the compressed airflow system can assist in improving the accuracy of data obtained from liquid-interference surfaces by the IOS.

Indexed as

Dental Impression TechniqueImaging, Three-DimensionalHumansAccuracyCompressed airflow systemIntraoral 3D scannersLiquid-interference surfaces

Identifiers

PMID39856516
PMCPMC11759805

What OpenQuestion holds

Textmetadata
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.