Evidence map›Paper›PMID 38638496›Full record

ArticleHealthcare technology letters

Mixed reality guided root canal therapy.

Fangjie Li, Qingying Gao, Nengyu Wang, Nicholas Greene, Tianyu Song, Omid Dianat, Ehsan Azimi

Open access · goldAbstract read
In one paragraph

Article in Healthcare technology letters. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% 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, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Guided Endodontics-Potential and Limitations.Australian dental journal · 2025
    Review
  4. Review
  5. Article
  6. Review
  7. Mixed reality guided root canal therapy.Healthcare technology letters
    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 at 3 institutions in 2 countries.

Fangjie LiDepartment of Biomedical Engineering Johns Hopkins University Baltimore Maryland USA.
Qingying GaoDepartment of Computer Science Johns Hopkins University Baltimore Maryland USA.
Nengyu WangDepartment of Computer Science Johns Hopkins University Baltimore Maryland USA.
Nicholas GreeneDepartment of Computer Science Johns Hopkins University Baltimore Maryland USA.
Tianyu SongChair for Computer Aided Medical Procedures Technical University of Munich Munich Germany.ORCID https://orcid.org/0000-0002-8428-9651
Omid DianatSchool of Dentistry University of Maryland Baltimore Maryland USA.
Ehsan AzimiDepartment of Computer Science Johns Hopkins University Baltimore Maryland USA.ORCID https://orcid.org/0000-0003-3433-7958
Johns Hopkins University · USTechnical University of Munich · DEUniversity of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Root canal therapy (RCT) is a widely performed procedure in dentistry, with over 25 million individuals undergoing it annually. This procedure is carried out to address inflammation or infection within the root canal system of affected teeth. However, accurately aligning CT scan information with the patient's tooth has posed challenges, leading to errors in tool positioning and potential negative outcomes. To overcome these challenges, a mixed reality application is developed using an optical see-through head-mounted display (OST-HMD). The application incorporates visual cues, an augmented mirror, and dynamically updated multi-view CT slices to address depth perception issues and achieve accurate tooth localization, comprehensive canal exploration, and prevention of perforation during RCT. Through the preliminary experimental assessment, significant improvements in the accuracy of the procedure are observed. Specifically, with the system the accuracy in position was improved from 1.4 to 0.4 mm (more than a 70% gain) using an Optical Tracker (NDI) and from 2.8 to 2.4 mm using an HMD, thereby achieving submillimeter accuracy with NDI. 6 participants were enrolled in the user study. The result of the study suggests that the average displacement on the crown plane of 1.27 ± 0.83 cm, an average depth error of 0.90 ± 0.72 cm and an average angular deviation of 1.83 ± 0.83°. Our error analysis further highlights the impact of HMD spatial localization and head motion on the registration and calibration process. Through seamless integration of CT image information with the patient's tooth, our mixed reality application assists dentists in achieving precise tool placement. This advancement in technology has the potential to elevate the quality of root canal procedures, ensuring better accuracy and enhancing overall treatment outcomes.

Indexed as

augmented realitydentistrytracking

Identifiers

PMID38638496
PMCPMC11022218
OpenAlexW4393866092

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.