Evidence map›Paper›PMID 41035794›Full record

ArticleFrontiers in oral health2025

Robot-assisted autotransplantation of third molars in the maxilla: two case reports.

Yunkun Liu, Jia Song, Xiaoyu Chen, Chuyang Zhang, Yong Yang, Dan Liu, Haolin Zhou, Bingling Wu, Jian Zhang, Zhiyu Gu

Abstract readCase Reports
In one paragraph

Article in Frontiers in oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Yunkun Liu *Stomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Jia Song *Stomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Xiaoyu ChenStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Chuyang ZhangStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Yong YangStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Dan LiuStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Haolin ZhouStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Bingling WuStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Jian ZhangStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.
Zhiyu GuStomatology Hospital Affiliated to Zunyi Medical University, Zunyi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autotransplantation of teeth has attracted increasing attention due to its excellent biocompatibility and ability to preserve natural dentition. However, conventional autotransplantation of tooth techniques are highly technique-sensitive and reliant on clinician experience, limiting their predictability and broader clinical application. With the advancement of digital dentistry and surgical robotics, robot-assisted autotransplantation of teeth offers a new approach that enhances precision and consistency. In these two reports, digital intraoral scans and cone-beam computed tomography data were processed through AI-assisted segmentation, surgical path planning, and 3D printing technologies. Prior to robotic surgery, surgical guides were installed in the patient's oral cavity to perform calibration and ensure accurate alignment. During the procedure, an autonomous surgical robot was employed to prepare the recipient sites in the upper first molar regions. Following socket preparation, tooth replicas were used to simulate the transplantation process, allowing confirmation of fit and orientation before proceeding with the actual implantation. The transplantation of upper third molars was performed following a standardized digital protocol, involving one-time root canal treatment, 3 mm apicoectomy, and retrograde filling immediately after extraction. The treated teeth were then implanted into fresh extraction socket within the optimal time window, with the total duration from endodontic treatment to implantation not exceeding 15 min. The cases were followed up for three and six months, respectively, postoperative follow-ups showed favorable outcomes, including stable fixation, healthy surrounding soft tissues, and progressive bone healing as confirmed by radiographic imaging. These findings suggest that the integration of AI-based planning and robotic assistance significantly improves the predictability and clinical outcomes of autotransplantation of teeth, supporting its potential as a standardized and intelligent solution in modern dental surgery.

Indexed as

3D printingartificial intelligenceautonomous robotic surgerydental autotransplantationoral surgerytooth replica

Identifiers

PMID41035794
PMCPMC12482627

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.