Evidence map›Paper›PMID 40825229›Full record

ArticleJMIR formative research2025

AI-Enhanced 3D Models in Global Virtual Reality Case Conferences for Surgical Care in a Low-Income Country: Exploratory Study.

Miriam Obst, Jan Arensmeyer, Henrik Bonsmann, Andreas Kolbinger, Joel Kigenyi, Francis Oneka, Benard Owere, Joachim Schmidt, Philipp Feodorovici, Jan Wynands

Abstract read
In one paragraph

Article in JMIR formative research, 2025. 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. Review
  2. Article
  3. Who will be our adult congenital heart disease patient tomorrow?European heart journal supplements : journal of the European Society of Cardiology · 2026
    Article
  4. 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

10 authors.

Miriam Obst *Faculty of Medicine, University of Bonn, Bonn, Germany.ORCID 0009-0004-2328-3231
Jan Arensmeyer *Bonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.ORCID 0000-0003-0705-2973
Henrik BonsmannBonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.ORCID 0009-0005-6816-6650
Andreas KolbingerMedical Practice of Reconstructive and Aesthetic Surgery Pfaffenhofen, Pfaffenhofen, Germany.ORCID 0009-0009-3209-7808
Joel KigenyiLamu Medical Centre for Reconstructive and Global Surgery, Jinja, Uganda.ORCID 0009-0009-0736-2083
Francis OnekaLamu Medical Centre for Reconstructive and Global Surgery, Jinja, Uganda.ORCID 0009-0005-0376-8300
Benard OwereLamu Medical Centre for Reconstructive and Global Surgery, Jinja, Uganda.ORCID 0009-0004-8754-0225
Joachim SchmidtBonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.ORCID 0009-0000-3159-652X
Philipp Feodorovici *Bonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.ORCID 0009-0000-3940-0501
Jan Wynands *Bonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.ORCID 0009-0004-3852-0084

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Approximately 5 billion people worldwide lack adequate access to surgical care, primarily in the Global South. Especially in crisis regions and war zones, telemedical applications may enhance health services. This study explores the feasibility of using artificial intelligence (AI)-enhanced 3D imaging and extended reality (XR) technologies for intercontinental surgical case conferences in a low-resource scenario in Uganda. Our pilot study aims to assess the value of these technologies to address the lack of surgical resources and multilateral knowledge exchange. Objective: This study intends to determine the feasibility of using new AI-enhanced image modeling technology within an immersive spatial XR scenario to collaboratively and remotely assess reconstructive patient cases in the resource-limited country of Uganda. Methods: Within a surgical camp at Lamu Medical Centre, Uganda, 3D models of patients' conditions were created using a smartphone app. Digital models were generated from photographs taken on-site and processed into 3D formats to be visualized in virtual case conferences. Here, surgeons from Uganda and Germany used virtual reality (VR) headsets to collaboratively discuss case strategies while marking surgical approaches on each digital patient model. Results: The study included 15 patients requiring reconstructive surgery, with a diverse range of conditions. The use of XR technology facilitated detailed visualization and discussion of surgical strategies. The process was time-efficient, with a total of under 8 minutes per case for data acquisition and model creation, and resource-efficient with surgeons reporting sufficient quality of smartphone-derived models. Valuable user experience and precise interaction during the VR case processing were found, underlining its potential to improve surgical planning and patient care in resource-limited settings. Conclusions: The findings indicate that AI-enhanced 3D imaging and immersive virtual communication platforms are valuable tools for integrative surgical case assessments. The cost-effectiveness of the used consumer solutions should be especially beneficial for low-resource environments. While the study demonstrates the feasibility of this approach, further research is needed to explore a broader application and impact of these technologies in global health. The study highlights the potential of XR to enhance training and surgical precision, contributing to better health care outcomes in underserved regions.

Indexed as

Artificial IntelligenceImaging, Three-DimensionalVirtual RealityAdultDeveloping CountriesFeasibility StudiesFemaleHumansMalePilot ProjectsTelemedicineUganda3D scanningartificial intelligenceextended realityglobal surgerymetaversereconstructive surgeryspatial computingvirtual reality

Identifiers

PMID40825229
PMCPMC12360718

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.