Suppr超能文献

低收入国家外科护理全球虚拟现实病例会议中的人工智能增强3D模型:探索性研究

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

作者信息

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

机构信息

Faculty of Medicine, University of Bonn, Bonn, Germany.

Bonn Surgical Technology Centre (BOSTER), University Hospital Bonn, Joseph-Schumpert-Allee 1, Bonn, 53227, Germany, +491752721843.

出版信息

JMIR Form Res. 2025 Aug 18;9:e69300. doi: 10.2196/69300.

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.

摘要

背景

全球约有50亿人无法获得足够的外科护理,主要集中在全球南方地区。特别是在危机地区和战区,远程医疗应用可以改善医疗服务。本研究探讨了在乌干达资源匮乏的情况下,使用人工智能(AI)增强的3D成像和扩展现实(XR)技术进行洲际外科病例研讨会的可行性。我们的试点研究旨在评估这些技术在解决外科资源短缺和多边知识交流方面的价值。

目的

本研究旨在确定在沉浸式空间XR场景中使用新的AI增强图像建模技术,以在资源有限的乌干达协作远程评估重建患者病例的可行性。

方法

在乌干达拉穆医疗中心的一个外科营地内,使用智能手机应用程序创建患者病情的3D模型。数字模型由现场拍摄的照片生成,并处理成3D格式,以便在虚拟病例研讨会上可视化。在此过程中,来自乌干达和德国的外科医生使用虚拟现实(VR)头盔共同讨论病例策略,同时在每个数字患者模型上标记手术方法。

结果

该研究纳入了15名需要进行重建手术的患者,病情各异。XR技术的使用促进了手术策略的详细可视化和讨论。该过程效率高,每个病例的数据采集和模型创建总共不到8分钟,且资源效率高,外科医生报告称智能手机衍生模型的质量足够。在VR病例处理过程中发现了宝贵的用户体验和精确交互,突显了其在资源有限环境中改善手术规划和患者护理的潜力。

结论

研究结果表明,AI增强的3D成像和沉浸式虚拟通信平台是综合外科病例评估的宝贵工具。所使用的消费级解决方案的成本效益对于资源匮乏的环境尤其有益。虽然该研究证明了这种方法的可行性,但需要进一步研究以探索这些技术在全球健康领域更广泛的应用和影响。该研究强调了XR在加强培训和提高手术精度方面的潜力,有助于在服务不足地区实现更好的医疗保健结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/532c/12360718/d91eb67d7115/formative-v9-e69300-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验