Use of Augmented Reality for Training Assistance in Laparoscopic Surgery: Scoping Literature Review.

IF 5.8 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES Journal of Medical Internet Research Pub Date : 2025-01-28 DOI:10.2196/58108
Francisco Javier Celdrán, Javier Jiménez-Ruescas, Carlos Lobato, Lucía Salazar, Juan Alberto Sánchez-Margallo, Francisco M Sánchez-Margallo, Pascual González
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Abstract

Background: Laparoscopic surgery training is a demanding process requiring technical and nontechnical skills. Surgical training has evolved from traditional approaches to the use of immersive digital technologies such as virtual, augmented, and mixed reality. These technologies are now integral to laparoscopic surgery training.

Objective: This scoping literature review aimed to analyze the current augmented reality (AR) solutions used in laparoscopic surgery training.

Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, we conducted a scoping review using 4 databases: Scopus, IEEE Xplore, PubMed, and ACM. Inclusion and exclusion criteria were applied to select relevant articles. Exclusion criteria were studies not using AR, not focused on laparoscopic surgery, not focused on training, written in a language other than English, or not providing relevant information on the topics studied. After selecting the articles, research questions (RQs) were formulated to guide the review. In total, 2 independent reviewers then extracted relevant data, and a descriptive analysis of the results was conducted.

Results: Of 246 initial records, 172 (69.9%) remained after removing duplicates. After applying the exclusion criteria, 76 articles were selected, with 25 (33%) later excluded for not meeting quality standards, leaving 51 (67%) in the final review. Among the devices analyzed (RQ 1), AR video-based devices were the most prevalent (43/51, 84%). The most common information provided by AR devices (RQ 1) focused on task execution and patient-related data, both appearing in 20% (10/51) of studies. Regarding sensorization (RQ 2), most studies (46/51, 90%) incorporated some form of sensorized environment, with computer vision being the most used technology (21/46, 46%) and the trainee the most frequently sensorized element (41/51, 80%). Regarding training setups (RQ 3), 39% (20/51) of the studies used commercial simulators, and 51% (26/51) made use of artificial models. Concerning the evaluation methods (RQ 4), objective evaluation was the most used, featured in 71% (36/51) of the studies. Regarding tasks (RQ 5), 43% (22/51) of studies focused on full surgical procedures, whereas 57% (29/51) focused on simple training tasks, with suturing being the most common among the latter (11/29, 38%).

Conclusions: This scoping review highlights the evolving role of AR technologies in laparoscopic surgery training, although the impact of optical see-through devices remains unclear due to their limited use. It underscores the potential of emerging technologies such as haptic feedback, computer vision, and eye tracking to further enhance laparoscopic skill acquisition. While most relevant articles from other databases were included, some studies may have been missed due to the specific databases and search strategies used. Moreover, the need for standardized evaluation metrics is emphasized, paving the way for future research into AR's full potential in laparoscopic skill acquisition.

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来源期刊
CiteScore
14.40
自引率
5.40%
发文量
654
审稿时长
1 months
期刊介绍: The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades. As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor. Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.
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