JMIR Publications

ABSTRACT

Background:

Training in laparoscopic surgery is a long and demanding process that requires extensive theoretical knowledge, along with technical and non-technical skills. Learning models in surgical training have rapidly evolved from traditional approaches based on the "see one, do one, teach one" philosophy to more sophisticated surgical simulators. The emergence of immersive digital technologies, such as virtual, augmented, and mixed reality, has led to a paradigm shift in the field of surgical training. The use of these technologies is becoming an important part of the training process in laparoscopic surgery.

Objective:

This systematic review aims to analyze the current augmented reality (AR) solutions used as training support in laparoscopic surgery. We will also review the training simulators, sensorization systems and display devices used for this purpose. Likewise, we will analyze the methods of assessing trainees’ skills, the main training tasks and procedures, and feedback used in these training systems. All this will give us a more detailed view of the current state of AR in the field of laparoscopic surgery training.

Methods:

PRISMA methodology was used to conduct the systematic review. A search was carried out in 4 scientific databases (Scopus, IEEE Xplore, PubMed and ACM). After eliminating duplicates results, a peer review process was conducted to make the final selection of articles based on our exclusion criteria. The following information was extracted from the selected articles: year of publication; abstract, modality of teaching; type of device used for AR; type of training information provided to the learner; sensorization technology; type of AR simulator (commercial or prototype); type of evaluation (objective or subjective); training tasks/procedures performed; specialty of laparoscopic surgery. This information was collected in an attempt to answer the following research questions: What type of devices and feedback are used for AR-based laparoscopic training? (RQ1); what type of sensorization is used for AR-based laparoscopic training? (RQ2); what type of simulator/setup are used for AR-based laparoscopic training? (RQ3); what type of evaluation is used to assess skill acquisition in AR-based laparoscopic training? (RQ4); and what type of surgical tasks and/or procedures are used in AR-based laparoscopic training? (RQ5).

Results:

A total of 246 records were obtained. After eliminating duplicate records, 172 remained. A total of 76 articles were left after applying the exclusion criteria. Twenty-five records that did not meet the quality criteria were eliminated, so that 51 articles were finally included in this review. We analyzed these articles based on each of the purposed research questions, generating different categories and classifications. For each research question all articles were properly classified according to these categories and classifications.

Conclusions:

This systematic review highlights the evolving landscape of AR technologies in the context of laparoscopic surgery training. The emergence of optical see through devices, the benefits of haptic feedback, computer vision and AI tools, and eye-tracking technology underscore the dynamic nature of this field. Moreover, the need for standardized objective evaluation metrics is emphasized, paving the way for future investigations into the full potential of AR in enhancing laparoscopic skill acquisition.