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Ann Surg Treat Res. 2018 Dec;95(6):297-302. English. Original Article. https://doi.org/10.4174/astr.2018.95.6.297
Lee D , Kong HJ , Kim D , Yi JW , Chai YJ , Lee KE , Kim HC .
Interdisciplinary Program, Bioengineering Major, Graduate School, Seoul National University, Seoul, Korea.
Department of Biomedical Engineering, Chungnam National University Hospital, Chungnam National University College of Medicine, Daejeon, Korea.
Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea.
Department of Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Department of Surgery, Seoul Metropolitan Government - Seoul National University Boramae Medical Center, Seoul, Korea. kevinjoon@naver.com
Department of Biomedical Engineering, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Institute of Medical & Biological Engineering, Medical Research Center, Seoul National University College of Medicine, Seoul, Korea.
Abstract

Purpose

Increased robotic surgery is attended by increased reports of complications, largely due to limited operative view and lack of tactile sense. These kinds of obstacles, which seldom occur in open surgery, are challenging for beginner surgeons. To enhance robotic surgery safety, we created an augmented reality (AR) model of the organs around the thyroid glands, and tested the AR model applicability in robotic thyroidectomy.

Methods

We created AR images of the thyroid gland, common carotid arteries, trachea, and esophagus using preoperative CT images of a thyroid carcinoma patient. For a preliminary test, we overlaid the AR images on a 3-dimensional printed model at five different angles and evaluated its accuracy using Dice similarity coefficient. We then overlaid the AR images on the real-time operative images during robotic thyroidectomy.

Results

The Dice similarity coefficients ranged from 0.984 to 0.9908, and the mean of the five different angles was 0.987. During the entire process of robotic thyroidectomy, the AR images were successfully overlaid on the real-time operative images using manual registration.

Conclusion

We successfully demonstrated the use of AR on the operative field during robotic thyroidectomy. Although there are currently limitations, the use of AR in robotic surgery will become more practical as the technology advances and may contribute to the enhancement of surgical safety.

Copyright © 2019. Korean Association of Medical Journal Editors.