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Wang B, Yu JF, Ao W, Wang J, Guo XY, Li MY, Huang WY, Zhou CP, Yan SY, Zhang LY, Wang SS, Cai SJ, Lin SY, Zhao WX. Optimizing robotic thyroid surgery: lessons learned from an retrospective analysis of 104 cases. Front Endocrinol (Lausanne) 2024; 15:1337322. [PMID: 38362277 PMCID: PMC10867960 DOI: 10.3389/fendo.2024.1337322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 01/15/2024] [Indexed: 02/17/2024] Open
Abstract
Background Robotic assistance in thyroidectomy is a developing field that promises enhanced surgical precision and improved patient outcomes. This study investigates the impact of the da Vinci Surgical System on operative efficiency, learning curve, and postoperative outcomes in thyroid surgery. Methods We conducted a retrospective cohort study of 104 patients who underwent robotic thyroidectomy between March 2018 and January 2022. We evaluated the learning curve using the Cumulative Sum (CUSUM) analysis and analyzed operative times, complication rates, and postoperative recovery metrics. Results The cohort had a mean age of 36 years, predominantly female (68.3%). The average body mass index (BMI) was within the normal range. A significant reduction in operative times was observed as the series progressed, with no permanent hypoparathyroidism or recurrent laryngeal nerve injuries reported. The learning curve plateaued after the 37th case. Postoperative recovery was consistent, with no significant difference in hospital stay duration. Complications were minimal, with a noted decrease in transient vocal cord palsy as experience with the robotic system increased. Conclusion Robotic thyroidectomy using the da Vinci system has demonstrated a significant improvement in operative efficiency without compromising safety. The learning curve is steep but manageable, and once overcome, it leads to improved surgical outcomes and high patient satisfaction. Further research with larger datasets and longer follow-up is necessary to establish the long-term benefits of robotic thyroidectomy.
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Affiliation(s)
- Bo Wang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Jia-Fan Yu
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Wei Ao
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Jun Wang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Xin-Yi Guo
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Meng-Yao Li
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Wen-Yu Huang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Chi-Peng Zhou
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Shou-Yi Yan
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Li-Yong Zhang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Si-Si Wang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Shao-Jun Cai
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Si-Ying Lin
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
| | - Wen-Xin Zhao
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fujian, Fuzhou, China
- Clinical Research Center for Precision Management of Thyroid Cancer of Fujian Province, Fuzhou, China
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Wang B, Zheng J, Yu JF, Lin SY, Yan SY, Zhang LY, Wang SS, Cai SJ, Abdelhamid Ahmed AH, Lin LQ, Chen F, Randolph GW, Zhao WX. Development of Artificial Intelligence for Parathyroid Recognition During Endoscopic Thyroid Surgery. Laryngoscope 2022; 132:2516-2523. [PMID: 35638245 DOI: 10.1002/lary.30173] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/24/2022] [Accepted: 04/13/2022] [Indexed: 12/21/2022]
Abstract
OBJECTIVE We aimed to establish an artificial intelligence (AI) model to identify parathyroid glands during endoscopic approaches and compare it with senior and junior surgeons' visual estimation. METHODS A total of 1,700 images of parathyroid glands from 166 endoscopic thyroidectomy videos were labeled. Data from 20 additional full-length videos were used as an independent external cohort. The YOLO V3, Faster R-CNN, and Cascade algorithms were used for deep learning, and the optimal algorithm was selected for independent external cohort analysis. Finally, the identification rate, initial recognition time, and tracking periods of PTAIR (Artificial Intelligence model for Parathyroid gland Recognition), junior surgeons, and senior surgeons were compared. RESULTS The Faster R-CNN algorithm showed the best balance after optimizing the hyperparameters of each algorithm and was updated as PTAIR. The precision, recall rate, and F1 score of the PTAIR were 88.7%, 92.3%, and 90.5%, respectively. In the independent external cohort, the parathyroid identification rates of PTAIR, senior surgeons, and junior surgeons were 96.9%, 87.5%, and 71.9%, respectively. In addition, PTAIR recognized parathyroid glands 3.83 s ahead of the senior surgeons (p = 0.008), with a tracking period 62.82 s longer than the senior surgeons (p = 0.006). CONCLUSIONS PTAIR can achieve earlier identification and full-time tracing under a particular training strategy. The identification rate of PTAIR is higher than that of junior surgeons and similar to that of senior surgeons. Such systems may have utility in improving surgical outcomes and also in accelerating the education of junior surgeons. LEVEL OF EVIDENCE 3 Laryngoscope, 2022.
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Affiliation(s)
- Bo Wang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.,Division of Thyroid and Parathyroid Endocrine Surgery, Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA
| | - Jing Zheng
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.,Department of Thyroid Surgery, Zhangzhou Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China
| | - Jia-Fan Yu
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Si-Ying Lin
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Shou-Yi Yan
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Li-Yong Zhang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Si-Si Wang
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Shao-Jun Cai
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Amr H Abdelhamid Ahmed
- Division of Thyroid and Parathyroid Endocrine Surgery, Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA
| | - Lan-Qin Lin
- Department of Operation, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Fei Chen
- College of Computer and Data Science, Fuzhou University, Fuzhou, Fujian, China
| | - Gregory W Randolph
- Division of Thyroid and Parathyroid Endocrine Surgery, Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, Massachusetts, USA.,Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Wen-Xin Zhao
- Department of Thyroid Surgery, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
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