1.New advances in the identification and protection of parathyroid glands in thyroid surgery
Yangfang LIU ; Junyi GAO ; Huaijin ZHENG ; Surong HUA ; Quan LIAO
Chinese Journal of Endocrine Surgery 2025;19(4):467-471
Identification and functional protection of parathyroid glands are the key to reduce the incidence of postoperative complications after thyroid surgery. In recent years, the development of several fluorescence imaging technology and the application of artificial intelligence based on deep learning in thyroid surgery have brought technical breakthroughs in the identification and blood supply assessment of parathyroid glands during surgery, helping surgeons to identify parathyroid glands quickly and accurately, and improving the prognosis of surgery. Based on this, this article focuses on the new advances in the identification and protection of parathyroid glands in thyroid surgery, especially the research and application progress of fluorescence imaging, lymph node tracers, artificial intelligence and other aspects, and discusses the future development prospects.
2.Exploration of the application of artificial intelligence assisted bleeding point recognition in laparoscopic pancreatic surgery
Lu PING ; Mengqing SUN ; Xianlin HAN ; Ruohan CUI ; Hu ZHOU ; Jile SHI ; Yuze HUA ; Surong HUA ; Wenming WU
Chinese Journal of Surgery 2025;63(10):920-925
Objective:To explore the clinical application value of artificial intelligence models in identifying bleeding events and hemorrhagic points during laparoscopic pancreatic surgery.Methods:This single-center retrospective cohort study collected surgical videos of 25 patients undergoing laparoscopic pancreatic surgery at the Department of General Surgery, Peking Union Medical College Hospital from January 2022 to December 2024. Videos within 5 seconds before and after representative bleeding events were captured at 30 frames/s, with 11 666 hemorrhagic-related video frames annotated. Two algorithm models were developed: a pigment-based model and a pigment+optical flow-based model for classification and target recognition of bleeding frames. The training and test sets for the pigment-based algorithm contained 4 692 hemorrhagic and 4 309 non-hemorrhagic frames, while those for the pigment+optical flow model included 1 339 hemorrhagic and 1 326 non-hemorrhagic frames. Performance evaluation was conducted using overlap thresholds, with accuracy and recall rates as key metrics.Results:The pigment-based model achieved 93.8% accuracy (134/143) and 43.3% recall (134/310) in hemorrhagic frame classification. At an overlap threshold of 0.3, the pigment-based model showed 84.1% accuracy (433/515) and 85.4% recall (433/507) in target recognition. When the threshold was increased to 0.5, the pigment+optical flow model demonstrated 88.1% accuracy (354/402) and 89.2% recall (354/397) in hemorrhagic target recognition.Conclusions:It is difficult to distinguish active bleeding from old bleeding completely by pigment information alone. The spatio-temporal features can be effectively extracted by combining pigment and optical flow information, and the bleeding can be accurately identified and located, which has potential clinical application value.
3.New advances in the identification and protection of parathyroid glands in thyroid surgery
Yangfang LIU ; Junyi GAO ; Huaijin ZHENG ; Surong HUA ; Quan LIAO
Chinese Journal of Endocrine Surgery 2025;19(4):467-471
Identification and functional protection of parathyroid glands are the key to reduce the incidence of postoperative complications after thyroid surgery. In recent years, the development of several fluorescence imaging technology and the application of artificial intelligence based on deep learning in thyroid surgery have brought technical breakthroughs in the identification and blood supply assessment of parathyroid glands during surgery, helping surgeons to identify parathyroid glands quickly and accurately, and improving the prognosis of surgery. Based on this, this article focuses on the new advances in the identification and protection of parathyroid glands in thyroid surgery, especially the research and application progress of fluorescence imaging, lymph node tracers, artificial intelligence and other aspects, and discusses the future development prospects.
4.Exploration of the application of artificial intelligence assisted bleeding point recognition in laparoscopic pancreatic surgery
Lu PING ; Mengqing SUN ; Xianlin HAN ; Ruohan CUI ; Hu ZHOU ; Jile SHI ; Yuze HUA ; Surong HUA ; Wenming WU
Chinese Journal of Surgery 2025;63(10):920-925
Objective:To explore the clinical application value of artificial intelligence models in identifying bleeding events and hemorrhagic points during laparoscopic pancreatic surgery.Methods:This single-center retrospective cohort study collected surgical videos of 25 patients undergoing laparoscopic pancreatic surgery at the Department of General Surgery, Peking Union Medical College Hospital from January 2022 to December 2024. Videos within 5 seconds before and after representative bleeding events were captured at 30 frames/s, with 11 666 hemorrhagic-related video frames annotated. Two algorithm models were developed: a pigment-based model and a pigment+optical flow-based model for classification and target recognition of bleeding frames. The training and test sets for the pigment-based algorithm contained 4 692 hemorrhagic and 4 309 non-hemorrhagic frames, while those for the pigment+optical flow model included 1 339 hemorrhagic and 1 326 non-hemorrhagic frames. Performance evaluation was conducted using overlap thresholds, with accuracy and recall rates as key metrics.Results:The pigment-based model achieved 93.8% accuracy (134/143) and 43.3% recall (134/310) in hemorrhagic frame classification. At an overlap threshold of 0.3, the pigment-based model showed 84.1% accuracy (433/515) and 85.4% recall (433/507) in target recognition. When the threshold was increased to 0.5, the pigment+optical flow model demonstrated 88.1% accuracy (354/402) and 89.2% recall (354/397) in hemorrhagic target recognition.Conclusions:It is difficult to distinguish active bleeding from old bleeding completely by pigment information alone. The spatio-temporal features can be effectively extracted by combining pigment and optical flow information, and the bleeding can be accurately identified and located, which has potential clinical application value.
5.Artificial intelligence in diagnosis and treatment of thyroid and parathyroid diseases: a surgical perspective
Surong HUA ; Huaijin ZHENG ; Quan LIAO
Chinese Journal of General Surgery 2024;39(1):30-35
In recent years, artificial intelligence technology has been empowering various industries and leading industrial upgrading. The progress of artificial intelligence in medical image analysis and surgical navigation positioning is revolutionizing the entire medical field and gradually penetrating into the diagnosis and treatment of thyroid and parathyroid diseases. This article focuses on the application of artificial intelligence in the surgical diagnosis and treatment of thyroid and parathyroid diseases, emphasizing the research and application progress of deep learning based artificial intelligence systems in preoperative evaluation, intraoperative decision-making assistance, and postoperative prognosis prediction, and exploring future development prospects.
6.The value of mitoxantrone hydrochloride injection for tracing in endoscopic thyroidectomy via anterior chest approach for the treatment of papillary thyroid carcinoma
Xiaojing NING ; Hongyu WANG ; Liyuan FU ; Yi YIN ; Surong HUA
Chinese Journal of Endocrine Surgery 2024;18(3):377-382
Objective:To explore the value of mitoxantrone hydrochloride injection for tracing in endoscopic thyroidectomy (ETE) via anterior chest approach for papillary thyroid carcinoma (PTC) .Methods:A retrospective analysis was conducted on patients undergoing ETE via anterior chest approach for PTC admitted to Beijing Longfu Hospital (Medical Treatment Combination with Peking Union Medical College Hospital) from Sep. 2022 to Mar. 2024. The patients were divided into two groups: the control group (without tracer) and the tracer group (with mitoxantrone hydrochloride injection for tracing). All surgeries were performed by the same thyroid surgical team. Baseline, postoperative pathologies and complications were compared between the 2 groups.Results:A total of 25 patients (13 in the control group and 12 in the tracer group) were included in this study, and the average dissection of unilateral central region lymph nodes in the tracer group was 7.4±4.6, significantly more than in the control group (2.4±1.9) ( P=0.004). There were no instances of mistakenly resected parathyroid gland in the postoperative pathology or accidental injury of recurrent laryngeal nerve in either group. The incidence of transient hypocalcemia did not significantly different between the two groups ( P=0.503). However, the incidence of transient hypoparathyroidism in the tracer group was 1 (1/12,8.3%), significantly lower than in the control group 4 (4/13,30.8%) ( P=0.009). The tracer group exhibited more impressive levels in parathyroid hormone (5.4±8.1) pg/mL compared to the control group (20.0±11.1) pg/mL ( P=0.001) .The total volume of postoperative drainage in the tracer group (142.9±71.7) mL was more than that of the control group (87.7±38.8) mL ( P=0.030). But It did not affect the extubation time in either group ( P=0.610). No residual tracer was observed at the skin puncture site in the tracer group after 2 weeks. Conclusions:Mitoxantrone hydrochloride injection for tracing as tracer in ETE via breast approach can increase the number of pathological lymph nodes dissection in cervical central region. Combined with negative development, identifying and protecting the function of parathyroid glands show feasible and potential application value to improve the safety of thyroidectomy. The use of mitoxantrone hydrochloride injection for tracer has the risk of increased exudation from the surgical area, but does not affect the time to remove the drain.
7.Application of near-infrared autofluorescence probe in intraoperative parathyroid gland identification
Surong HUA ; Junyi GAO ; Zhen CAO ; Huaijin ZHENG ; Hongyu WANG ; Xiaojing NING ; Liyuan FU ; Yang ZHANG ; Yikun WANG ; Ziwen LIU ; Quan LIAO
Chinese Journal of Endocrine Surgery 2024;18(5):675-678
Objective:To explore the use of near-infrared autofluorescence probe (NIRAF-P) and its application in identifying parathyroid glands during surgery.Methods:A total of 68 patients undergoing thyroid surgery at Peking Union Medical College Hospital and Beijing Longfu Hospital between Dec. 2023 and Jun. 2024 were selected. During the operation, the near-infrared parathyroid gland detector was used to identify the parathyroid gland tissue to be tested, and histopathological examination was performed. The positive predictive value and accuracy of the near-infrared parathyroid gland detector were analyzed.Results:A total of 111 parathyroid glands were identified in 68 patients, and the positive predictive value and accuracy of the NIRAF-P were 95.5% and 94.6%, respectively.Conclusions:The NIRAF-P has high accuracy in identifying parathyroid glands. The standardized application of the NIRAF-P can help improve the efficiency of identifying parathyroid glands during surgery.
8.Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients (version 2024)
Yao LU ; Yang LI ; Leiying ZHANG ; Hao TANG ; Huidan JING ; Yaoli WANG ; Xiangzhi JIA ; Li BA ; Maohong BIAN ; Dan CAI ; Hui CAI ; Xiaohong CAI ; Zhanshan ZHA ; Bingyu CHEN ; Daqing CHEN ; Feng CHEN ; Guoan CHEN ; Haiming CHEN ; Jing CHEN ; Min CHEN ; Qing CHEN ; Shu CHEN ; Xi CHEN ; Jinfeng CHENG ; Xiaoling CHU ; Hongwang CUI ; Xin CUI ; Zhen DA ; Ying DAI ; Surong DENG ; Weiqun DONG ; Weimin FAN ; Ke FENG ; Danhui FU ; Yongshui FU ; Qi FU ; Xuemei FU ; Jia GAN ; Xinyu GAN ; Wei GAO ; Huaizheng GONG ; Rong GUI ; Geng GUO ; Ning HAN ; Yiwen HAO ; Wubing HE ; Qiang HONG ; Ruiqin HOU ; Wei HOU ; Jie HU ; Peiyang HU ; Xi HU ; Xiaoyu HU ; Guangbin HUANG ; Jie HUANG ; Xiangyan HUANG ; Yuanshuai HUANG ; Shouyong HUN ; Xuebing JIANG ; Ping JIN ; Dong LAI ; Aiping LE ; Hongmei LI ; Bijuan LI ; Cuiying LI ; Daihong LI ; Haihong LI ; He LI ; Hui LI ; Jianping LI ; Ning LI ; Xiying LI ; Xiangmin LI ; Xiaofei LI ; Xiaojuan LI ; Zhiqiang LI ; Zhongjun LI ; Zunyan LI ; Huaqin LIANG ; Xiaohua LIANG ; Dongfa LIAO ; Qun LIAO ; Yan LIAO ; Jiajin LIN ; Chunxia LIU ; Fenghua LIU ; Peixian LIU ; Tiemei LIU ; Xiaoxin LIU ; Zhiwei LIU ; Zhongdi LIU ; Hua LU ; Jianfeng LUAN ; Jianjun LUO ; Qun LUO ; Dingfeng LYU ; Qi LYU ; Xianping LYU ; Aijun MA ; Liqiang MA ; Shuxuan MA ; Xainjun MA ; Xiaogang MA ; Xiaoli MA ; Guoqing MAO ; Shijie MU ; Shaolin NIE ; Shujuan OUYANG ; Xilin OUYANG ; Chunqiu PAN ; Jian PAN ; Xiaohua PAN ; Lei PENG ; Tao PENG ; Baohua QIAN ; Shu QIAO ; Li QIN ; Ying REN ; Zhaoqi REN ; Ruiming RONG ; Changshan SU ; Mingwei SUN ; Wenwu SUN ; Zhenwei SUN ; Haiping TANG ; Xiaofeng TANG ; Changjiu TANG ; Cuihua TAO ; Zhibin TIAN ; Juan WANG ; Baoyan WANG ; Chunyan WANG ; Gefei WANG ; Haiyan WANG ; Hongjie WANG ; Peng WANG ; Pengli WANG ; Qiushi WANG ; Xiaoning WANG ; Xinhua WANG ; Xuefeng WANG ; Yong WANG ; Yongjun WANG ; Yuanjie WANG ; Zhihua WANG ; Shaojun WEI ; Yaming WEI ; Jianbo WEN ; Jun WEN ; Jiang WU ; Jufeng WU ; Aijun XIA ; Fei XIA ; Rong XIA ; Jue XIE ; Yanchao XING ; Yan XIONG ; Feng XU ; Yongzhu XU ; Yongan XU ; Yonghe YAN ; Beizhan YAN ; Jiang YANG ; Jiangcun YANG ; Jun YANG ; Xinwen YANG ; Yongyi YANG ; Chunyan YAO ; Mingliang YE ; Changlin YIN ; Ming YIN ; Wen YIN ; Lianling YU ; Shuhong YU ; Zebo YU ; Yigang YU ; Anyong YU ; Hong YUAN ; Yi YUAN ; Chan ZHANG ; Jinjun ZHANG ; Jun ZHANG ; Kai ZHANG ; Leibing ZHANG ; Quan ZHANG ; Rongjiang ZHANG ; Sanming ZHANG ; Shengji ZHANG ; Shuo ZHANG ; Wei ZHANG ; Weidong ZHANG ; Xi ZHANG ; Xingwen ZHANG ; Guixi ZHANG ; Xiaojun ZHANG ; Guoqing ZHAO ; Jianpeng ZHAO ; Shuming ZHAO ; Beibei ZHENG ; Shangen ZHENG ; Huayou ZHOU ; Jicheng ZHOU ; Lihong ZHOU ; Mou ZHOU ; Xiaoyu ZHOU ; Xuelian ZHOU ; Yuan ZHOU ; Zheng ZHOU ; Zuhuang ZHOU ; Haiyan ZHU ; Peiyuan ZHU ; Changju ZHU ; Lili ZHU ; Zhengguo WANG ; Jianxin JIANG ; Deqing WANG ; Jiongcai LAN ; Quanli WANG ; Yang YU ; Lianyang ZHANG ; Aiqing WEN
Chinese Journal of Trauma 2024;40(10):865-881
Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.
9.Application of deep learning to identify recurrent laryngeal nerve in endoscopic thyroidectomy via breast approach
Surong HUA ; Zhihong WANG ; Jiayi LI ; Junyi GAO ; Jing WANG ; Guanglin HE ; Palashate YEERKENBIEKE ; Xianlin HAN ; Ge CHEN ; Quan LIAO
Chinese Journal of Endocrine Surgery 2022;16(3):287-292
Objective:To explore whether deep learning could apply to recognize the recurrent laryngeal nerve (RLN) in videos of endoscopic thyroidectomy (ETE) via breast approach.Methods:Videos of ETE via breast approach in Peking Union Medical College Hospital from Feb. 2020 to Aug. 2021 were collected. Videos containing RLN were selected, and the outline of RLN was marked by two thyroid surgeons. Then data were divided into a training set and a test set in a ratio of 5:1 and classified into the high and low difficulty group according to a senior thyroid surgeon’s opinion. Those pictures were input to D-LinkNet model. Precision, sensitivity and mean dice index was calculated.Results:A total of 46 videos including 153, 520 frames of pictures were included in this study. 131,039 frames of 39 videos were in the training set and 22,481 frames of 7 videos were in the test set. When the intersection over union threshold was 0.1, the sensitivity and precision was 92.9%/72.8% and 47.6%/54.9% in high and low recognition group, respectively. When the intersection over union threshold was 0.5, the sensitivity and precision turned to 85.8%/67.2% and 37.6%/43.5% in high and low difficulty group, respectively. Mean Dice index was 0.781 and 0.663 in high and low difficulty group, respectively.Conclusions:RLN recognition based on deep learning is feasible and has potential application value in ETE, which may help surgeons reduce the risk of accidental injury of RLN and improve the safety of thyroidectomy.
10.Application of Endoscopic Parathyroidectomy in the Treatment of Primary Hyperparathyroidism
Surong HUA ; Zhihong WANG ; Junyi GAO ; Mengyi WANG ; Qiaofei LIU ; Wenjing LIU ; Guannan GE ; Yingxin WEI ; Ya HU ; Quan LIAO
Chinese Journal of Endocrine Surgery 2022;16(4):391-395
Objective:To summarize the experience and the clinical data of patients with primary hyperparathyroidism undergoing endoscopic parathyroidectomy.Methods:A total of 24 patients who underwent endoscopic parathyroidectomy for primary hyperparathyroidism in Peking Union Medical College Hospital during Feb. 2021 to May. 2022 were concluded in this study (20 cases of parathyroidectomy via axillary approach and 4 cases of parathyroidectomy via thoracic and breast approach) . The operation time, postoperative drainage, length of stay, level of parathyroid hormone and serum calcium of those patients were collected. Postoperative complications and recurrence of hyperparathyroidism were also observed.Results:The postoperative levels of serum parathyroid hormone and serum calcium were significantly reduced (over 50%) compared with preoperative level ( P<0.05) . The average operation time was (96±22) min (64-157 min) . The mean postoperative drainage volume was (47±16) ml on day 1, (46±11) ml on day 2, and (30±9) ml on day 3, respectively. The average length of postoperative hospital stay was (2.8±1.1) days (2-6 days) . In one case of parathyroidectomy via axillary approach, the operation was converted to open surgery because of the low position of lesion. Other cases completed endoscopic surgery and obtained satisfactory cosmetic results. There were no postoperative complications such as bleeding, permanent hoarseness, coughing while drinking water, or surgical site infection. The mean follow-up time was (7.4±4.2) months (1-16 months) . There was no obvious discomfort and no recurrence during follow-up. Conclusion:Endoscopic parathyroidectomy is safe and effective in the treatment of primary hyperparathyroidism, which can be used as a surgical option for patients with cosmetic requirements.

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