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本文综述了便携式智能神经阻滞穿刺系统在野战救护方面的研究进展,探讨其在提高神经阻滞精准性、安全性和效率方面的应用现状与潜力。智能神经阻滞系统结合超声成像和人工智能(AI)技术,能够实现神经结构的自动识别与精准定位,辅助临床医师进行高效、安全的神经阻滞操作。在野战急救中,该系统可快速评估伤情并实施镇痛,同时具备培训功能,提升医护人员技术水平。此外,智能神经阻滞在麻醉、镇痛及慢性疼痛管理中展现出显著优势,通过精准阻滞减少并发症,改善患者预后。未来,该系统将向远程医疗融合、可穿戴设备协同、AI算法优化及多设备互联方向发展,有望在野战救护中发挥更大作用,推动神经阻滞技术的智能化与精准化。
Abstract:This review examines the research progress of portable intelligent nerve block puncture systems in battlefield emergency care and explores their current applications and potentials for enhancing the precision, safety, and efficiency of nerve blocks. By integrating ultrasound imaging and artificial intelligence(AI) technologies, these systems can automatically identify and precisely locate nerve structures, thereby assisting clinicians in performing nerve blocks more efficiently and safely. In battlefield emergency settings, the system can rapidly assess injuries and provide analgesia while also serving as a training tool to enhance the skills of medical personnel. Additionally, intelligent nerve block techniques have shown significant advantages in anesthesia, postoperative pain management, and chronic pain treatment by reducing complications and improving patient outcomes. Future developments are expected to focus on integrating remote medical services, wearable devices, optimizing AI algorithms, and enhancing multi-device interoperability. These advancements are expected to expand its role in battlefield emergency care, driving the intelligent and precise advancement of nerve block techniques.
[1]王萃,姚凌,朱霞玲,等.掌上超声在战场条件下的应用初探[J].海军医学杂志,2019,40(6):521-522. DOI:10.3969/j.issn. 1009-0754.2019.06.007.
[2]韩天民,宋慧菊,钟靖明,等.某院收治3776例战伤统计分析[J].西南国防医药,2015,25(4):423-425. DOI:10.3969/j.issn.1004-0188.2015.04.030.
[3] AMARAL S,PAWA A. Ultrasound-guided regional anesthesia:present trends and future directions[J]. Braz J Anesthesiol,2023,73(6):705-706. DOI:10.1016/j.bjane.2023.09.006.
[4] VIDERMAN D,DOSSOV M,SEITENOV S,et al. Artificial intelligence in ultrasound-guided regional anesthesia:a scoping review[J]. Front Med(Lausanne),2022,9:994805. DOI:10.3389/fmed.2022.994805.
[5] GUNGOR I,GUNAYDIN B,OKTAR S O,et al. A real-time anatomy identification via tool based on artificial intelligence for ultrasound-guided peripheral nerve block procedures:an accuracy study[J]. J Anesth,2021,35(4):591-594. DOI:10.1007/s00540-021-02947-3.
[6] NASCIMENTO J C,MARQUS J S. Robust shape tracking with multiple models in ultrasound images[J]. IEEE Trans Image Process,2008,17(3):392-406. DOI:10.1109/TIP.2007.915552.
[7] GU NGOR I,GU NAYDIA B,BU Y UKGEBIZ YESIL B M,et al. Evaluation of the effectiveness of artificial intelligence for ultrasound guided peripheral nerve and plane blocks in recognizing anatomical structures[J]. Ann Anat,2023,250:152143. DOI:10.1016/j.aanat. 2023.152143.
[8] BOWNESS J S,MORSE R,LEWIS O,et al. Variability between human experts and artif icial intelligence in identif ication of anatomical structures by ultrasound in regional anaesthesia:a framework for evaluation of assistive artificial intelligence[J]. Br J Anaesth,2023,132(5):1063-1072. DOI:10.1016/j.bja.2023.09.023.
[9] ALKHATIB M,HAFIANE A,TAHRI O,et al. Adaptive median binary patterns for fully automatic nerves tracking in ultrasound images[J]. Comput Methods Programs Biomed,2018,160(3):129-140. DOI:10.1016/j.cmpb.2018.03.013.
[10]马宇,熊源长,邓小明.便携式超声设备在未来战伤急救和麻醉镇痛中的应用[J].人民军医,2014,57(1):17-18.
[11]张伟丽,彭碧波,李胜男,等.便携式超声在战场战伤救治中应用与展望[J].中华灾害救援医学,2021,9(8):1189-1193. DOI:10.13919/j.issn.2095-6274.2021.08.012.
[12] LI Z,ZHAO L,WANG W,et al. Application of intelligent ultrasound in real-time monitoring of postoperative analgesic nerve block[J/OL].Cont rast Media Mol Imaging,2021:3309382. DOI:10.1155/2021/3309382.
[13]李正阳,周路路,贾宁,等.布比卡因脂质体超声引导下竖脊肌平面阻滞用于胸腔镜手术患者的临床观察[J].麻醉安全与质控,2024,6(5):270-274. DOI:10.3969/j.issn.2096-2681.2024.05.007.
[14] DE JOSE MARIA B,BANUE E,NAVARRO EGEA M,et al.Ultrasound-guided supraclavicular vs infraclavicular brachial plexus blocks in children[J]. Paediatr Anaesth,2008,18(9):838-844. DOI:10.1111/j.1460-9592.2008.02644.x.
[15] HAO D,FIOR E M,DI CAPUA C,et al. Ultrasound-guided peripheral nerve blocks:a practical review for acute cancer-related pai n[J]. C u r r Pai n He a d a che Re p,2022,26(11):813-820.DOI:10.1007/s11916-022-01089-9.
[16] LECUN Y,BENGIO Y,HINTON G. Deep learning[J]. Nature,2015,521(7553):436-444. DOI:10.1038/nature14539.
[17] SOFFER S,BEN-COHEN A,SHIMON O,et al. Convolutional neural networks for radiologic images:a radiologist’s guide[J].Radiology,2019,290(3):590-606. DOI:10.1148/radiol.2018180547.
[18] GOMEZ-FLORES W,COELHO DE ALBUQUERQUE PEREIA W.A comparative study of pre-trained convolutional neural networks for semantic segmentation of breast tumors in ultrasound[J]. Comput Biol Med,2020,126:104036. DOI:10.1016/j.compbiomed.2020.104036.
[19] HUANG C,ZHOU Y,TAN W,et al. Applying deep learning in recognizing the femoral nerve block region on ultrasound images[J].Ann Transl Med,2019,7(18):453. DOI:10.21037/atm.2019. 08.61.
[20] LIU C,LI L,ZHOU X,et al. Intelligent three-dimensional reconstruction algorithm-based ultrasound-guided nerve block in intraoperative anesthesia and postoperative analgesia of orthopedic surgery[J]. Comput Math Methods Med,2022:9447649. DOI:10.1155/2022/9447649.
[21]司晓娟,托静美,宋和琴.超声人工智能辅诊系统在甲状腺可疑结节良恶性鉴别诊断中应用价值[J].临床军医杂志,2024,52(3):312-315. DOI:10.16680/j.1671-3826.2024.03.25.
[22] BERGGREEN J,JOHANSSON A,JAHR J,et al. Deep learning on ultrasound images visualizes the femoral nerve with good precision[J]. Healthcare(Basel),2023,11(2):184. DOI:10.3390/healthcare11020184.
[23] HUANG A,JIANG L,ZHANG J,et al. Attention-VGG16-UNet:a novel deep learning approach for automatic segmentation of the median nerve in ultrasound images[J]. Quant Imaging Med Surg,2022,12(6):3138-3150. DOI:10.21037/qims-21-1074.
[24] WU C H,SYU W T,LIN M T,et al. Automated segmentation of median nerve in dynamic sonography using deep learning:evaluation of model performance[J]. Diagnostics(Basel),2021,11(10):1893. DOI:10.3390/diagnostics11101893.
[25]高晓曼,李咸鹏,郑煜丽,等.急诊科老年髋部骨折外周神经阻滞镇痛的研究进展[J].中国急救医学,2022,42(9):825-829. DOI:10.3969/j.issn.1002-1949.2022.09.017.
[26]刘晓翔,高成杰,贾云逸,等.急救现场采用便携式超声引导腰骶丛前路单点穿刺神经阻滞技术对下肢创伤患者实施镇痛的效果[J].山东医药,2024,64(15):71-74. DOI:10.3969/j.issn.1002-266X.2024.15.016.
[27]黄风怡,陈一佳,高飞,等.纳布啡复合罗哌卡因用于髂筋膜间隙阻滞对老年髋部骨折病人术前镇痛效果的影响[J].临床外科杂志,2022,30(6):524-527. DOI:10.3969/j.issn.1005-6483. 2022.06.007.
[28]朱捷,周丽梅,袁丹凤,等.野战救护智能辅助系统的设计与实现[J].解放军护理杂志,2020,37(2):89-92. DOI:10.3969/j.issn.1008-9993. 2020.02.026.
[29] BOWNESS J,El-BOGHDADLY K,BURCKETT-ST LAURENT D.Artificial intelligence for image interpretation in ultrasound-guided regional anaesthesia[J]. A naesthesia,2021,76(5):602-607.DOI:10.1111/anae.15212.
[30] BOWNESS J S,El-BOGHDADLY K,WOODWORTH G,et al.Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia[J]. Reg Anesth Pain Med,2022,47(6):375-379. DOI:10.1136/rapm-2021-103368.
[31] ROBARDS C,HADZIC A,SOMASUNDARAM L,et al.Intraneural injection with low-current stimulation during popliteal sciatic nerve block[J]. Anesth Analg,2009,109(2):673-677.DOI:10.1213/ane.0b013e3181aa2d73.
[32] PASN ICK I M,K ROL A,KOSSON D,et al. T he safet y of读者·作者·编者peripheral nerve blocks:the role of triple monitoring in regional anaesthesia,a comprehensive review[J]. Healthcare(Basel),2024,12(7):769. DOI:10.3390/healthcare12070769.
[33] SINGHAL M,GUPTA L,HIRANI K. A comprehensive analysis and review of artificial intelligence in anaesthesia[J/OL]. Cureus,2023,15(9):e45038. DOI:10.7759/cureus.45038.
[34] FLAVIN M T,HA K H,GUO Z,et al. Bioelastic state recovery for haptic sensory substitution[J]. Nature,2024,635(8038):345-352.DOI:10.1038/s41586-024-08155-9.
[35] LI X,YE S,SHEN Q,et al. Evaluating virtual reality anatomy training for novice anesthesiologists in performing ultrasoundguided brachial plexus blocks:a pilot study[J]. BMC Anesthesiol,2024,24(1):474. DOI:10.1186/s12871-024-02865-3.
[36] K ELLY C J,K ARTHIK ESALI NGAM A,SULEYMAN M,et al. Key challenges for delivering clinical impact with artificial intelligence[J]. BMC Med,2019,17(1):195. DOI:10.1186/s12916-019-1426-2.
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中图分类号:TP18;R82
引用信息:
[1]于晓萌,傅强.便携智能神经阻滞系统在野战救护的研究进展[J].麻醉安全与质控,2025,7(05):439-444.
2025-05-15
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2025-06-20
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2025-09-24
2025-09-24