Henderson Eric R, Gracias David H, Ramakrishnan Venkat M, Tiomkin Stas, Wachs Juan P, Wollin Daniel A
Thayer School of Engineering, Dartmouth College, Hanover, NH.
Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, NH.
Proc SPIE Int Soc Opt Eng. 2025 Jan 19;13301:48-62. Epub 2025 Mar 19.
Surgery involves iterative identification of anatomical structures and intervention upon them. In recent years, machine-based tissue recognition has advanced substantially, enhancing the safety and efficacy of medical procedures by reducing uncertainty about structure identity through quantitative evaluation (e.g., tissue density, optical properties, fluorescence contrast). However, while tissue-identifying tools have progressed rapidly, the development of intervention tools has lagged. It is worth considering the eventual convergence of these technologies at their mature stage, culminating in autonomous robotic surgery (ARS). Beyond technical feasibility, deploying such a groundbreaking technology requires careful consideration. Typically, expensive and novel medical advancements are introduced in tertiary academic medical centers, where state-of-the-art infrastructure and trained personnel are available. However, ARS holds the greatest potential for regions lacking access to surgeons, making it crucial to define the optimal scenarios for its implementation. The technical demands of ARS will vary significantly depending on the type of procedure. Decision-making should prioritize a focused set of surgery-requiring conditions and assess the cumulative risk profile of offering ARS in regions with no existing treatment options. Key factors in this evaluation include: 1) procedure commonness; 2) ARS feasibility with current technology; 3) risk of adverse events from a robotic intervention; 4) procedure urgency (i.e., risk of no intervention); 5) risk of abandoning procedure in the setting of technical failure; 6) ability to have remote human oversight; and 7) current availability of resources in the target population/region. Based on these considerations, the initial stabilization of high-energy open skeletal trauma-particularly in active combat military settings-represents a highly feasible and valuable early application. Additionally, the future development of self-sufficient microrobots capable of operating without external imaging could further enhance the portability and accessibility of ARS as the technology matures.
手术涉及对解剖结构的反复识别并对其进行干预。近年来,基于机器的组织识别技术有了长足进步,通过定量评估(如组织密度、光学特性、荧光对比度)降低结构识别的不确定性,从而提高了医疗程序的安全性和有效性。然而,尽管组织识别工具发展迅速,但干预工具的开发却滞后了。值得考虑这些技术在成熟阶段的最终融合,最终实现自主机器人手术(ARS)。除了技术可行性外,部署这样一项开创性技术需要仔细考量。通常,昂贵且新颖的医学进步首先在三级学术医疗中心引入,那里具备最先进的基础设施和训练有素的人员。然而,ARS在缺乏外科医生的地区具有最大潜力,因此确定其最佳实施场景至关重要。ARS的技术需求会因手术类型而有显著差异。决策应优先考虑一组特定的需要手术的病症,并评估在没有现有治疗选择的地区提供ARS的累积风险概况。该评估中的关键因素包括:1)手术的常见程度;2)当前技术下ARS的可行性;3)机器人干预导致不良事件的风险;4)手术的紧迫性(即不进行干预的风险);5)在技术失败情况下放弃手术的风险;6)进行远程人工监督的能力;7)目标人群/地区当前的资源可用性。基于这些考虑,高能开放性骨骼创伤的初始稳定治疗——特别是在现役战斗军事环境中——是一个高度可行且有价值的早期应用。此外,随着技术的成熟,能够在无需外部成像的情况下运行的自给自足微型机器人的未来发展,可能会进一步提高ARS的便携性和可及性。
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