Franke Stefan, Meixensberger Jürgen, Neumuth Thomas
University of Leipzig, Innovation Center Computer Assisted Surgery, Leipzig, Germany.
University Hospital Leipzig, Department of Neurosurgery, Germany; University of Leipzig, Innovation Center Computer Assisted Surgery, Leipzig, Germany.
J Biomed Inform. 2015 Apr;54:158-66. doi: 10.1016/j.jbi.2015.02.005. Epub 2015 Mar 6.
Surgical workflow management is expected to enable situation-aware adaptation and intelligent systems behavior in an integrated operating room (OR). The overall aim is to unburden the surgeon and OR staff from both manual maintenance and information seeking tasks. A major step toward intelligent systems behavior is a stable classification of the surgical situation from multiple perspectives based on performed low-level tasks.
The present work proposes a method for the classification of surgical situations based on multi-perspective workflow modeling. A model network that interconnects different types of surgical process models is described. Various aspects of a surgical situation description were considered: low-level tasks, high-level tasks, patient status, and the use of medical devices. A study with sixty neurosurgical interventions was conducted to evaluate the performance of our approach and its robustness against incomplete workflow recognition input.
A correct classification rate of over 90% was measured for high-level tasks and patient status. The device usage models for navigation and neurophysiology classified over 95% of the situations correctly, whereas the ultrasound usage was more difficult to predict. Overall, the classification rate decreased with an increasing level of input distortion.
Autonomous adaptation of medical devices and intelligent systems behavior do not currently depend solely on low-level tasks. Instead, they require a more general type of understanding of the surgical condition. The integration of various surgical process models in a network provided a comprehensive representation of the interventions and allowed for the generation of extensive situation descriptions.
Multi-perspective surgical workflow modeling and online situation models will be a significant pre-requisite for reliable and intelligent systems behavior. Hence, they will contribute to a cooperative OR environment.
手术工作流程管理有望在集成手术室（OR）中实现情境感知适应和智能系统行为。总体目标是使外科医生和手术室工作人员从手动维护和信息查找任务中解脱出来。迈向智能系统行为的一个重要步骤是基于执行的低级任务从多个角度对手术情境进行稳定分类。
本研究提出了一种基于多视角工作流程建模的手术情境分类方法。描述了一个连接不同类型手术过程模型的模型网络。考虑了手术情境描述的各个方面：低级任务、高级任务、患者状态和医疗设备的使用。进行了一项包含60例神经外科手术干预的研究，以评估我们方法的性能及其对不完整工作流程识别输入的鲁棒性。
高级任务和患者状态的正确分类率超过90%。导航和神经生理学的设备使用模型对超过95%的情况分类正确，而超声的使用情况更难预测。总体而言，随着输入失真程度的增加，分类率下降。
医疗设备的自主适应和智能系统行为目前并不完全依赖于低级任务。相反，它们需要对手术状况有更全面的理解。将各种手术过程模型集成到一个网络中，可以全面呈现手术干预情况，并生成详细的情境描述。
多视角手术工作流程建模和在线情境模型将是可靠和智能系统行为的重要前提条件。因此，它们将有助于营造一个协作的手术室环境。
