SMART-Endomicroscopy (Sensing and Mechatronically Assisted Real-Time Endomicroscopy)

随着外科技术变得越来越微创，手术平台的复杂性不可避免地会增加。在临床上，将实时显微可视化无缝地集成到手术工作流程中并与现有的成像手段(如MRI、CT和超声)相结合是至关重要的。这项提议的目的是开发一种新的智能内窥镜探头，它集成了原位传感和机电控制，以便为微创手术(MIS)提供灵活和一致的组织特征。它解决了与生物光子学、机械/光学微型化和集成、超分辨率图像重建以及活体、原位组织表征的跟踪、定位和大范围覆盖有关的具体研究和工程挑战。通过多尺度微创成像集成，拟议的SMART内窥镜可能允许将癌症分期和干预作为单一程序执行，允许在手术的所有阶段进行组织学和血管检查，从而可以在术中改变管理决定，以确保对个别患者进行最佳治疗。随着个性化医疗成为现实，这将有助于改变手术治疗选择和患者癌症结果。该项目呼应了目前管理信息系统向小型化智能仪器的范式转变，该仪器具有集成的成像和传感，并通过机器人控制得到增强。它得到了一个多学科团队的支持，他们在物理、工程、医学图像计算和外科方面具有互补的技能。

As surgical techniques become more minimally invasive, there is an inevitable increase in complexity of the operating platforms. Clinically, it is of vital importance to integrate real-time microscopic visualisation into the surgical workflow in a seamless way and in combination with the existing imaging modalities such as MRI, CT and ultrasound. The aim of this proposal is to develop a new SMART-endomicroscopic probe that integrates in situ sensing and mechatronic control to allow for flexible and consistent tissue characterisation for Minimally Invasive Surgery (MIS). It addresses specific research and engineering challenges related to biophotonics, mechanical/optical miniaturisation and integration, super-resolution image reconstruction, as well as tracking, localisation and large area coverage for in vivo, in situ tissue characterisation. Through multi-scale minimally invasive imaging integration, the proposed SMART-Endomicroscope will potentially allow cancer staging and intervention to be performed as a single procedure, permitting histological and vascular examination to be performed at all stages of the operation, such that management decisions can be altered intra-operatively to ensure best treatment for the individual patient. This will help to transform surgical treatment options and patient cancer outcomes as personalised healthcare becomes a reality. The project echoes the current paradigm shift in MIS towards miniaturised smart instruments with integrated imaging and sensing, enhanced by robotic control. It is supported by a multidisciplinary team with complementary skills in physics, engineering, medical image computing and surgery.