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

随着手术技术变得更加微创，手术平台的复杂性不可避免地增加。在临床上，将实时显微镜可视化以无缝的方式集成到手术工作流程中并与现有的成像模式（如MRI，CT和超声）相结合至关重要。该提案的目的是开发一种新的SMART显微内镜探头，该探头集成了原位传感和机电控制，以实现微创手术（MIS）的灵活和一致的组织表征。它解决了与生物光子学，机械/光学成像和集成，超分辨率图像重建以及体内原位组织表征的跟踪，定位和大面积覆盖相关的特定研究和工程挑战。通过多尺度微创成像集成，拟议的SMART内窥镜将有可能允许癌症分期和干预作为一个单一的程序来执行，允许在手术的所有阶段进行组织学和血管检查，这样可以在术中改变管理决策，以确保对个体患者的最佳治疗。这将有助于改变手术治疗选择和患者癌症结果，因为个性化医疗保健成为现实。该项目呼应了当前MIS向集成成像和传感的智能仪器的范式转变，并通过机器人控制进行增强。它由一个多学科团队提供支持，该团队在物理学，工程学，医学图像计算和外科手术方面具有互补技能。

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.