Smart Electro-Optical Techniques for Bowel Cancer Surgery

这项研究将寻求开发一种新的电阻抗技术，专注于肠癌的诊断和治疗。在英国，每年有超过42,000人被诊断为肠癌，超过16,000人死于肠癌，使其成为英国第二大癌症死因[1]。筛查计划在通过早期诊断[2][3]降低患者死亡率方面取得了重大成功，但这一成功取决于可用的诊断技术的质量[4]。在这些诊断过程中加入更多的定量成分将提高其可靠性，并有助于减少漏诊病例的数量。手术干预后30天的死亡率约为6%[5]，因此仍有改善治疗和手术后结果的余地。手术仍然是结直肠癌最常见的治疗方法[6]，因此，能够实时向外科医生提供组织特性信息的工具将有助于移除(癌前)生长，而不会干扰其他未受影响的组织，并避免相关并发症。该项目建议开发一种先进的生物成像技术，以提供这种无价的定量评估。这项研究旨在建立一种技术，通过数据分析以及传感器和信号处理系统的设计、制造和测试，实时指导癌症识别和切除手术。这项尖端的光电成像技术将在体内和体外模型中进行测试，并使用先进的化学成像技术进行验证。

This research will look to develop a novel electrical impedance technology with a focus on diagnosis and treatment of bowel cancer. Over 42,000 people are diagnosed and more than 16,000 die from bowel cancer every year in the UK, making it the country's second leading cause of death among cancers [1]. Screening programmes have demonstrated significant success in reducing patient mortality through early diagnosis [2][3], but that success is dependent on the quality of the diagnostic techniques available [4]. Incorporating further quantitative components into these diagnostic processes will improve their reliability and help reduce the number of missed cases. Mortality rates 30-days following surgical intervention stand at around 6% [5], and so there also remains scope for improving treatment and post-operative outcomes. Surgery remains the most common treatment method for colo-rectal cancers [6], and so a tool capable of providing surgeons with information about tissue properties in real time will aid in the removal of (pre)cancerous growths without disturbing other unaffected tissues and avoid associated complications. This project proposes the development of an advanced bio-imaging technique that provides this invaluable quantitative assessment. The research aims to establish a technique that will guide cancer identification and removal surgery in real time, through data analysis, and the design, fabrication, and testing of sensors and signal processing systems. This cutting-edge electro-optical imaging technology will be tested in In-vivo and ex-vivo models, and validated using advanced chemical imaging techniques.