Early cancer diagnostics using evanescent wave Mid-IR spectroscopy

癌症仍然是世界上最流行的疾病之一。癌症与非常高的死亡率（10年生存率为50%）相关，因为大多数癌症在晚期被诊断出来。在早期检测方面已经取得了最新进展，尽管所采用的测定仍然是实验性的，非常昂贵，并且可能具有较差的灵敏度和特异性。另一方面，中红外光谱已被证明在检测血液和其他体液中的癌症特异性分析物方面是稳健的。然而，常规的基于FTIR的测量（包括使用ATR晶体）对于低分析物浓度下的这种诊断不够灵敏。在这个项目中，我们将利用信号增强ATR芯片和波导芯片开发高灵敏度的倏逝波中红外光谱，并将使用机器学习方法进行快速早期癌症诊断和治疗监测。具体而言，该项目将涉及设计和制造高灵敏度的一次性ATR和波导芯片，用于癌症（乳腺和卵巢）生物标志物传感。制造的芯片将用于从剑桥大学英国癌症研究中心的合作者那里获得的血浆样本的中红外光谱，并将使用专门为此目的开发的机器学习和深度学习算法分析结果。

Cancer continues to be one of the most prevalent diseases worldwide. Cancer is associated with a very high mortality rate (50% survival at 10 years) as most cancers are diagnosed at a late stage. Recent advances have been made in early detection, though the assays employed are still experimental, highly expensive and can suffer from poor sensitivity and specificity. On the other hand, Mid-IR spectroscopy have shown to be robust in detecting cancer-specific analytes within the blood and other bodily fluids. However, conventional FTIR based measurements (including the use of ATR crystals) are insufficiently sensitive for such diagnostics at low analyte concentrations. In this project, we will exploit highly sensitive evanescent wave Mid-IR spectroscopy using signal enhanced ATR chips and waveguide chips and will use machine learning approach for rapid early cancer diagnostics as well as therapy monitoring. In specific this project will involve the design and fabrication of highly sensitive disposable ATR and waveguide chips optimised for cancer (breast and ovarian) biomarker sensing. The fabricated chips will be utilised for Mid-IR spectroscopy of blood plasma samples obtained from our collaborators from Cancer Research UK at Cambridge University and the results will be analysed using machine learning and deep learning algorithms specifically developed for this purpose.