Infrared Imaging for Diagnosis and Prediction of the Biopotental of Low and Intermediate Risk Prostate Cancer

在英国，每年有超过25万人被诊断患有癌症，其中四种最常见的癌症，乳腺癌，肺癌，肠癌和前列腺癌，占所有这些病例的一半以上。许多癌症，如前列腺癌，与年龄密切相关，77%的病例被诊断为55岁以上的男性。这产生了一个复合问题，因为西方人口正在迅速老龄化，而欧洲国家被诊断患有癌症的人数不可避免地会增加。这将给卫生保健系统的各个部分带来相当大的压力，并将对卫生保健费用产生巨大影响。这个问题在某些癌症中尤其具有先见之明，如前列腺癌和乳腺癌，这些癌症在老年人中是地方性的，在许多情况下其自然史是不确定的。显然，临床上需要一种稳健且优选自动化的系统，其不仅可以促进病理诊断，而且可以区分需要监测或较不积极治疗的低风险肿瘤和进展更快且需要积极干预以防止发病和死亡的高风险肿瘤。我们先前在小规模研究中已经表明，与算法模型结合使用的红外光谱标记物不仅可以用于提供肿瘤分级数据，而且可以提供分期和预后信息。红外光谱法辅助临床诊断的吸引力在于它是一种广为人知的技术，易于获得，可靠，使用简单且相对便宜。它还允许进一步的扫描后询问，因为它不会破坏正在研究的组织。然而，由于缺乏对一些基本原则的理解，临床环境的引入受到了阻碍。我们已经成功地解决了单细胞的许多基本问题，并旨在利用这些知识来解决组织活检的扫描问题。本提案的目的是开发使用癌症组织光谱分析的技术，该技术建立在我们的合作研究小组和该领域其他工作人员开发的强大科学基础之上。我们建议开发快速准确的分析系统，它可以应用于生物组织的识别和表征，我们将使用前列腺癌作为主要模型。使用前列腺癌作为我们的低风险和高风险疾病模型，我们将调整现有的技术和协议，使组织样本的快速高通量红外线筛查能够从研究实验室转移到标准病理实验室然后，我们将使用该系统开发一个模型，该模型可以区分先前被分级为低或中级前列腺癌并且具有已知结果的样本中的低风险和高风险前列腺癌。然后，使用大量的低和中级前列腺癌对该模型进行盲测，以评估该模型预测疾病结果的能力。光谱筛查的另一个好处是，高风险和低风险疾病之间的光谱差异的询问将指导研究新的分子标记物，这些分子标记物可以揭示肿瘤进展以及产生用于临床的新的分子诊断标记物。由于该技术是非破坏性的，任何新的标记物可以被测试回原来的组织，它是发现从。我们设想，该系统的开发和强大的测试将导致一个强大的诊断和预后的工具，可能会被纳入到肿瘤学的实践在实验室和诊所，它将有可能描述新的技术与实用程序在其他领域的生物健康和生物科学。

More than a quarter of a million people are diagnosed with cancer annually in the UK and the four most common ones, breast, lung, bowel and prostate cancer, make up over half of all these cases. Many, such as prostate cancer correlate strongly with age, 77% of cases being diagnosed in men over the age of 55. This produces a compound problem, as Western populations are ageing rapidly and the number of people diagnosed with cancer in European countries is inevitably going to rise. This will put a considerable strain on all parts of the health care systems and will have dramatic effects on health care costs. The problem is particularly prescient in certain cancers such as prostate cancer and breast cancer, which are endemic in the older population and whose natural history is uncertain in many cases. There is a clear clinical need for a robust and preferably automated system which can not only facilitate the pathological diagnosis but also to discriminate between tumours of low risk, which require surveillance or less aggressive treatment, and those of high risk, which will progress more rapidly and which need aggressive intervention to prevent morbidity and death. We have shown previously in small scale studies that infra red spectral markers used in conjunction with algorithmic models can be utilised not only to provide tumour grading data but also to provide staging and prognostic information. The attraction of infrared spectroscopy to aid clinical diagnosis is that it is a widely known technology which is readily available, reliable, simple to use and relatively inexpensive. It also allows further post scanning interrogation because it does not destroy the tissue under investigation. However, introduction into the clinical environment has been hampered by a lack of understanding of some of the fundamental principles. We have successfully addressed many of the fundamental issue with single cells and aim to utilize this knowledge to address scanning of tissue biopsiesThe aim of this proposal is to develop techniques using spectroscopic analysis of cancer tissue, which build on a strong scientific base developed by our collaborative research group and by others working in this field. We propose to develop rapid and accurate systems of analysis, which can be applied to the identification and characterisation of biological tissues and we will use prostate cancer as the primary model.Using prostate cancer as our model of low and high risk disease we will adapt existing technologies and protocols to enable rapid high throughput infra red screening of tissue samples which could be transferred from the research laboratory into a standard pathology laboratory. We will then use this system to develop a model, which can distinguish between low and high risk prostate cancers in samples that have been previously graded as low or intermediate grade prostate cancers and of known outcome. This model will then be blind tested using a large set of low and intermediate grade prostate cancers to assess the ability of the model to predict disease outcome. An added benefit of spectral screening is that interrogation of the spectral differences between high and low risk disease will direct research towards novel molecular markers that may shed light on tumour progression as well as generating new molecular diagnostic markers for use in the clinic. As the technique is non destructive any new markers identified can be tested back on the original tissue it was discovered from.We envision that development and robust testing of the system will lead to a powerful diagnostic and prognostic tool that may be incorporated in to oncological practice both in the laboratory and the clinic and that it will potentially describe new techniques with utility in other areas of bio-health and biological science.