Chemometric histopathology via coherent Raman imaging for precision medicine (CHARM)

通过相干拉曼成像进行化学计量组织病理学精准医学 (CHARM)

• 批准号: 10033272
• 金额: $ 91.99万
• 依托单位: UNIVERSITY OF CAMBRIDGE
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10033272
• 关键词: Chemometric; histopathology; via; coherent; Raman

The CHARM project aims to radically transform the cancer diagnosing process and bring the emerging field of digital histopathology to the next level, introducing a novel technology for tissue analysis, capable to measure the molecular composition of the patient tissue samples and to recognize and classify the tumor in a completely label/stain-free way. The instrument, integrated with artificial intelligence (AI), will offer to histopathologists a reliable, fast and low-cost Clinical Decision Support System (CDSS) for cancer diagnosis and personalized cancer therapy. We will develop a Class C, (IVDR, In-Vitro Diagnostic Regulation) medical device consisting of a turnkey low-cost broadband Coherent Raman Scattering (CRS) microscope (enabled by our patented graphene-based fiber laser technology), named the Chemometric Pathology System (CPS), integrating an AI module based on deep learning, statistics and machine learning. The CPS will be capable of automatically analyzing unstained tissues, providing fast and accurate tumour identification (differentiating normal vs neoplastic tissues) with accuracy >98% and final tumour diagnosis prediction (differentiating and grading histologic subtypes) with accuracy >90%, thus offering to the histopathologist a decision tree compatible with existing clinical protocols but with biomolecularbased objectivity and reduced time to result (TRL6). We will develop a robust business case for the application and ensure the project continuation to higher TRLs and the final market entrance. This proposal builds on the results of the ERC POC project GSYNCOR.no project summary.

魅力项目旨在从根本上改变癌症诊断过程，并将数字组织病理学的新兴领域提升到新的水平，引入一种新型的组织分析技术，能够测量患者组织样品的分子组成，并以完全无标记的无标记的方式识别和识别和分类肿瘤。该仪器与人工智能（AI）整合在一起，将为组织病理学家提供可靠，快速和低成本的临床决策支持系统（CDSS），用于癌症诊断和个性化癌症治疗。我们将开发C类（IVDR，IVDR，IN-VITRO诊断调节）医疗设备，该设备由Turnkey低成本宽带连贯的拉曼散射（CRS）显微镜组成（由我们的基于专利的石墨烯基纤维激光技术启用），命名为Chemotemittric Pathology System（CPS），将基于AI模块集成了基于深度学习的AI模块。 CP将能够自动分析未染色的组织，以> 98％的准确性> 98％和最终的肿瘤诊断预测（与精确的肿瘤诊断预测（与精确的组织学亚型）相分化> 90％，从而与现有的临床临床疗法相反，从而提供了快速准确的肿瘤识别（与正常与肿瘤组织区分与肿瘤组织的区分），从而提供了临床疗法的临床疗法，从而提供了临床疗法的重置，从而提供了预测（与肿瘤组织相差）（相差和评分）结果（TRL6）。我们将为应用程序开发一个强大的业务案例，并确保该项目延续到更高的TRL和最终的市场入口。该建议基于ERC POC项目Gsyncor.NO项目摘要的结果。