A multicenter study in bronchoscopy combining Stimulated Raman Histology with Artificial intelligence for rapid lung cancer detection - The ON-SITE study

支气管镜检查结合受激拉曼组织学与人工智能快速检测肺癌的多中心研究 - ON-SITE 研究

• 批准号: 10698382
• 负责人: Allen Cole Burks
• 金额: $ 94.53万
• 依托单位: INVENIO IMAGING INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10698382
• 关键词: Ablation; Address; Algorithms; Area Under Curve; Artificial Intelligence; Biomedical Engineering; Biopsy; Biopsy Specimen; Brain Neoplasms; Bronchoscopy; Cancer Detection; Cancer Patient; Cells; Certification; Cessation of life; Classification; Clinical; DNA Sequence Alteration; Data Set; Detection; Development; Devices; Diagnosis; Diagnostic; Disease; Epidermal Growth Factor Receptor; Evaluation; Forcep; Future; Grant; Hilar; Histology; Image; Image Analysis; Institution; KRAS2 gene; Location; Lung; Lung nodule; Malignant Neoplasms; Malignant neoplasm of lung; Mediastinal; Medical Device; Medicine; Modality; Molecular; Molecular Diagnosis; Molecular Profiling; Multicenter Studies; Mutation; Nature; Needles; Outcome; Pathologic; Pathologist; Pathology; Patients; Performance; Peripheral; Pharmacologic Substance; Procedures; ROC Curve; Research Design; Sampling; Science; Site; Specificity; System; Testing; Time; Tissues; Training; Translating; Validation; aspirate; cost; deep learning; deep learning algorithm; low dose computed tomography; lung imaging; lung lesion; lymph nodes; meetings; microscopic imaging; molecular marker; next generation sequencing; participant enrollment; prognostic; programmed cell death ligand 1; screening program; standard of care; tool; treatment planning

Project Summary & Abstract Lung cancer accounts for about 25% of all cancer deaths in the US, as it is often caught at an advanced stage when treatment options are limited. This has led to the institution of screening programs with low-dose CT, resulting in ~1.6 million pulmonary nodules detected every year, most of them (~80%) in the periphery of the lung. Tissue biopsy is the standard of care for establishing a definitive diagnosis for treatment planning. Rapid on-site evaluation (ROSE) of tissue biopsies in the procedure room by cytopathologists or cytotechnicians can be used to establish that: 1. Diagnostic quality tissue has been procured; identifying malignancy by ROSE has been shown to reduce the number of biopsy tools and repeat procedures 2. An adequate number of cells have been obtained to allow molecular profiling by next- generation sequencing and molecular testing 3. The absence of metastatic disease in the lymph nodes justifies the more-invasive peripheral biopsy. Nevertheless, ROSE is not the standard of care despite its advantages, because its quality is highly variable across sites, it can increase procedure times, and its costs are unlikely to be fully reimbursed. We propose the development of an FDA-cleared medical device that allows microscopic imaging of fresh, unprocessed tissue biopsies in the treatment room and provides accurate, near real-time diagnosis based on deep learning. Specifically, the proposed system uses Stimulated Raman Histology (SRH), which was pioneered by the PI, translated for intraoperative diagnosis in brain tumors, shown to be suitable for automated diagnosis via deep learning with a performance that is non-inferior to pathologists, and resulted in the first CE-certified device for identification of brain tumor margins by the company. Here, we address an urgent clinical need in lung cancer, giving doctors confidence in their intraoperative decisions, and reducing unnecessary biopsies/procedures for patients and payers. Further, we will investigate the potential to provide accurate intraoperative diagnosis of molecular markers that could enable local delivery of pharmaceuticals, ablation, and other therapies, in the biopsy procedure.

项目摘要和摘要 肺癌约占美国所有癌症死亡的25％，因为它经常被捕 治疗选择有限的高级阶段。这导致了筛查机构 低剂量CT的程序，每年检测到约160万个肺结核， 其中大多数（〜80％）在肺的周围。 组织活检是建立明确诊断治疗的护理标准 规划。在手术室中对组织活检的快速现场评估（玫瑰）通过 可以使用细胞病理学家或细胞技术医生来确定： 1。已经采购了诊断质量组织；通过玫瑰识别恶性肿瘤 显示以减少活检工具和重复程序的数量 2。已经获得了足够数量的细胞，可以通过接下来的分子分析 生成测序和分子测试 3。淋巴结中没有转移性疾病证明了更多的侵入性 周围活检。 尽管如此，尽管它具有优势，但罗斯并不是护理的标准，因为它的质量是 跨站点的高度变化，它可以增加程序时间，并且其成本不太可能完全 报销。我们建议开发FDA已清理医疗设备，该设备允许 治疗室中新鲜，未加工的组织活检的微观成像，并提供 基于深度学习的准确，接近实时诊断。 具体而言，拟议的系统使用刺激的拉曼组织学（SRH），这是 由PI开创，翻译为脑肿瘤的术中诊断，证明是合适的 通过深度学习进行自动诊断，表现不属于 病理学家，并为识别脑肿瘤缘的第一个CE认证的装置提供了 由公司。在这里，我们解决了肺癌的紧急临床需求，给医生提供 对他们的术中决策充满信心，并减少不必要的活检/程序 病人和付款人。 此外，我们将研究提供准确的术中诊断的潜力 可以局部递送药物，消融和其他的分子标记物 疗法，活检程序。