Label-free, high resolution, functional, two-photon imaging for non-invasive early cancer detection

用于非侵入性早期癌症检测的无标记、高分辨率、功能性双光子成像

• 批准号: 9811585
• 负责人: IRENE GEORGAKOUDI
• 金额: $ 7.5万
• 依托单位: TUFTS UNIVERSITY MEDFORD
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9811585
• 关键词: Algorithms; Benign; Biological Markers; Biomechanics; Biometry; Biopsy; Bladder; Cancer Detection; Cancer Diagnostics; Cancer Patient; Carcinoma; Cells; Cervical; Cervix Uteri; Cessation of life; Characteristics; Clinical; Clinical Treatment; Collagen; Collagen Fiber; Colon; Colposcopy; Data Set; Detection; Developed Countries; Developing Countries; Development; Diagnosis; Diagnostic; Diagnostic Imaging; Discriminant Analysis; Disease; Early Diagnosis; Epithelial; Epithelium; Esophagus; Evaluation; Fiber; Fluorescence; Functional Imaging; Future; Generations; Goals; Gold; Hand; Histopathology; Human; Human Papilloma Virus Vaccine; Hysterectomy; Image; Image Analysis; Imagery; Incidence; Inflammation; Label; Lesion; Loop electrosurgical excision procedure; Malignant Neoplasms; Measurement; Metabolic; Metaplasia; Methods; Mitochondria; Morphology; NADH; Nature; Nuclear; Optics; Oral cavity; Organ; Outcome; Oxidation-Reduction; Patients; Performance; Premalignant; Process; Property; Protocols documentation; Reporting; Resolution; Screening for cancer; Signal Transduction; Specificity; Specimen; Structure; Testing; Time; Tissue imaging; Tissues; Translations; Variant; base; cancer diagnosis; clinical Diagnosis; cost; crosslink; diagnosis standard; experience; fluorescence imaging; human imaging; imaging platform; imaging system; improved; in vivo; in vivo imaging; indexing; innovation; insight; microscopic imaging; non-invasive imaging; novel therapeutics; psychologic; quantitative imaging; second harmonic; second harmonic generation imaging; skin lesion; tissue biomarkers; two-photon

PROJECT SUMMARY Established methods for early cancer detection rely on simple tissue visualization methods, accompanied by biopsy and histopathological evaluation, which is primarily based on morphological tissue features. These approaches are inaccurate or inefficient. Our long-term objective is to transform pre- and early epithelial cancer diagnosis through the use of functional metabolic, morphological and biomechanical tissue biomarkers that are extracted non-invasively, automatically and in near real time from fiber-probe-based endogenous two-photon images. Endogenous two-photon imaging is uniquely capable to provide label-free, functional, high resolution tissue images. In this proposal, we aim to establish and validate such measurements and biomarkers for the detection of human cervical pre-cancers using freshly excised tissues. The cervix is an ideal organ for developing and testing our approach as it relaxes some of the size limitations presented for endoscopic applications, enabling us to focus on demonstrating the principles of this innovative platform. In addition, we expect that our proposed methods will enable significant improvements in the specificity of detection of cervical pre-cancers. To achieve our goals, we will acquire images from fifty freshly excised human cervical tissue specimens from patients undergoing colposcopy, loop electrosurgical excision procedure, or hysterectomy. We will acquire endogenous two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) images and extract signals attributed to NADH, FAD, and collagen. We will process these images using methods we developed to assess: a) the depth-dependent optical redox ratio, mitochondrial organization and nuclear to cytoplasmic ratio variations from FAD and NADH TPEF images of the epithelium, and b) the collagen fiber organization and crosslinking from SHG and TPEF images of the stroma. We will use discriminant analysis to develop algorithms that include the optimal combination of the extracted optical parameters to distinguish high- grade from non-high grade cervical lesions, relying on histopathology as the gold standard. Our algorithms will be entirely automated and fast and will yield a diagnosis based on functional tissue characteristics. Thus, we expect that results from this study will motivate the development of a probe-based 2P imaging system for clinical in vivo imaging translation to enable real-time, highly accurate detection of cervical pre-cancerous lesions. Ultimately, we anticipate that probe-based 2P imaging will transform early cancer diagnosis for a wide range of tissues, such as the oral cavity, the esophagus, the colon, and the bladder.

项目摘要 已建立的早期癌症检测方法依赖于简单的组织可视化方法， 活检和组织病理学评估，主要基于组织形态特征。这些 方法不准确或效率低下。我们的长期目标是将前期和早期上皮癌 通过使用功能性代谢、形态学和生物力学组织生物标志物进行诊断， 从基于光纤探针的内源性双光子中无创、自动和接近真实的时间地提取 图像.内源性双光子成像是唯一能够提供无标记，功能，高分辨率 组织图像。在这项提案中，我们的目标是建立和验证这种测量和生物标志物， 使用新鲜切除的组织检测人宫颈癌前病变。子宫颈是发育的理想器官 并测试我们的方法，因为它放宽了内窥镜应用的一些尺寸限制， 使我们能够专注于展示这个创新平台的原则。此外，我们预计， 所提出的方法将能够显著提高宫颈癌前病变检测的特异性。到 为了实现我们的目标，我们将从50个新鲜切除的人类宫颈组织标本中获取图像， 接受阴道镜检查、环形电切除术或子宫切除术的患者。我们将获得 内源性双光子激发荧光（TPEF）和二次谐波产生（SHG）图像， 提取归因于NADH、FAD和胶原蛋白的信号。我们将处理这些图像使用的方法， 开发评估：a）深度依赖的光学氧化还原比，线粒体组织和核， 来自上皮的FAD和NADH TPEF图像的细胞质比率变化，和B）胶原纤维 组织和交联从SHG和TPEF图像的基质。我们将使用判别分析， 开发算法，包括提取的光学参数的最佳组合，以区分高， 从非高级别宫颈病变中区分高级别宫颈病变，依靠组织病理学作为金标准。我们的算法将 完全自动化和快速，并将产生基于功能组织特征的诊断。因此我们 我希望这项研究的结果将推动基于探头的2P成像系统的发展，用于临床 体内成像转换，以实现宫颈癌前病变的实时、高度准确的检测。 最终，我们预计基于探针的2P成像将改变早期癌症诊断的广泛范围， 组织，如口腔、食道、结肠和膀胱。