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 早期癌症检测的既定方法取决于简单的组织可视化方法，并伴随 活检和组织病理学评估主要基于形态组织特征。这些 方法不准确或效率低下。我们的长期目标是改变前和早期上皮癌 通过使用功能代谢，形态学和生物力学组织生物标志物的诊断 从基于纤维探针的内源性两光子中，非侵入性，自动和几乎实时提取 图像。内源性两光子成像具有独特的能力，能够提供无标签，功能性高分辨率 组织图像。在此提案中，我们旨在建立和验证此类测量和生物标志物 使用新鲜切除的组织检测人宫颈前癌。子宫颈是发展的理想器官 并测试我们的方法，因为它放松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理。此外，我们希望我们的 提出的方法将使宫颈前癌检测的特异性有显着改善。到 实现我们的目标，我们将从五十个新鲜切除的人类宫颈组织标本中获取图像 进行阴道镜检查，循环电外科切除手术或子宫切除术的患者。我们将获得 内源性两光激发荧光（TPEF）和第二个谐波生成（SHG）图像，以及 提取信号归因于NADH，FAD和胶原蛋白。我们将使用方法处理这些图像 开发以评估：a）深度依赖性的光学氧化还原比，线粒体组织和核与核 上皮的FAD和NADH TPEF图像的细胞质比变化，b）胶原蛋白纤维 基质的SHG和TPEF图像的组织和交联。我们将使用判别分析进行 开发算法，包括提取的光学参数的最佳组合，以区分高 依靠组织病理学作为黄金标准的非高级宫颈病变的等级。我们的算法会 完全自动化和快速，并将基于功能组织特征产生诊断。因此，我们 期望这项研究的结果将激发基于探针的2p成像系统的开发 体内成像翻译以实现实时，高度准确的颈椎前病变。 最终，我们预计基于探针的2p成像将改变早期的癌症诊断 组织，例如口腔，食道，结肠和膀胱。