Depth-resolved Quantitative Multi-Modal Imaging for GI Cancer Detection

描述（由申请人提供）：肿瘤变化的早期检测仍然是临床癌症诊断和治疗的关键挑战。许多癌症起源于上皮层，例如胃肠道（GI）的上皮层。白光内窥镜引导的切除活检和组织病理学是目前胃肠道癌症诊断的金标准。然而，由于采样误差，它遭受高假阴性率。此外，在内镜消融治疗后，相当一部分（约10%- 30%）患者显示存在埋藏在新上皮下的化生或异型增生，这与癌症发展风险相关。目前的标准内窥镜技术无法检测到这些表面下病变。因此，迫切需要开发新的诊断工具，其可以评估跨粘膜深度的组织结构和分子信息，以改善对表面下癌症的检测，并评估病变的侵入深度。 由于癌症发展与形态学和分子学改变相关，因此能够对组织的形态学和分子生物标志物进行定量成像并在体内和真实的时间内评估病变的深度-范围而不需要组织切除的成像技术将是GI癌症诊断和治疗的重大进步。本申请的目的是开发新一代用于GI癌症检测的多模态深度分辨成像技术。该建议是建立在我们的新型多模态光学成像平台结合高分辨率光学相干断层扫描（OCT）和深度分辨高灵敏度荧光层状光学断层扫描（FLOT）的同时结构和分子成像。我们对动物模型的多模态成像的广泛初步数据证明了同时定量成像结构和分子信息的可行性，以获得更准确的诊断和预后。为了建立OCT/FLOT对GI癌症检测的诊断能力，我们建议进行探索性/开发性研究（R21），以实现三个特定目标：1）使用OCT/FLOT对GI癌症动物模型进行成像，并获得相关的组织病理学诊断。2)从共配准OCT/FLOT图像中开发定量结构和分子成像参数，用于多参数分析。3)建立OCT/FLOT用于GI癌症检测的灵敏度、特异性和诊断准确性，并测试与单一模态相比使用组合信息增强癌症检测的假设。如果成功，该项目将产生一种全新的非侵入性多模态成像技术，用于改善GI癌症检测，该技术可以很容易地转化为GI诊所的内窥镜成像。预计它将对GI癌症以及各种上皮癌的检测、诊断和表征产生重大影响。 公共卫生相关性：早期发现肿瘤变化，特别是那些隐藏在表面之下的肿瘤变化仍然是临床癌症诊断和胃肠道（GI）治疗的关键挑战。本申请的目的是开发新一代多模态深度分辨成像技术，用于深度分辨结构和分子成像，以增强GI癌症检测。如果成功，该项目将产生一种新的非侵入性多模态成像技术，可以很容易地转化为胃肠道癌症以及各种上皮癌的内窥镜成像。

DESCRIPTION (provided by applicant): Early detection of neoplastic changes remains a critical challenge in clinical cancer diagnosis and treatment. Many cancers arise from epithelial layers such as those of the gastrointestinal (GI) tract. White-light endoscopy guided excisional biopsy and histopathology is currently the gold standard for GI cancer diagnosis. However, it suffers from high false negative rates due to the sampling errors. Furthermore, a significant portion (~10%- 30%) of patients after endoscopic ablative therapeutic treatment showed the presence of metaplasia or dysplasia buried underneath the neo-epithelium, which is associated with the risk of cancer development. Current standard endoscopic technology is unable to detect those subsurface lesions. Therefore, there is a critical need for developing new diagnostic tools which can assess tissue architectural and molecular information across the mucosal depth for improved detection of subsurface cancer, and evaluate the invasion depth of a lesion. Since cancer development is associated with in both morphological and molecular alterations, an imaging technology that can quantitative image tissue's morphological and molecular biomarkers and assess the depth- extent of a lesion in vivo and in real time, without the need for tissue excision, would be a major advance in GI cancer diagnostics and therapy. The objective of this application is to develop a new generation of multi-modal depth-resolved imaging technology for GI cancer detection. This proposal is built upon our novel multi-modal optical imaging platform combining high-resolution optical coherence tomography (OCT) and depth-resolved high-sensitivity fluorescence laminar optical tomography (FLOT) for simultaneous structural and molecular imaging. Our extensive preliminary data on multi-modal imaging of animal models demonstrates the feasibility for simultaneous quantitative imaging of structural and molecular information for more accurate diagnosis and prognosis. To establish the diagnostic ability of OCT/FLOT for GI cancer detection, we propose to pursue an Exploratory/Developmental Research (R21) to pursue three specific aims: 1) Image an animal model of GI cancer using OCT/FLOT and obtain the correlated histopathological diagnosis. 2) Develop quantitative structural and molecular imaging parameters from co-registered OCT/FLOT images for multi-parametric analysis. 3) Establish the sensitivity, specificity, and diagnostic accuracy of OCT/FLOT for GI cancer detection, and test the hypothesis of enhanced cancer detection using combined information compared to single modality alone. If successful, this project will result in a fundamentally new non-invasive multi-modal imaging technology for improved GI cancer detection, which can be readily translated into endoscopic imaging in the GI clinics. It is expected to have a major impact on detection, diagnosis, and characterization of GI cancers, as well as a wide range of epithelial cancers. PUBLIC HEALTH RELEVANCE: Early detection of neoplastic changes especially those buried underneath the surface remains a critical challenge in clinical cancer diagnosis and treatment of the gastrointestinal (GI) tract. The objective of this application is to develop a new generation of multi-modal depth-resolved imaging technology for depth- resolved structural and molecular imaging for enhanced GI cancer detection. If successful, this project will result in a new non-invasive multi-modal imaging technology that can be readily translated into endoscopic imaging of GI cancers, as well as a wide range of epithelial cancers.