Dual-wavelength endoscopic Raman probe for eosinophilic esophagitis

双波长内窥镜拉曼探头治疗嗜酸性食管炎

• 批准号: 10653201
• 负责人: Anita Mahadevan-Jansen
• 金额: $ 41.48万
• 依托单位: VANDERBILT UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10653201
• 关键词: Academic Medical Centers; Address; Affect; Allergens; Biochemical; Biochemical Markers; Biological Markers; Biopsy; Child; Childhood; Classification; Clinical; Computer Models; Consumption; Coupled; Custom; Deglutition; Detection; Development; Devices; Diagnosis; Disease; Disease Progression; Distress; Endoscopes; Endoscopy; Eosinophilic Esophagitis; Epithelium; Esophageal Diseases; Esophageal Tissue; Esophagogastroduodenoscopy; Esophagus; Fingerprint; Food; Gastroesophageal reflux disease; Glycogen; Goals; Growth; Histologic; Histology; Image; In Situ; Inflammation; Inflammatory; Institutional Review Boards; Light; Lipids; Maps; Measurement; Measures; Mediating; Metabolic; Methods; Microscope; Modeling; Molecular; Molecular Profiling; Monitor; Monte Carlo Method; Nature; Nucleic Acids; Operative Surgical Procedures; Optics; Outcome; Participant; Patients; Pediatric Hospitals; Performance; Prediction of Response to Therapy; Procedures; Process; Property; Proteins; Raman Spectrum Analysis; Schedule; Spatial Distribution; Specimen; Surveys; Symptoms; System; Techniques; Technology; Time; Tissues; Treatment outcome; United States; Visit; Vomiting; Water; chronic inflammatory disease; classification algorithm; data fusion; design; diagnosis standard; diagnostic tool; ex vivo imaging; feeding; imaging system; improved; in vivo; in-vivo diagnostics; ineffective therapies; inflammatory marker; light scattering; machine learning classification; multimodality; multiphoton microscopy; novel; novel diagnostics; patient response; pediatric patients; point of care; prospective test; response; time use; tissue biomarkers; tissue phantom; treatment response

Project Summary Eosinophilic esophagitis (EoE) is a chronic inflammatory disease affecting the esophagus, and one of the most common causes of vomiting, feeding and swallowing difficulties, including esophageal food impaction in children. EoE is difficult to diagnose and distinguish from other common esophageal diseases in real-time using white light endoscopic imaging of the esophagus conducted via an esophagogastroduodenoscopy (EGD) procedure. Therefore, clinicians rely on multiple random esophageal biopsies which is obtained during this procedure for histologic confirmation (gold standard). However, since EoE is a patchy disease even the multiple biopsies may not yield accurate results. This can lead to a delay in diagnosis and ineffective treatment, and result in preventable complications such as esophageal remodeling requiring surgical interventions. As such there is an urgent need to develop alternative diagnostic tools which can quickly survey more regions of the esophagus, in situ, and provide tissue-specific inflammatory biomarker information for real-time identification of EoE. Raman spectroscopy (RS) is one such technology that can provide a solution as it relies on light interaction with molecules to provide a unique “fingerprint” of the biochemical and molecular composition of a specimen within seconds. Therefore, RS via an endoscope is uniquely suited for real-time biochemical assessment of active EoE. This proposal, presents the development and assessment of a depth specific dual-wavelength Raman endoscope to characterize both biochemical and water changes within the esophagus as it relates to active EoE. To accomplish these goals, Raman biomarkers will be characterized and identified spatially and correlated with known biomarkers of EoE in vivo as well as ex vivo. Computational modeling will be performed using a modified Monte Carlo simulation to optimize probe design based on tissue optical properties. Ex vivo non-linear imaging coupled with Raman maps will be performed on a subset of biopsies, obtained during the EGD procedures, to further study the spatial distribution of key biomarkers and help guide the endoscopic Raman probe design. This probe will be evaluated using optical tissue phantoms and in vivo patient measurements. Finally, a machine learning classification algorithm will be optimized and evaluated to provide a mechanism by which in vivo RS spectra can be classified into active EoE, inactive EoE, GERD (i.e., acid reflux disease) and other non-EoE control. Furthermore, we aim to track patient’s response to treatment and assess Raman spectral changes over time to determine the feasibility of using RS to provide a predictive treatment outcome model. The successful completion of this proposal will yield a novel diagnostic tool for real-time detection and monitoring of EoE in pediatric cases.

项目摘要 嗜酸性食管炎（EOE）是一种影响食道的慢性炎性疾病，是最大的疾病之一 呕吐，喂养和吞咽困难的常见原因，包括儿童食管食品的影响。 EOE难以实时使用白色诊断和区分其他常见的食管疾病 通过食管胃刺核（EGD）进行的食道的光内窥镜成像。 因此，临床医生依靠多个随机的食管活检，在此过程中获得 组织学确认（黄金标准）。但是，由于EOE是一种斑驳的疾病，即使多个活检也可能 不能产生准确的结果。这可能导致诊断和无效治疗的延迟，并导致 可预防的并发症，例如需要手术干预的食管重塑。因此有一个 迫切需要开发替代诊断工具，这些工具可以快速调查食道的更多地区 原位，并提供组织特异性的炎症生物标志物信息，以实时鉴定EOE。拉曼 光谱法（RS）就是这样的技术，可以提供解决方案，因为它依赖于与光的相互作用 分子提供独特的“指纹”样本的生化和分子组成 秒。因此，通过内窥镜RS非常适合活性EOE的实时生化评估。 该提案介绍了深度特定双波长拉曼的开发和评估 内窥镜表征与活性EOE相关的食道内生化和水变化的表征。 为了实现这些目标，拉曼生物标志物将在空间上进行表征和识别 EOE在体内和体内的已知生物标志物。将使用修改后进行计算建模 蒙特卡洛模拟以基于组织光学特性优化探针设计。外体非线性成像 结合拉曼地图将在EGD程序期间获得的活检子集进行， 进一步研究关键生物标志物的空间分布，并有助于指导内窥镜拉曼探针设计。这 探针将使用光学组织幻像和体内患者测量进行评估。最后，一台机器 学习分类算法将得到优化和评估，以提供一种机制 光谱可以分为活动性EOE，无活性EOE，GERD（即酸反射疾病）和其他非EOE 控制。此外，我们旨在跟踪患者对治疗和评估的反应拉曼光谱变化 是时候确定使用RS提供预测治疗结果模型的可行性。 该提案的成功完成将产生一种新颖的诊断工具，用于实时检测和监视 小儿病例的EOE。