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）是一种影响食管的慢性炎症性疾病， 呕吐、进食和吞咽困难的常见原因，包括儿童的食管食物嵌塞。 EoE难以使用白色实时诊断并与其他常见食管疾病区分 通过食管胃镜检查（EGD）程序进行的食管光内镜成像。 因此，临床医生依赖于在此过程中获得的多个随机食管活检， 组织学确认（金标准）。然而，由于EoE是一种斑片状疾病，即使多次活检也可能 不产生准确的结果。这可能导致诊断延迟和无效治疗，并导致 可预防的并发症，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，可以快速调查食管的更多区域， 原位，并提供组织特异性炎症生物标志物信息用于实时鉴定EoE。拉曼 光谱学（RS）是一种这样的技术，其可以提供解决方案，因为它依赖于光与光的相互作用。 分子，以提供样品内的生物化学和分子组成的独特“指纹”。 秒因此，通过内窥镜的RS特别适合于活性EoE的实时生化评估。 该建议，提出了发展和评估的深度特定的双波长拉曼 内窥镜，以表征食管内的生化和水的变化，因为它涉及到活跃的EoE。 为了实现这些目标，拉曼生物标志物将在空间上被表征和识别，并与 体内以及离体EoE的已知生物标志物。将使用修改后的 基于组织光学特性优化探头设计的蒙特卡罗模拟。离体非线性成像 结合拉曼图，将对EGD程序期间获得的活检样本子集进行成像， 进一步研究关键生物标志物的空间分布并帮助指导内窥镜拉曼探针设计。这 将使用光学组织模型和体内患者测量来评价探针。最后，一台机器 学习分类算法将被优化和评估，以提供一种机制，通过该机制，在体内RS 光谱可以被分类为活动EoE、非活动EoE、GERD（即，酸反流病）和其他非EoE 控制此外，我们的目标是跟踪病人的反应，治疗和评估拉曼光谱的变化， 时间来确定使用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用于实时检测和监测的新型诊断工具 在儿科病例中的EoE。