Validating Automated Photoreceptor Analytics Software For Degenerative Eye Disease Research and Biopharma Clinical Trials.

验证用于退行性眼病研究和生物制药临床试验的自动光感受器分析软件。

• 批准号: 9918805
• 负责人: Eric L. Buckland
• 金额: $ 72.66万
• 依托单位: TRANSLATIONAL IMAGING INNOVATIONS, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9918805
• 关键词: Adoption; Affect; Algorithms; Biological Markers; Blindness; Blood Vessels; Cell Therapy; Clinical; Clinical Trials; Collaborations; Computer software; Cone; Consent; Data; Databases; Degenerative Disorder; Detection; Development; Diagnostic; Disease; Disease Progression; Eye diseases; Foundations; Funding; Gender; Goals; Health; Healthcare; Housing; Image; Imaging Device; Industrialization; Influentials; Inherited; Institution; Legal patent; Licensing; Manuals; Masks; Measures; Mosaicism; Multicenter Trials; Nerve Degeneration; Ophthalmoscopy; Optical Coherence Tomography; Outcome; Output; Patients; Phase; Photoreceptors; Positioning Attribute; Privacy; Prognostic Marker; Publishing; Qualifying; Reading; Reproducibility; Research; Retina; Retinal Degeneration; Retinal Diseases; Signal Transduction; Small Business Innovation Research Grant; Software Tools; Structure; Technology; Testing; Time; Translations; Treatment Efficacy; Validation; Vision; Wisconsin; adaptive optics; analytical tool; automated algorithm; base; clinical efficacy; comparative; effective therapy; experience; fighting; fovea centralis; fundus imaging; gene therapy; image guided; imaging modality; imaging program; innovation; interest; medical schools; microsystems; ocular imaging; programs; retinal imaging; screening; statistics; stem cell therapy; therapy development; tool

ABSTRACT Neurodegeneration is implicated in almost all major causes of retinal vision loss and specifically in inherited degenerative eye disease. While visual function tests and major imaging modalities, such optical coherence tomography, are favored diagnostic and treatment management tools for symptomatic patients, these clinical tools are unsatisfactory as prognostic indicators or as endpoints for judging clinical efficacy of new preventative and restorative therapies (e.g., neuro-protectives, gene therapies, or stem cell therapies) that operate at the cellular level in the retina. Adaptive optics (AO) ophthalmoscopy has emerged as a sensitive marker of the presence and viability of photoreceptors; however, there are no validated algorithms or objective quantitative measures based on AO fundus images and there are no representative image databases upon which to base screening judgements. In this Direct-to-Phase II SBIR, Translational Imaging Innovations (TII) and Prof. Joseph Carroll, Director of the Advanced Ocular Imaging Program (AOIP), Medical College of Wisconsin (MCW), will validate and commercialize an Automated Photoreceptor Analytics Software for Degenerative Eye Disease. This platform will leverage Mosaic Analytics (MOSAIC), an automated photoreceptor analysis package developed at MCW, and the AOIP Image Bank, which houses images and data on 1578 subjects - 336 normals and the remainder afflicted with one or more of 100 retinal diseases. MOSAIC will unlock the latent value of AO-enhanced ophthalmoscopy to provide a reliable, objective, direct measure of photoreceptor health, and provide quantitative endpoints for assessing the clinical efficacy of cellular therapies. To achieve this goal, we will propose four aims: (a) Strengthen the Photoreceptor Processing Algorithm(s) through a priori image Quality Metrics and a posteriori Confidence Metrics, adoption of Subtractive Regions of Interest, and algorithm tuning to retinal Domains of Interest; (b) Validate the Algorithm(s) for Computing an array of Objective Quantitative Biomarkers; (c) Establish a Proper Context of Use for Qualifying an Objective Clinical Trial Endpoint within the FDA MDDT program; and (d) Publish the first Normative Reference Database for Quantitative Photoreceptor Biomarkers in healthy/diseased eyes. Our proposal fills an important technology gap in the field of retinal imaging. While the number and type of imaging devices continues to grow, the analytical tools to assess and manage images from these devices have not developed in parallel. As such, the diagnostic potential of these exquisite imaging devices remains unrealized. The validation of quantitative adaptive optics biomarkers will increase confidence in the outcome of clinical trials and reduce time to market for new cellular therapies. The reliability, reproducibility, and ease of use of MOSAIC will catalyze the adoption of adaptive optics fundus imaging and accelerated the development of therapies for blinding degenerative diseases.

抽象的 神经变性几乎与视网膜视力丧失的所有主要原因有关，尤其是继承 退化性眼病。视觉功能测试和主要成像方式，这种光学相干断层扫描，但 是有症状患者的诊断和治疗管理工具，这些临床工具不令人满意 作为预后指标或作为判断新预防性和恢复性疗法的临床功效的终点（例如， 在视网膜中细胞水平起作用的神经保护剂，基因​​疗法或干细胞疗法。自适应光学器件 （AO）眼镜检查已成为光感受器的存在和生存能力的敏感标记。然而， 没有基于AO眼镜图像的算法或客观定量措施，没有 代表性的图像数据库，以筛选判断。在这个直接到相的II SBIR中，翻译 成像创新（TII）和高级眼成像计划（AOIP）主任约瑟夫·卡罗尔（Joseph Carroll）教授 威斯康星州学院（MCW）将验证和商业化自动化感受器分析软件 退化性眼病。 该平台将利用马赛克分析（Mosaic），这是一个自动化的光感受器分析软件包 MCW和AOIP图像库，其中包含1578名受试者的图像和数据-336正常和其余部分 患有100个视网膜疾病中的一个或多个。马赛克将解锁AO增强眼镜的潜在值 提供可靠，客观的直接衡量光感受器健康，并为 评估细胞疗法的临床功效。为了实现这一目标，我们将提出四个目标：（a）加强 通过先验图像质量指标和后验置信度指标，光感受器处理算法（S）， 采用利益的减法区域，并将算法调整到感兴趣的视网膜领域； （b）验证 用于计算一系列客观定量生物标志物的算法； （c）建立适当的使用环境 在FDA MDDT计划中鉴定客观的临床试验终点； （d）发布第一个规范 在健康/患病眼中的定量光感受器生物标志物的参考数据库。 我们的建议填补了视网膜成像领域的重要技术空白。而成像的数量和类型 设备不断增长，评估和管理这些设备图像的分析工具尚未开发 平行线。因此，这些精美的成像设备的诊断潜力仍然未实现。验证 定量自适应光学物质生物标志物将增加对临床试验结果的信心，并减少时间 新的细胞疗法市场。马赛克的可靠性，可重复性和易用性将催化采用 自适应光学底面成像，并加速了盲目疾病的疗法的发展。