OCT and OCTA image processing for retinal assessment of people with MS

用于多发性硬化症患者视网膜评估的 OCT 和 OCTA 图像处理

• 批准号: 10357873
• 负责人: Jerry L Prince
• 金额: $ 44.1万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10357873
• 关键词: Address; Affect; Algorithmic Analysis; Algorithms; Anatomy; Angiography; Bayesian Modeling; Behavior; Biological; Biological Markers; Central Nervous System Diseases; Clinic; Clinical; Communities; Computational algorithm; Computer software; Computers; Data; Development; Diagnosis; Disease; Disease Management; Disease Progression; Endothelium; Equilibrium; Esthesia; Evaluation; Event; Eye; Eye diseases; Failure; Foundations; Four-dimensional; Future; Grant; Graph; Image; Imaging Device; Individual; Language; Learning; Literature; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Measurement; Measures; Methodology; Methods; Modeling; Monitor; Morphologic artifacts; Multiple Sclerosis; Muscular Atrophy; Neurodegenerative Disorders; Optical Coherence Tomography; Persons; Play; Process; Relapse; Research; Retina; Role; Sampling; Scanning; Severities; Source; Spinal Cord Lesions; Technology; Testing; Text; Thick; Thinness; Time; Training; Variant; Vision; Visit; advanced disease; automated algorithm; base; burden of illness; cerebral atrophy; cohort; convolutional neural network; cost; deep learning; density; diagnostic tool; disability; efficacy evaluation; experience; ganglion cell; gray matter; image processing; imaging Segmentation; imaging biomarker; imaging modality; improved; insight; learning progression; macula; macular edema; magnetic resonance imaging biomarker; nervous system disorder; novel; novel diagnostics; open source; portability; random forest; recursive neural network; research clinical testing; retina blood vessel structure; retinal imaging; segmentation algorithm; three dimensional structure; tool; treatment choice; white matter

Project Summary/Abstract (Max 30 lines of text) Although magnetic resonance imaging (MRI) is necessary for diagnosing multiple sclerosis (MS), it has been challenging to acquire consistent MRI measurements of MS disease burden. Spectral domain optical coherence tomography (OCT) of the retina has emerged as a complementary source of imaging biomarkers, wherein retinal thickness measurements have been shown to correlate well with MS disease burden. As well, OCT angiography (OCTA)—a new imaging modality acquired with the same OCT scanner—yields multiple new biomarkers among which macular vessel density has been shown to correlate with MS disability. There is strong evidence that OCT and OCTA may provide much needed imaging biomarkers for MS, but there are remaining technical challenges to overcome. Many algorithms for computation of retinal layer thicknesses from OCT images have been developed, but measurement of longitudinal changes in individual MS subjects remains highly challenging, especially in MS where yearly changes are small relative to intrinsic measurement variations. We propose a novel iterative registration and deep learning segmentation algorithm for longitudinal OCT retinal image segmentation. Development of automatic algorithms for analysis of OCTA images is in an early stage and there are opportunities for significant improvements. We will develop a deep network for OCTA vessel segmentation and biomarker computation that both suppresses artifacts that are common in OCTA and provides consistent results across different scanners. As both OCT and OCTA become more widely used in the characterization and management of MS, it is becoming increasingly important to jointly characterize these biomarkers and relate them to disease status, which is currently characterized largely by clinical evaluations. We will address the central question of whether OCT and OCTA can be used to predict disease progression by developing a new disease progression score for MS based on multiple OCT and OCTA measurements as well as clinical and MRI biomarkers, acquired in both single and multiple imaging visits. The proposed research will: 1) Develop a fast, topologically-correct longitudinal segmentation method for the macula; 2) Develop a method for artifact-suppressed and consistent computation of OCTA features in the macula; 3) Develop a disease progression score to jointly characterize longitudinal retinal OCT and OCTA measurements in MS; and 4) Carry out longitudinal studies of healthy controls and people with MS using OCT and OCTA measurements. We will assess whether average features within the macula or features averaged over smaller segments yield better estimates of progression. We will also assess whether OCT alone or OCT together with OCTA provide better estimates of progression. Image processing and disease progression algorithms will be made freely available to the research community. The proposed research will greatly advance the use of OCT and OCTA in characterizing longitudinal changes in the retina, potentially leading to standard eye measurements for monitoring and managing MS and other neurological and eye diseases.

项目摘要/摘要(最多30行文本) 虽然磁共振成像(MRI)对于诊断多发性硬化症(MS)是必要的，但它已经被 获得一致的多发性硬化症疾病负担的MRI测量具有挑战性。光谱域光学 视网膜的相干断层扫描(OCT)已经成为成像生物标志物的补充来源， 其中视网膜厚度测量已被证明与MS疾病负担很好地相关。也是, OCT血管造影术(OCTA)--一种用同一OCT扫描仪获取的新成像方式--产生多个 新的生物标志物，其中黄斑血管密度已被证明与多发性硬化症残疾相关。的确有 强有力的证据表明，OCT和OCTA可能为多发性硬化症提供急需的成像生物标志物，但有 仍然存在需要克服的技术挑战。计算视网膜层厚度的多种算法 已经开发了OCT图像，但测量单个MS受试者的纵向变化 仍然具有极大的挑战性，特别是在MS中，相对于内在衡量标准来说，每年的变化很小 变种。提出了一种新的迭代配准和深度学习的纵向分割算法 OCT视网膜图像分割。用于分析OCTA图像的自动算法的开发正在进行中 目前还处于早期阶段，并有重大改进的机会。我们将为OCTA开发一个深度网络 血管分割和生物标记物计算都抑制了OCTA和OCTA中常见的伪影 在不同的扫描仪上提供一致的结果。随着OCT和OCTA在 多发性硬化症的特征和管理，联合描述这些特征变得越来越重要 生物标记物与疾病状态有关，目前主要以临床评估为特征。 我们将解决OCT和OCTA是否可以通过以下方式预测疾病进展的核心问题 基于多个OCT和OCTA测量为MS开发新的疾病进展评分 作为临床和核磁共振生物标记物，在单次和多次影像检查中获得。拟议的研究将： 1)开发了一种快速的、拓扑正确的黄斑纵向分割方法；2)开发了一种方法 用于抑制伪影和一致地计算黄斑中的OCTA特征；3)发展为疾病 联合表征MS患者纵向视网膜OCT和OCTA测量的进展评分；以及 4)使用OCT和OCTA测量对健康对照和MS患者进行纵向研究。 我们将评估黄斑内的平均特征或较小片段上的平均特征是否产生 对进展的更好估计。我们还将评估OCT是单独提供还是与OCTA一起提供 对进展的更好估计。图像处理和疾病进展算法将免费进行 可供研究界使用。拟议的研究将极大地促进OCT和OCTA的使用 在描述视网膜的纵向变化时，潜在地导致标准的眼睛测量 监测和管理多发性硬化症以及其他神经和眼部疾病。