3D Image Analysis Approach to Determine Severity and Cause of Optic Nerve Edema

3D 图像分析方法确定视神经水肿的严重程度和原因

• 批准号: 8652462
• 负责人: MONA K. GARVIN
• 金额: $ 33.3万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-05-01 至 2018-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8652462
• 关键词: Acute; Algorithms; Blindness; Bruch' s basal membrane structure; Clinical; Clinical assessments; Computer software; Computing Methodologies; Data; Development; Diagnosis; Diagnostic Procedure; Dimensions; Disease; Early Diagnosis; Edema; Evaluation; Eye diseases; Fundus; Goals; Graph; Image; Imaging Techniques; Intracranial Hypertension; Knowledge; Machine Learning; Measurement; Measures; Methodology; Methods; Mission; Modality; Monitor; Nerve Fibers; Optic Disk; Optic Nerve; Optical Coherence Tomography; Papilledema; Patients; Process; Public Health; Relative (related person); Research; Resolution; Severities; Shapes; Staging; Structure; Swelling; Techniques; Testing; Thick; Three-Dimensional Image; Time; Vision; Work; base; cost; digital; disability burden; expectation; improved; innovation; instrument; novel; optic nerve disorder; public health relevance

DESCRIPTION (provided by applicant): Currently, the clinical assessment of optic nerve swelling is limited by the subjective ophthalmoscopic evaluation by experts in order to diagnose and differentiate the cause of the optic disc edema. The long-term goal of our research effort is to develop automated 3D image-analysis approaches for the identification of an optimal set of 3D parameters to quantify the severity of optic nerve edema over time and to help differentiate the underlying cause. The overall objective in this application is to develop strategies, using spectral-domain optical coherence tomography (SD-OCT), to rapidly and accurately determine the severity of optic nerve swelling in patients diagnosed with papilledema and to ascertain morphological features that differentiate papilledema from other disorders causing optic nerve edema. The central hypothesis is that information about volumetric and shape parameters obtainable from 3D image analysis techniques will improve the ability to accurately assess the severity and cause of optic disc edema over the existing subjective ophthalmoscopic assessment of optic nerve swelling using the Fris¿n scale or current 2D OCT parameters. The rationale for the proposed research is that having such 3D parameters will dramatically improve the way optic disc swelling is assessed. The following specific aims will be pursued: 1. Develop and evaluate the methodology for computing novel volumetric and shape parameters of a swollen optic nerve head from SD-OCT. This will be completed by refining and evaluating our novel 3D graph-based segmentation algorithms in SD-OCT volumes of patients with optic disc swelling. 2. Identify SD-OCT parameters that optimally correlate with clinical measurements of severity in patients with papilledema and develop a continuous severity scale. This will be accomplished by using machine-learning approaches to relate SD-OCT parameters to expert-defined Fris¿n scale grades (a fundus-based measure of severity). It is anticipated that volumetric 3D parameters will more closely correlate with clinical measures than 2D parameters and will provide a continuous severity scale. 3. Identify SD-OCT parameters that differentiate papilledema from other causes of optic disc swelling (or apparent optic disc swelling, as in pseudopapilledema) and develop a corresponding predictive classifier. Our working hypothesis is that 3D shape parameters, especially those near Bruch's membrane opening, will contribute the most in the automatic differentiation process. The approach is innovative because the 3D image-analysis methodology developed by the applicants enables novel determination of 3D volumetric and shape parameters and represents a significant improvement over the status quo of using qualitative image information and 2D OCT image information for assessing optic disc swelling. The proposed research is significant because it will help to establish a much-needed alternative and more objective method by which to assess the severity and cause of optic disc swelling.

描述（申请人提供）：目前，视神经肿胀的临床评估仅限于专家主观检眼镜评估，以诊断和区分视盘水肿的原因。我们研究工作的长期目标是：开发自动 3D 图像分析方法，用于识别一组最佳 3D 参数，以量化视神经水肿随时间变化的严重程度，并帮助区分根本原因。该应用的总体目标是使用以下方法制定策略。谱域光学相干断层扫描（SD-OCT），快速准确地确定诊断为视乳头水肿的患者视神经肿胀的严重程度，并确定区分视乳头水肿与其他引起视神经水肿的疾病的形态特征。与现有的主观检眼镜评估相比，通过 3D 图像分析技术获得的体积和形状参数将提高准确评估视盘水肿严重程度和原因的能力。使用 Fris 进行神经肿胀¿所提出的研究的基本原理是，拥有这样的 3D 参数将极大地改善视盘肿胀的评估方式： 1. 开发和评估计算新体积的方法。以及 SD-OCT 肿胀视神经乳头的形状参数 这将通过在视盘肿胀患者的 SD-OCT 体积中改进和评估我们新颖的基于 3D 图形的分割算法来完成。 2. 确定与视乳头水肿患者的严重程度临床测量最佳相关的 SD-OCT 参数，并制定连续的严重程度量表。这将通过使用机器学习方法将 SD-OCT 参数与专家定义的 Fris 相关联来实现。 n 等级（基于眼底的严重程度测量）预计体积 3D 参数将比 2D 参数与临床测量更密切相关，并将提供连续的严重程度等级 3. 识别区分视乳头水肿和其他疾病的 SD-OCT 参数。视盘肿胀（或明显的视盘肿胀，如假性视乳头水肿）的原因并开发相应的预测分类器我们的工作假设是 3D 形状参数，尤其是靠近 Bruch 膜开口的参数，将贡献最大。该方法是创新的，因为申请人开发的3D图像分析方法能够以新颖的方式确定3D体积和形状参数，并且代表了对使用定性图像信息和2D OCT图像信息进行评估的现状的显着改进。这项研究意义重大，因为它将有助于建立一种急需的替代且更客观的方法来评估视盘肿胀的严重程度和原因。