Keratoconus eye model bank for virtual clinical trials and medical educations

用于虚拟临床试验和医学教育的圆锥角膜眼模型库

基本信息

批准号：
7739613
负责人：
Ying-Ling Ann Chen
金额：
$ 18.75万
依托单位：
UNIVERSITY OF TENNESSEE SPACE INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-09-01 至 2011-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7739613
关键词：
Address Anterior Behavior Biomedical Research Biometry Budgets Characteristics Classification Clinic Clinical Clinical Trials Collection Computing Methodologies Consultations Control Groups Cornea Corneal Topography Corneal dystrophy Data Databases Development Device Designs Devices Diagnostic Disease Distant Early Diagnosis Education Elements Expert Systems Eye Eye Banks Fingerprint Goals Guidelines Health Health Personnel Human Image Intervention Keratoconus Letters Light Maps Measurement Medical Medical Education Microscopic Modeling Operative Surgical Procedures Optics Patients Performance Physics Pupil Research Research Activity Research Personnel Resources Retinoscopy Scientist Sensitivity and Specificity Simulate Source Staging Structure Students Surface Techniques Technology Telemedicine Thick Training Vision Visual Acuity base design detector digital flexibility gaze human subject instrument instrumentation mathematical model novel population based prospective public health relevance research clinical testing response simulation statistics tool virtual

项目摘要

DESCRIPTION (provided by applicant): The capability to provide accurate predictions of vision performance and ophthalmic diagnostics of healthy and diseased eyes is desired. If this computational capability existed, dramatic changes could result in ocular instrument design and development, ophthalmic medical education, and ocular telemedicine. Physics and mathematical models of the eye would then be used with computational methods to simulate and predict accurately ocular characteristics and responses. The paradigm of clinical trials could conceivably be revised to achieve faster deployment of diagnostic instrumentation if demographically representative ocular responses were confidently known at the outset of the development. Similar advances are possible in medical training if realistic diagnostic device behavior could be demonstrated for students using computed images of disease and conditions. Finally, opportunities in telemedicine and expert system-based diagnostic and referral decisions become possible and practical. The major obstacles to this capability are two-fold: 1) the absence of demographically specific characteristics of the ocular model of health and diseased eyes and 2) the verification that such a data-base of ocular characteristics can be used in computations to provide accurate predictions. This proposed effort is the initial step in addressing these problems. Development of an optically functional and analytical eye-model bank to represent a diversity of human eyes is proposed. The integrative eye bank embodies population-based ocular statistics and preserves the correlations between ocular parameters and patients' demographic features. Advanced ophthalmic technologies have enabled access to the "fingerprints" of an eye with cornea topography, wavefront aberration, and ocular biometry. In the first half of this project, novel optical eye modeling techniques will be integrated with contemporary biometric and detailed clinic data to provide realistic and anatomically-accurate models including emmetropic, ammetropic, and diseased keratoconic eyes. During the latter 12 months, the eye bank applications will be demonstrated in (1) medical education, (2) patient consultation, and (3) virtual clinical trials for instrumentation. PUBLIC HEALTH RELEVANCE: Physical, medical, and computational scientists will collaboratively establish an anatomically accurate digital optical eye bank of advanced clinical personalized data to represent both healthy and diseased eyes. Optical computations will be performed to demonstrate prospective applications for the prediction of patient vision and the simulation of ophthalmic biomedical instrument measurements for medical training and novel device construction.

描述（由申请人提供）：需要能够准确预测健康和患病眼睛的视力表现和眼科诊断。如果这种计算能力存在，眼科仪器的设计和开发、眼科医学教育和眼科远程医疗可能会发生巨大的变化。然后，眼睛的物理和数学模型将与计算方法一起使用，以准确地模拟和预测眼睛特征和反应。如果在开发之初就能够确信地了解具有人口统计学代表性的眼部反应，那么可以想象，可以对临床试验的范式进行修改，以实现诊断仪器的更快部署。如果可以使用疾病和状况的计算图像向学生展示真实的诊断设备行为，那么在医学培训方面也可能取得类似的进步。最后，远程医疗和基于专家系统的诊断和转诊决策的机会变得可能和实用。这种能力的主要障碍有两个：1）缺乏健康和患病眼睛的眼部模型的人口统计特征；2）验证这样的眼部特征数据库可以用于计算以提供准确的数据。预测。这项提议的努力是解决这些问题的第一步。建议开发一种光学功能和分析性眼睛模型库来代表人眼的多样性。综合眼库体现了基于人群的眼部统计数据，并保留了眼部参数与患者人口统计特征之间的相关性。先进的眼科技术已经能够通过角膜地形图、波前像差和眼部生物测量来获取眼睛的“指纹”。在该项目的前半部分，新颖的光学眼建模技术将与当代生物识别和详细的临床数据相结合，以提供逼真且解剖学上准确的模型，包括正视眼、屈光眼和患病圆锥角膜眼。在后 12 个月内，眼库应用将在 (1) 医学教育、(2) 患者咨询和 (3) 仪器虚拟临床试验中得到展示。公共健康相关性：物理、医学和计算科学家将合作建立一个解剖学上准确的数字光学眼库，其中包含先进的临床个性化数据，以代表健康和患病的眼睛。将进行光学计算，以展示预测患者视力以及模拟眼科生物医学仪器测量的潜在应用，以用于医疗培训和新型设备构造。