Comprehensive Eye Evaluation Algorithm: CEEvA

Information

  • Research Project
  • 9252893
  • ApplicationId
    9252893
  • Core Project Number
    R43EY026832
  • Full Project Number
    1R43EY026832-01A1
  • Serial Number
    026832
  • FOA Number
    PA-15-269
  • Sub Project Id
  • Project Start Date
    3/1/2017 - 7 years ago
  • Project End Date
    2/28/2018 - 6 years ago
  • Program Officer Name
    WUJEK, JEROME R
  • Budget Start Date
    3/1/2017 - 7 years ago
  • Budget End Date
    2/28/2018 - 6 years ago
  • Fiscal Year
    2017
  • Support Year
    01
  • Suffix
    A1
  • Award Notice Date
    2/23/2017 - 7 years ago

Comprehensive Eye Evaluation Algorithm: CEEvA

Summary The objective of this project is to develop the Comprehensive Eye Evaluation Algorithm (CEEvA), a system to achieve blindness prevention in a cost effective way. CEEvA uses fundus images and available personal medical data in the electronic medical record (medical history and laboratory tests) to automatically screen not only for DR, but also for POAG and AMD in populations at higher risks. CEEvA targets screening for three eye diseases in the following populations: 1) DR screening annually for every diabetic, 2) POAG screening for those with diabetes, or with family history of POAG, who are African?American over the age of 40, or who are Hispanic?American aged 65 and older, and 3) AMD screening for Whites over 65 years. The motivation of this project is to increase the efficiency of eye disease screening by detecting the main causes of blindness in the US population. Currently, diabetic retinopathy (DR), age- related macular degeneration (AMD) and primary open?angle glaucoma (POAG) affect 7.7 million, 2.1 million, and 2.7 million people, respectively. Direct medical costs in the United States due to these three eye diseases are $14.5 billion per year. The effectiveness of screening for DR has generated multiple successful screening programs. Although screening for only AMD and POAG has not been demonstrated to be cost effective in the population at large, various studies have demonstrated that by screening the populations at higher risk for these diseases, vision loss is reduced by up to 40%. The objectives of this project will be accomplished through two specific aims. In Aim 1 we will incorporate medical data to complement and augment the prototype fundus?based algorithms previously developed for DR, AMD, and glaucoma detection. In Aim 2, our goal is to validate CEEvA software in an accurate and reliable way by using 407 cases of retrospective data. At the end of Phase I we will have a system ready for validation in a Phase II prospective study in preparation for an FDA clinical trial.

IC Name
NATIONAL EYE INSTITUTE
  • Activity
    R43
  • Administering IC
    EY
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    224791
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    867
  • Ed Inst. Type
  • Funding ICs
    NEI:224791\
  • Funding Mechanism
    SBIR-STTR RPGs
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    VISIONQUEST BIOMEDICAL, LLC
  • Organization Department
  • Organization DUNS
    804567217
  • Organization City
    ALBUQUERQUE
  • Organization State
    NM
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    871064200
  • Organization District
    UNITED STATES