Automated image-based biomarker computation tools for diabetic retinopathy

Information

  • Research Project
  • 8252674
  • ApplicationId
    8252674
  • Core Project Number
    R41TR000377
  • Full Project Number
    1R41TR000377-01
  • Serial Number
    000377
  • FOA Number
    PA-11-097
  • Sub Project Id
  • Project Start Date
    9/1/2012 - 12 years ago
  • Project End Date
    11/30/2013 - 11 years ago
  • Program Officer Name
    WILSON, TODD
  • Budget Start Date
    9/1/2012 - 12 years ago
  • Budget End Date
    11/30/2013 - 11 years ago
  • Fiscal Year
    2012
  • Support Year
    01
  • Suffix
  • Award Notice Date
    8/13/2012 - 12 years ago
Organizations

Automated image-based biomarker computation tools for diabetic retinopathy

DESCRIPTION (provided by applicant): In this STTR project, we present EyeMark, a set of tools for automated computation of biomarkers for diabetic retinopathy using retinal image photographs. Specifically, we will develop tools for computation of microaneurysm (MA) appearance and disappearance rates (jointly known as turnover rates) for use as a biomarker in monitoring progression of diabetic retinopathy (DR). The availability of a reliable image-based biomarker will have high positive influence on various aspects of DR care, including screening, monitoring progression, drug discovery and clinical research. There is ample published evidence that MA turnover rates are a good predictor of likelihood of progression to more severe retinopathy, establishing MA turnover as an excellent biomarker for diabetic retinopathy. Measuring this quantity involves two steps: careful alignment of current and baseline images, and marking of individual MAs. This process is very time consuming and prone to error, if done by entirely by human graders. The primary goal of this project is to overcome the above limitations by automating both the steps involved in MA turnover measurement: accurate image registration, and MA detection. We will develop end-too-end desktop software for automated computation of MA turnover and also provide intuitive visualization tools for clinicians to more effectively monitor diabetic retinopathy progression. PUBLIC HEALTH RELEVANCE: The proposed tool will greatly enhance the clinical care available to diabetic retinopathy patients by providing an automated tool for computation of a biomarker in a non-invasive manner. This will enable identification of patients who are more likely to progress to severe retinopathy, thus helping prevent vision loss in such patients by timely intervention. Early identification is especially important in face of long backlog of diabetic patients waiting for an eye examination, and the fact that 90% of vision loss can be saved by early identification. The availability of an effective biomarker will also positively influence the drug discovery process by facilitating early and reliable determination of biological efficacy of potential new therapies.

IC Name
NATIONAL CENTER FOR ADVANCING TRANSLATIONAL SCIENCES
  • Activity
    R41
  • Administering IC
    TR
  • Application Type
    1
  • Direct Cost Amount
  • Indirect Cost Amount
  • Total Cost
    260857
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    350
  • Ed Inst. Type
  • Funding ICs
    NCATS:260857\
  • Funding Mechanism
    SBIR-STTR RPGs
  • Study Section
    ZRG1
  • Study Section Name
    Special Emphasis Panel
  • Organization Name
    EYENUK, INC.
  • Organization Department
  • Organization DUNS
    832930569
  • Organization City
    WOODLAND HILLS
  • Organization State
    CA
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    913677409
  • Organization District
    UNITED STATES