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Computer based screening for diabetic retinopathy

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 1R44EY018280-01A1
Agency Tracking Number: EY018280
Amount: $874,730.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: N/A
Solicitation Number: PHS2007-2
Solicitation Year: 2008
Award Year: 2008
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
2501 Yale Blvd. SE Suite 201
United States
DUNS: 183651723
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 (505) 228-3875
Business Contact
Phone: (505) 798-2505
Research Institution

DESCRIPTION (provided by applicant): This proposed project is motivated by two observations. First, broad-scale screening of diabetics for retinopathy is economically prohibitive without the introduction of computer-assisted diagnosis of retinal images. S
econd, screening by family physicians or other non-ophthalmologists does not result in sufficiently high sensitivity or specificity. There are over 20 million people in the US with diabetes and it is estimated that less than half of those are screened per
iodically for diabetic retinopathy. Access to this type of healthcare is an obstacle to the individual, while having an affordable solution to provide this service to the large volume of diabetics presents a significant challenge. Basing a comprehensive sc
reening program for US citizens on human readers to grade each case would prohibitively expensive. Like other medical applications, such mammograms and Pap smears, computer-assisted technology could provide the foundation for the solution to comprehensiv
e, periodic screening of our at risk population. Numerous investigators have developed specific algorithms, each to detect one type of lesion, such as dark lesions, white lesions, or vessel characteristics. These algorithms have been tested using a single
modality (pixel format, SLO, standard funduscope, color, red free, etc). Each new camera requires significant re-tuning of the algorithms. The goal of this project is to demonstrate then validate an entirely new approach for computer-assisted grading of r
etinal images. This algorithm is based on the human vision system and is tuned to each type of lesion, modality, grading system, etc. through the presentation of examples of each to a single algorithm. Sensitivity and specificity will be calculated. The
goal is to achieve 99% sensitivity and 90% specificity. The significance of this proposed research is two-fold. First, by providing a validated, robust computer-assisted grading system, all existing reading centers would benefit by the added efficiency of
our system. Our system does not replace current readers, it simply allows increases by factors of 4-5 throughput of cases without sacrifice of sensitivity and specificity. Our Product Development Plan expands on the economics of our approach. Second, by i
ncreasing the productivity of reading centers, a much larger population of at risk diabetics can be screened, leading to improved quality of life. PUBLIC HEALTH RELEVANCE: Today there are about 10 million diabetics that are not receiving annual eye examina
tions. Without these examinations early detection of vision threatening retinopathy is not possible. The result is early loss of vision for many of these diabetics. There is an insufficient number of healthcare specialists to perform eye examinations for
this population. Without the computer-based screening, a broad-scale screening of the population will not be possible.

* Information listed above is at the time of submission. *

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