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Automated quantification of lipid droplets in fatty liver tissue sections

Award Information
Agency: Department of Health and Human Services
Branch: National Institutes of Health
Contract: 2R42DK082087-02A1
Agency Tracking Number: R42DK082087
Amount: $1,458,397.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: NIDDK
Solicitation Number: PA10-051
Timeline
Solicitation Year: 2011
Award Year: 2011
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
11575 Sorrento Valley Rd.
SAN DIEGO, CA -
United States
DUNS: 612181532
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 PATRICK MCDONOUGH
 (858) 461-6863
 pmcdonough@valasciences.com
Business Contact
 EMILY ARSENAULT
Phone: (858) 461-6861
Email: earsenault@valasciences.com
Research Institution
 UNIVERSITY OF CALIFORNIA
 
UNIVERSITY OF CALIFORNIA LOS ANGELES Office of Research Administration 11000 Kinross Avenue, Suite 211
LOS ANGELES, CA 90095-
United States

 () -
 Nonprofit College or University
Abstract

DESCRIPTION (provided by applicant): NonAlcoholic Fatty liver is associated with obesity, and HCV infection, and is a leading cause of fibrosis, cirrhosis, and liver cancer. Lipid droplet formation (steatosis) is an underlying cause of the pathologies. However, there is considerable variation in the scoring of steatosis and fibrosis by pathologists. This proposal is for Phase II of the STTR project 1R41DK082087-01 Automated quantification of lipid droplets in fatty liver tissue sections . In Phase I, an image analysis algorithm (Steatosis Algorithm), was developed to predict the Steatosis Score of the pathologist associated with the project, via the analysis of digital photographs obtained from hematoxylin + eosin stained human biopsies. For phase II, a collaboration is proposed between Vala Sciences Inc and a team of eminent pathologists and liver specialists to further develop the Steatosis Algorithm, and to develop algorithms to quantify inflammation, and fibrosis. For this purpose we propose to scan extensive sets of slides with an automated digital slide scanner, to provide thousands of digital images for use in training the algorithms. Slide sets to be scanned include: 1) slides from the HALT-C clinical trial in which pegylated interferon was tested forpossible therapeutic effects against HCV in a longitudinal study, 2) slides from patients with both Alcoholic and NonAlcoholic fatty liver and Steatohepatitis previously collected and maintained by the pathologists and physicians associated with this project, and 3) mouse liver slides obtained in studies of liver metabolism. The algorithms will provide an objective assessment of steatosis, inflammation, and fibrosis, for liver samples obtained from both humans and animal models of fatty liver, and will beused in both the clinical and research areas. PUBLIC HEALTH RELEVANCE: Fatty liver disease is a condition that affects a high proportion of the US population, particularly people that are overweight or obese, or are infected with Hepatitis C virus. Fatty liver is characterized by the occurrence of fat droplets within the cells that make up the liver. Tissue samples (biopsies) are commonly taken from livers as part of the protocol for research studies on fatty liver disease, and the fat content, degree of inflammation, and fibrous nature of the samples are graded by pathologists, using microscopes and grading criteria, that is, at best, semi-quantitative. The proposed research will develop a technique for rapid and precise automatic quantification ofthe fat content of liver biopsies, which will be an aid to pathologists for diagnosing fatty liver, and to researchers investigating therapeutics to fatty liver in animal models of the disease.

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

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