Development of Automated Software Program for the Analysis of Parkinson's Diesease Dopamine Transporter Scans

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-FG02-07ER84897
Agency Tracking Number: 83229
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2007
Solicitation Topic Code: 51
Solicitation Number: DE-PS02-06ER06-30
Small Business Information
60 Temple Street, Suite 8A, New Haven, CT, 06510
DUNS: 020285081
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 George Zubal
 (203) 401-4300
Business Contact
 Jack Mariotti
Title: Dr
Phone: (203) 401-4351
Research Institution
This project will develop a fast, automated, and accurate software processing package that will objectively yield striatal quantitative uptake values for evaluating Parkinson's disease (PD) diagnosis and progression. This fully automated, Objective Striatal Analysis (OSA) package will evaluate subjects referred for SPECT neuroreceptor imaging studies, with a sensitivity and specificity higher than currently possible by visual inspection or manual image processing methods. By employing OSA, it will be possible to analyze archival scans, which otherwise would require months of manual labor. Without any user interaction, OSA will: (1) reorient the reconstructed brain volume along the cantho-meatal line; (2) identify axial slices with striatal activity; (3) place templates on the left and right caudate, the putamen, and the occipital background regions, following set rules for movement of regions; and (4) extract count density data for the determination of regional striatal. The required algorithms will be coded into a software package, and the results will be applied to groups of patients and healthy volunteers. The results will be compared to results obtained by manually analyzing the same subject groups. Commercial Applications and other Benefits as described by the awardee: The OSA for Parkinson¿s Disease should lead to more accurate and efficient clinical studies requiring fewer subjects. It would then be possible to evaluate new radiopharmaceutical and therapy agents without obfuscating the results by improper or insufficiently-tested image processing methods. In addition, the technology should serve as a model for the development of similar objective algorithms to fully assess radiopharmaceuticals in other disorders, such as Alzheimer¿s disease.

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

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