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

Award Information
Agency:
Department of Energy
Branch
n/a
Amount:
$100,000.00
Award Year:
2007
Program:
SBIR
Phase:
Phase I
Contract:
DE-FG02-07ER84897
Award Id:
84164
Agency Tracking Number:
83229
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
60 Temple Street, Suite 8A, New Haven, CT, 06510
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
020285081
Principal Investigator:
George Zubal
Dr
(203) 401-4300
gzubal@indd.org
Business Contact:
Jack Mariotti
Dr
(203) 401-4351
jmariotti@indd.org
Research Institution:
n/a
Abstract
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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