Quantitative I-123 Cardiac SPECT using a Novel Spectral Fitting Method for High E

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$117,839.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
1R43HL090118-01A1
Award Id:
89290
Agency Tracking Number:
HL090118
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
CARDIOVASCULAR IMAGING TECHNOLOGIES. LLC, 4320 WORNALL RD, STE 55, KANSAS CITY, MO, 64111
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
626962596
Principal Investigator:
() -
Business Contact:
() -
Research Institution:
n/a
Abstract
DESCRIPTION (provided by applicant): Current emphasis on metabolic approaches and models for diagnosing heart disease have renewed development of 123I SPECT imaging agents applied in stand-alone protocols and as a complimentary role to existing stress/rest perfusion protocols. However, a majority of the current nuclear cardiology SPECT equipment base and associated infrastructure utilize low energy (LE) collimation which is a significant technical obstacle to adapting 123I imaging due to spectrum contaminan ts from high energy (gt 500 keV) 123I emissions. Medium energy (ME) collimation for SPECT imaging is typically applied in general nuclear environments for 123I imaging, but is not readily available or nonexistent for nuclear cardiology large field of view systems and not at all available for small field of view dedicated cardiac SPECT systems. The primary objective of this work is to develop an energy-based algorithmic method allowing efficient and accurate imaging of 123I agents on existing nuclear cardiol ogy equipment employing low energy collimation while improving image accuracy in comparison with ME collimation thereby facilitating adaptation of cardiac 123I SPECT. The technique employs a list mode acquisition that improves the effective energy resoluti on of the gamma camera by iteratively estimating a spectrum free' of the spectral contaminants. The technique does not rely on assumptions about the patient habits or require the acquisition of additional data for modeling the scatter component.

* information listed above is at the time of submission.

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