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Proceedings Paper

Hybrid input function estimation using a single-input-multiple-output (SIMO) approach
Author(s): Yi Su; Kooresh I. Shoghi
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Paper Abstract

A hybrid blood input function (BIF) model that incorporates region of interests (ROIs) based peak estimation and a two exponential tail model was proposed to describe the blood input function. The hybrid BIF model was applied to the single-input-multiple-output (SIMO) optimization based approach for BIF estimation using time activity curves (TACs) obtained from ROIs defined at left ventricle (LV) blood pool and myocardium regions of dynamic PET images. The proposed BIF estimation method was applied with 0, 1 and 2 blood samples as constraints for BIF estimation using simulated small animal PET data. Relative percentage difference of the area-under-curve (AUC) measurement between the estimated BIF and the true BIF was calculated to evaluate the BIF estimation accuracy. SIMO based BIF estimation using Feng's input function model was also applied for comparison. The hybrid method provided improved BIF estimation in terms of both mean accuracy and variability compared to Feng's model based BIF estimation in our simulation study. When two blood samples were used as constraints, the percentage BIF estimation error was 0.82 ± 4.32% for the hybrid approach and 4.63 ± 10.67% for the Feng's model based approach. Using hybrid BIF, improved kinetic parameter estimation was also obtained.

Paper Details

Date Published: 28 February 2009
PDF: 8 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 726221 (28 February 2009); doi: 10.1117/12.811164
Show Author Affiliations
Yi Su, Washington Univ. in St. Louis (United States)
Kooresh I. Shoghi, Washington Univ. in St. Louis (United States)


Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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