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.

Original languageEnglish
Title of host publicationMedical Imaging 2009
Subtitle of host publicationBiomedical Applications in Molecular, Structural, and Functional Imaging
StatePublished - 2009
EventMedical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging - Lake Buena Vista, FL, United States
Duration: Feb 8 2009Feb 10 2009

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISSN (Print)1605-7422


ConferenceMedical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Compartment modeling
  • Input function
  • PET
  • Small animal imaging


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