Single-input-dual-output modeling of image-based input function estimation

Mol Imaging Biol. 2010 Jun;12(3):286-94. doi: 10.1007/s11307-009-0273-5. Epub 2009 Dec 1.


Purpose: Quantification of small-animal positron emission tomography (PET) images necessitates knowledge of the plasma input function (PIF). We propose and validate a simplified hybrid single-input-dual-output (HSIDO) algorithm to estimate the PIF.

Procedures: The HSIDO algorithm integrates the peak of the input function from two region-of-interest time-activity curves with a tail segment expressed by a sum of two exponentials. Partial volume parameters are optimized simultaneously. The algorithm is validated using both simulated and real small-animal PET images. In addition, the algorithm is compared to existing techniques in terms of area under curve (AUC) error, bias, and precision of compartmental model micro-parameters.

Results: In general, the HSIDO method generated PIF with significantly (P < 0.05) less AUC error, lower bias, and improved precision of kinetic estimates in comparison to the reference method.

Conclusions: HSIDO is an improved modeling-based PIF estimation method. This method can be applied for quantitative analysis of small-animal dynamic PET studies.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Animals
  • Computer Simulation
  • Fluorodeoxyglucose F18
  • Kinetics
  • Mice
  • Models, Biological*
  • Positron-Emission Tomography*


  • Fluorodeoxyglucose F18