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


METHODS
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.
Su
Yi
Y
Department of Radiology, Washington University School of Medicine, 510 South Kingshighway Boulevard, Campus Box 8225, St. Louis, MO 63110, USA.
Shoghi
Kooresh I
KI
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D019788:Fluorodeoxyglucose F18; D007700:Kinetics; D051379:Mice; D008954:Models, Biological; D049268:Positron-Emission Tomography
D019788:Fluorodeoxyglucose F18