Abstract
Fitting of PET pharmacokinetic parameters may suffer from bias or unrealistic outcomes, especially for noisy data. There are many readily available optimization algorithms, but each has different characteristics when fitting PET pharmacokinetic models. The purpose of this study is to evaluate the performance of four different types of optimization algorithms, including a modified simulated annealing method, in terms of precision and accuracy of PET pharmacokinetic parameters. The simulated annealing algorithm (SA), called Basin-hoping, was modified for present application. Input data, taken from [ 11C]-PK11195 neuroreceptor ligand studies, was used to simulate time activity curves at various noise levels. Also the influence of incorrect weighting factors on algorithm performance was studied. Surprisingly, effects of using incorrect but reasonable weighting factors on bias and precision were negligible. Except when extreme and unrealistic weighting factors were used, an increase in bias and decrease in precision was observed. In general the modified SA provided smallest weighted squared residual error and was able to find the global minimum without the need for a proper start parameter selection. However, occasionally better fits were found with the interior-reflective Newton method, but only when implemented using a range of start parameters, centered on the expected value.
| Original language | English |
|---|---|
| Pages | 3222-3225 |
| Number of pages | 4 |
| Publication status | Published - 1 Dec 2004 |
| Event | 2004 Nuclear Science Symposium, Medical Imaging Conference, Symposium on Nuclear Power Systems and the 14th International Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors - Rome, Italy Duration: 16 Oct 2004 → 22 Oct 2004 |
Conference
| Conference | 2004 Nuclear Science Symposium, Medical Imaging Conference, Symposium on Nuclear Power Systems and the 14th International Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors |
|---|---|
| Country | Italy |
| City | Rome |
| Period | 16/10/2004 → 22/10/2004 |
Cite this
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Simulated Annealing in pharmacokinetic modeling of PET neuroreceptor studies : Accuracy and precision compared with other optimization algorithms. / Yaqub, Maqsood; Boellaard, Ronald; Kropholler, Marc A.; Lubberink, Mark; Lammertsma, Adriaan A.
2004. 3222-3225 Paper presented at 2004 Nuclear Science Symposium, Medical Imaging Conference, Symposium on Nuclear Power Systems and the 14th International Workshop on Room Temperature Semiconductor X- and Gamma- Ray Detectors, Rome, Italy.Research output: Contribution to conference › Paper › Academic
TY - CONF
T1 - Simulated Annealing in pharmacokinetic modeling of PET neuroreceptor studies
T2 - Accuracy and precision compared with other optimization algorithms
AU - Yaqub, Maqsood
AU - Boellaard, Ronald
AU - Kropholler, Marc A.
AU - Lubberink, Mark
AU - Lammertsma, Adriaan A.
PY - 2004/12/1
Y1 - 2004/12/1
N2 - Fitting of PET pharmacokinetic parameters may suffer from bias or unrealistic outcomes, especially for noisy data. There are many readily available optimization algorithms, but each has different characteristics when fitting PET pharmacokinetic models. The purpose of this study is to evaluate the performance of four different types of optimization algorithms, including a modified simulated annealing method, in terms of precision and accuracy of PET pharmacokinetic parameters. The simulated annealing algorithm (SA), called Basin-hoping, was modified for present application. Input data, taken from [ 11C]-PK11195 neuroreceptor ligand studies, was used to simulate time activity curves at various noise levels. Also the influence of incorrect weighting factors on algorithm performance was studied. Surprisingly, effects of using incorrect but reasonable weighting factors on bias and precision were negligible. Except when extreme and unrealistic weighting factors were used, an increase in bias and decrease in precision was observed. In general the modified SA provided smallest weighted squared residual error and was able to find the global minimum without the need for a proper start parameter selection. However, occasionally better fits were found with the interior-reflective Newton method, but only when implemented using a range of start parameters, centered on the expected value.
AB - Fitting of PET pharmacokinetic parameters may suffer from bias or unrealistic outcomes, especially for noisy data. There are many readily available optimization algorithms, but each has different characteristics when fitting PET pharmacokinetic models. The purpose of this study is to evaluate the performance of four different types of optimization algorithms, including a modified simulated annealing method, in terms of precision and accuracy of PET pharmacokinetic parameters. The simulated annealing algorithm (SA), called Basin-hoping, was modified for present application. Input data, taken from [ 11C]-PK11195 neuroreceptor ligand studies, was used to simulate time activity curves at various noise levels. Also the influence of incorrect weighting factors on algorithm performance was studied. Surprisingly, effects of using incorrect but reasonable weighting factors on bias and precision were negligible. Except when extreme and unrealistic weighting factors were used, an increase in bias and decrease in precision was observed. In general the modified SA provided smallest weighted squared residual error and was able to find the global minimum without the need for a proper start parameter selection. However, occasionally better fits were found with the interior-reflective Newton method, but only when implemented using a range of start parameters, centered on the expected value.
UR - http://www.scopus.com/inward/record.url?scp=23844488222&partnerID=8YFLogxK
M3 - Paper
SP - 3222
EP - 3225
ER -