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Titolo: ERROR ANALYSIS ON PARAMETER ESTIMATES IN THE LIGANDRECEPTOR MODEL  APPLICATION TO PARAMETER IMAGING USING PET DATA
Autore: MILLET P; DELFORGE J; PAPPATA S; SYROTA A; CINOTTI L;
 Indirizzi:
 CEA,SERV HOSP FREDERIC JOLIOT,HOP ORSAY,4 PL GEN LECLERC F91400 ORSAY FRANCE CEA,SERV HOSP FREDERIC JOLIOT,HOP ORSAY F91400 ORSAY FRANCE CERMEP LYON FRANCE CEA,SERV HOSP FREDERIC JOLIOT,INSERM U334 F91406 ORSAY FRANCE
 Titolo Testata:
 Physics in medicine and biology
fascicolo: 12,
volume: 41,
anno: 1996,
pagine: 2739  2756
 SICI:
 00319155(1996)41:12<2739:EAOPEI>2.0.ZU;2P
 Fonte:
 ISI
 Lingua:
 ENG
 Soggetto:
 POSITRON EMISSION TOMOGRAPHY; C11 FLUMAZENIL KINETICS; HUMANBRAIN; BENZODIAZEPINE RECEPTORS; RO 151788; BINDING; INVIVO; FLUNITRAZEPAMC11; DISPLACEMENT; ANTAGONIST;
 Tipo documento:
 Article
 Natura:
 Periodico
 Settore Disciplinare:
 Science Citation Index Expanded
 Citazioni:
 28
 Recensione:
 Indirizzi per estratti:



 Citazione:
 P. Millet et al., "ERROR ANALYSIS ON PARAMETER ESTIMATES IN THE LIGANDRECEPTOR MODEL  APPLICATION TO PARAMETER IMAGING USING PET DATA", Physics in medicine and biology, 41(12), 1996, pp. 27392756
Abstract
Positron emission tomography and compartmental models allow the in vivo analysis of radioligand binding to receptor sites in the human brain. Benzodiazepine receptor binding was studied using a threecompartmental model and [C11]flumazenil. Four and five parameters were estimated from a single kinetic curve obtained with a multiinjection protocol, and parametric maps of receptor density and of the individual kinetic parameters were created with fourpixel sampling of the experimental images. The coefficient of variation on each estimated model parameter was calculated using the diagonal elements of the covariance matrix. However, these estimates are valid only under some statistical hypotheses which are not always verified with PET data. Thus, in order to verify the validity of the coefficient of variation of each parameter calculated with the covariance matrix, these results have been comparedwith the more rigorous statistical results provided by a Monte Carlo simulation. The study showed a negligible difference between the results obtained by the two methods for a low noise level in timeconcentration curves encountered using large ROIs. However, this bias becomes less negligible when the noise level is high and some estimations of the coefficients of variation were unacceptable (> 100%) with the fiveparameter model. Such difficulties did not occur with the fourparameter model which led to parametric images with good quality and acceptable estimates of coefficients of variation (less than 20% in about 75% of the ROIs).
ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 28/03/20 alle ore 10:54:12