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1.
Med Phys ; 36(10): 4791-802, 2009 Oct.
Article in English | MEDLINE | ID: mdl-19928109

ABSTRACT

PURPOSE: It is known that the arterial input function (AIF) in dynamic contrast-enhanced (DCE)-CT differs among patients even for fixed contrast injection protocols. Therefore, a study has been performed to investigate the interindividual variability of the AIF with respect to patient factors (such as weight, height, and age). In addition, it has been demonstrated that the relations from the interindividual variability investigation can be further used for the estimation of AIF for a patient without the requirement of measurement. METHODS: DCE-CT data for a cohort of 34 patients with cervical carcinoma were used for the investigation of interindividual variability of the AIF. To dissociate the effect of different durations of contrast injection, the arterial impulse response (AIR) to intravenous contrast injection was calculated and examined for its correlations with these patient factors. An empirical functional form was proposed to model the AIR with temporal intensity of a first pass of contrast agent followed by recirculation and quasiequilibrium state of contrast concentration. Specific features (onset time, peak time, and amplitudes) of the AIR were tested for correlations with the patient factors. Linear regression was applied to cases that show significant strong correlation between the AIR amplitudes and patient factors. The results were then used to predict the AIR for any given patient based on the patient factors. It was shown that using the predicted AIR, the AIF of the patient can be estimated without the requirement of measurement given the injection protocol is known. The method of AIF estimation was tested in DCE-CT data from another group of 14 patients. The efficacy of individually estimated AIF on pharmacokinetic analysis was assessed against the use of measured AIF and population-averaged AIF as the latter is another possible strategy for AIF generation if AIF measurement is not available. RESULTS: It was found that the amplitudes of AIR postonset time were significantly correlated with patient bodyweight at most time points (r<-0.44, P<0.01) except 8-17 s (P>0.01). When the adiabatic tissue homogeneity (ATH) and the Kety models were applied to the pharmacokinetic analysis, the mean percentage errors in kinetic parameter estimates induced by using the estimated AIF instead of the measured one for both models ranged from -4.98% to 11.19%. CONCLUSIONS: It was found that there are strong linear relationships between AIR and patient weight; thereby the AIR of a patient can be estimated with patient weight. The proposed method of AIF estimation is potentially applicable in cases where AIF measurement is not possible.


Subject(s)
Arteries/metabolism , Iohexol/pharmacokinetics , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Uterine Cervical Neoplasms/diagnostic imaging , Uterine Cervical Neoplasms/metabolism , Computer Simulation , Contrast Media/pharmacokinetics , Female , Humans , Injections, Intravenous , Iohexol/administration & dosage , Ions , Middle Aged , Models, Biological , Radionuclide Imaging , Reproducibility of Results , Sensitivity and Specificity , Uterine Cervical Neoplasms/blood supply
2.
Med Phys ; 35(12): 5921-33, 2008 Dec.
Article in English | MEDLINE | ID: mdl-19175147

ABSTRACT

Contrast injection protocol is known to affect the estimation of kinetic parameters in functional CT. A novel method is proposed to maximize the precision of parameter estimates by modulating the contrast injection scheme. The method models the intravenous contrast bolus to be dispersed by a "patient function" to give rise to the arterial input function, which, in turn, carries the contrast agent to tissue leading to contrast enhancement. The covariance matrix analysis was applied to calculate the uncertainty of parameter estimates as the coefficients of variation (CV) in the adiabatic tissue homogeneity (ATH), two-compartment, and the modified Kety model in which tumor pathophysiology is modeled. An optimization scheme was used to determine the optimal injection protocol which would minimize the CV of a particular kinetic parameter. For clinical utility, a recommended injection protocol was suggested from a statistical analysis with the optimal injection protocols obtained from the first group of 12 patients with cervix cancer. The efficacy of the recommended injection protocol was tested with a second group of 12 patients. In addition, the robustness of the recommended injection protocol to longitudinal study has been investigated in the presence of variations in arterial input function and tumor pathophysiology. Based on the data of the second group of patients, and using the ATH model, the recommended biphasic injection of two boluses improves the precision in the estimation of blood flow and mean transit time (MTT), by 36.9% and 38.4%, respectively, compared to the standard uniphasic injection protocol in the CV. However, measurement of the permeability surface area product and extravascular extracellular space volume favors a single fast bolus of the same contrast amount. The two-compartment model and the modified Kety model also benefited from the single fast bolus. The effect of variation in the arterial input function and tumor pathophysiology on the applicability of the recommended injection was also investigated. Based on computer simulation for a range of variations in the arterial input function and pathophysiology, the recommended biphasic injection was found to improve the precision in blood flow and MTT estimates by 31.4% and 36.5% on average, respectively, compared to the uniphasic injection.


Subject(s)
Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Uterine Cervical Neoplasms/diagnosis , Adult , Algorithms , Body Weight , Computer Simulation , Contrast Media/pharmacology , Female , Humans , Imaging, Three-Dimensional , Kinetics , Middle Aged , Time Factors , Uterine Cervical Neoplasms/diagnostic imaging
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