RESUMO
Objective:To investigate the effect of using two different input functions to reconstruct 18F-FDG PET/CT Patlak multi-parameter images on the quantitative parameters of lung cancer lesions. Methods:The original whole-body dynamic 18F-FDG PET/CT scan data of lung cancer patients in the Department of Nuclear Medicine, First Affiliated Hospital of Anhui Medical University were retrospectively analyzed. The total scan time was 75 min. Two input functions were used for Patlak multi-parameter reconstruction: ① Image-derived input function(IDIF)using the Time-activity curve(TAC)of descending aorta from 0 min to 75 min. ② Population-based input function (PBIF) developed by Yale University. Metabolic rate of FDG (MR FDG) and Distribution volume (DV) images were obtained by Patlak multi-parameter analysis software using the above input functions. The region of interest (ROI) method was used to delineate the lesions to obtain multi-parameter quantitative information, including the max, peak and mean value of MR FDG and DV. Paired t-test was used for statistical analysis. Results:The original data of 27 lung cancer patients who received whole-body dynamic 18F-FDG PET/CT imaging were reconstructed by Patlak with two different input functions. The max, peak and mean values of MR FDG-IDIF and MR FDG-PBIF in lung cancer lesions were as follows: (0.26 ± 0.15), (0.19 ± 0.12), (0.14 ± 0.08)μmol·min -1·ml -1 and (0.26 ± 0.15), ( 0.20 ± 0.13), (0.15 ± 0.09)μmol·min -1·ml -1, with no statistically significant difference between two functions( P > 0.05). The max, peak and mean values of DV IDIF and DV PBIF were (165.56 ± 99.89)%, (117.66 ± 72.24)%, (62.16 ± 33.65)% and(170.04 ± 103.93)%, (121.91 ± 73.71)%, (65.05 ± 37.17)%, with no statistically significant difference between two functions ( P > 0.05). Conclusions:The population-based input function may be an alternative for patients who could not lie supine for long time during whole-body dynamic 18F-FDG PET/CT Patlak multi-parameter imaging.
RESUMO
Objective To explore the application value of different dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) models in pathological grading of breast invasive ductal carcinoma.Methods Forty-five cases of breast invasive ductal carcinoma confirmed by clinical pathology from June 2016 to October 2017 in Shanxi Provincial People's Hospital were enrolled in this study.Grade 1 and 2 invasive ductal carcinomas were classified into the low-grade group,grade 3 invasive ductal carcinomas was classified as the high-grade group.The whole patients underwent DCE-MRI scans.Volume transport constant (Ktrans) was obtained by using the Extended Tofts Linear model with population arterial input function (AIF).Then,the Reference Region model was used to obtain the reference region model volume transport constant(RRKtrans).The performances of histogram analysis of these two quantitative parameters in pathological grading of breast invasive ductal carcinoma were compared.Results The mean,25 ％,50 ％,75 ％,90 ％ percentiles,kurtosis and skewness of RRKtrans in high grade group were (0.793±0.258)/min,(0.484±0.209)/min,(0.773±0.277)/min,(1.066±0.351)/min,(1.322±0.406)/min,2.647 (1.426,3.679),0.398 (0.297,0.514) respectively,and the corresponding parameters in low grade group were (0.506±0.203)/min,(0.301 ±0.142)/min,(0.487 ±0.211)/min,(0.692±0.281)/min,(0.861±0.323)/min,1.725 (0.779,2.316),0.258 (0.133,0.302) respectively.There were significant differences between the two groups (all P ＜ 0.05).The mean,50 ％,75 ％,90 ％percentiles of Ktrans in high grade groups were (0.099±0.034)/min,(0.110±0.033)/min,(0.132±0.045)/min,(0.140±0.047)/min respectively,and the corresponding parameters in low grade group were (0.067±0.030)/min,(0.082 ±0.067)/min,(0.096 ±0.059)/min,(0.113 ±0.074)/min respectively.There were significant differences between the two groups (all P ＜ 0.05).RRKtrans was superior to Ktrans in distinguishing area under the curve (AUC) of receiver operating characteristic curve (ROC) of high and low grading of breast invasive ductal carcinoma.Conclusion RRKtrans obtained by Reference Region model and Ktrans obtained by Population AIF DCE-MRI have some values in pathological grading of breast invasive ductal carcinoma,but the performance of RRKtrans is superior to Kftrans.