| ObjectiveTo investigate the characteristics of Patlak multi-parameter imaging in 18F-2-fluoro-2-deoxyd-D-glucose positron emission tomography/computed tomography for lung cancer.MethodsThe data and clinical data of 27 patients with pathologically diagnosed lung cancer who completed whole-body dynamic 18F-FDG PET/CT examination in our hospital from August 2020 to August 2022 were retrospectively analyzed.The original PET scan data were derived from the Patlak analysis module in the acquisition workstation of Siemens Biograph Vision PET/CT equipment in our department to outline the region of interest of the proximal descending aorta,and the Image-derived input function(IDIF)was generated.Multi-parameter images were reconstructed,including Metabolic rate of FDG(MRFDG)image,Distribution volume(DV)image and traditional Standardized uptake value(SUV)image.The primary lesions of lung cancer patients were delineated in each image,and the delineation methods were divided into contour delineation method and boundary delineation method.The maximum value,mean value and peak value of lesions in MRFDG,DV and SUV images were automatically obtained.Radioactive uptake of lung Background in multi-reference and SUV images was measured,and Background mean(BKGmean)and Background standard deviation(BKGSD)of quantitative values were obtained.The maximum and mean values of Target/Background Ratio(TBR)and Contrast/noise ratio(CNR)were calculated for the lesions in MRFDG and SUV images.The relationship between the features of multi-reference images and clinicopathological features of lung cancer was analyzed statistically,and the effects of contour delineation and boundary delineation on quantitative parameters were compared.Results(1)A total of 27 patients(15 males,12 females,mean age 64.67± 10.55 years)were included in this study.There were 25 cases of non-small cell lung cancer,including 12cases of squamous cell carcinoma and 13 cases of adenocarcinoma.There was 2 case of small cell lung cancer.(2)Quantitative values of MRFDG,DV and SUV in primary lung cancer lesions of 27 patients were:SUVmax(13.16 ± 5.45),SUVpeak(10.36 ± 4.83),SUVmean(7.56 ± 3.52),MRFDGmax(0.26 ± 0.15)μmol·min-1·ml-1,MRFDGpeak(0.19 ± 0.12)μmol·min-1·ml-1,MRFDGmean(0.14 ± 0.08)μmol·min-1·ml-1,DVmax(165.56 ± 99.89)%,DVpeak(117.66 ±72.24)%and DVmean(62.16 ± 33.65)%.in addition,TBRmax-SUV(20.16 ± 9.77),TBRmax-MRFDG(24.36 ± 11.50),TBRmean-SUV(11.32 ± 5.86),TBRmean-MRFDG(12.99 ±6.29),CNRmax-SUV(64.67 ± 23.44),CNRmax-MRFDG(85.97 ± 29.03),CNRmean-SUV(34.70 ± 14.53)and CNRmean-MRFDG(43.78 ± 16.87),The maximum and mean values of TBR and CNR in MRFDG image were significantly higher than those in SUV image(t=4.836,t=4.159,t=7.389,t=4.847,all P<0.05).(3)The study on the relationship between MRFDG parameter values(MRFDGmax,MRFDGpeak,MRFDGmean)and clinicopathologic characteristics of lung cancer patients showed that the differences of MRFDG parameter values were statistically significant in the long diameter and pathological types of different tumor lesions(t=3.564,t=3.683,t=4.223,t=3.700,t=3.497,t=3.464,all P<0.05),and the length and diameter of tumor lesions≥3cm,the MRFDG parameter value in squamous cell carcinoma patients group was higher.(4)The mean values of quantitative parameters(MRFDG and DV)obtained by different methods were significantly different(t=6.216,t=7.058,all P<0.05).There was no significant difference between the maximum and peak values of MRFDG and DV(t=0.000,t=0.000,t=1.789,t=1.433,all P>0.05).Conclusion(1)Studies have shown that the multi-parameter quantitative values of the primary lesions of lung cancer can be obtained by Patlak reconstruction after 18F-FDG PET/CT dynamic scanning.According to the objective indicators TBR and CNR,MRFDG images are superior to SUV images in terms of lesion detection.(2)The parameter values of MRFDG(MRFDGmax,MRFDGpeak,MRFDGmean)were correlated with the clinicopathological characteristics of lung cancer,and there were differences in the length diameter and pathological type groups of different tumor lesions.And the MRFDG values of patients with tumor lesions≥ 3cm were higher than those with tumor lesions<3cm.Patients with squamous cell carcinoma had higher MRFDG than those with adenocarcinoma.(3)Different delineation methods had certain influence on the mean value of quantitative parameters(MRFDG and DV),but had no statistical significance on the maximum value and peak value.(4)This study provides reference data and guidance for the follow-up experimental studies on diagnosis,staging and efficacy evaluation of lung cancer using dynamic PER/CT Patlak multi-parameter imaging.ObjectiveTo investigate the effect of 18F-FDG PET/CT Patlak multi-parameter image reconstruction using two different input functions on the quantitative parameters of lung cancer lesions.MethodsThe original scanning data of lung cancer patients who completed whole-body dynamic 18F-FDG PET/CT examination in our hospital from August 2020 to August 2022 were retrospectively analyzed.The total scanning time was 75 min.Two input functions were used for Patlak multi-parameter reconstruction:(1)Descending aorta time-activity curve(TAC)was used as input function(IDIF);② Take the population-based input function(PBIF)developed by Yale University.Patlak multi-parameter analysis software reconstructed the metabolic rate(MRFDG)and distribution volume(DV)images with the above input functions respectively.The primary lesions of lung cancer patients were mapped by VOI method in each image,and multi-reference quantitative information including max,peak and mean values of MRFDG and DV were obtained.Paired T-test was used for statistical analysis.ResultsThe original data of 27 patients with lung cancer who underwent whole-body dynamic 18F-FDG PET/CT multi-parameter imaging were obtained by Patlak reconstruction using two different input functions.The maximum value,peak value and average value of lung cancer focus MRFDG-IDIF and MRFDG-PBIF were respectively:(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,the difference was not statistically significant(t=1.007,t=0.827,t=0.756,P>0.05).The max,peak and average value of DVIDIF and DVPBIF are respectively:(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)%,there was no statistical significance(t=0.934,t=0.836,t=1.363,P>0.05).ConclusionThis study showed that there was no significant difference in the quantitative values of the multi-parameter images obtained by Patlak reconstruction with two different input functions.Population-based input function may be an alternative input function for whole-body dynamic 18F-FDG PET/CT Patlak multiparametric imaging in patients who have difficulty tolerating prolonged lying down. |
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