The Application Of Dual-energy CT In The Diagnosis And Prediction Of Lung Cancer Subtypes

Objective:To evaluate the clinical usefulness of quantitative dual-energy computed tomography(DECT)iodine enhancement metrics combined with morphological CT features in distinguishing small-cell lung cancer(SCLC)from non-small-cell lung cancer(NSCLC).Methods:106 untreated lung cancer patients who underwent DECT before biopsy or surgery were prospectively enrolled.27 routine CT descriptors,including tumor location,size,shape,margin,enhancement heterogeneity,and internal and surrounding structures,and associated findings were assessed and DECT parameters were measured in all patients.Multiple logistic regression analyses were applied to identify independent predictors of SCLC.The area under the receiver operating characteristic curve was compared between CT features combined with DECT metrics and CT features alone for distinguishing SCLC from NSCLC.Results:Histology revealed NSCLC in 80 and SCLC in 26 patients.In univariate analysis,12 morphological CT features and two DECT metrics differed significantly between NSCLC and SCLC.When we combined DECT parameters with CT features for multivariate analysis,the independent predictors of SCLC were large tumor size,central location,confluent mediastinal lymphadenopathy,homogeneous enhancement,absence of coarse spiculation,and lower iodine density and iodine ratio(all p<0.05).The area under the receiver operating characteristic curve was improved from 0.908 to 0.981 after adding DECT metrics compared with CT features alone(p=0.007).Conclusion:The combination of DECT measures and CT morphological features can be used to distinguish SCLC from NSCLC,with higher diagnostic performance compared with CT morphological features alone.Objective:To investigate the clinical usefulness of quantitative dual-source dual-energy CT(DECT)iodine enhancement metrics combined with morphological CT features in distinguishing different lung cancer subtypes.Methods:Consecutive patients suspected with lung cancer were prospectively enrolled and underwent DECT in arterial phase prior to biopsy or surgery.Tumor histological subtypes were determined in 110 patients.Two radiologists interpreted CT morphologic features of 110 lesions in a consensual manner.In addition,two radiologists independently contoured lesions and placed regions of interest in descending aorta or arteria subclavia on the same section for normalization,from which automated computer measurements were generated:Iodine density and iodine ratio(the ratio of iodine density of lesion to that of artery on the same section).DECT metrics and morphological CT features were compared among different lung cancer subtypes.Chi-square was used to compare qualitative parameters.One way ANOVA was used to compare quantitative parameters satisfying normal distribution,while those parameters not satisfying normal distribution or ranked data were compared by Kruskal-Wall is rank sum test.Multinomial logistic regression models were used to differentiate the histological subtypes of lung cancer:adenocarcinoma,squamous cell carcinoma(SCC),small cell lung cancer(SCLC).Results:Histology revealed adenocarcinoma in 48,SCC in 36 and SCLC in 26 patients.In analysis of CT features,tumor diameter,distribution,spiculation,pleural retraction,vascular involvement,confluent mediastinal lymphadenopathy,encasement of mediastinal structures and enhancement heterogeneity showed statistical difference(all Ps<0.05).The diameter of SCC(5.73±3.67cm)and SCLC(6.08±4.39 cm)were larger than adenocarcinoma(3.75±2.80 cm);Adenocarcinoma was mostly located in periphery(31/48),while SCC(26/36)and SCLC(21/26)mainly centrally located;Spiculation was mostly found in adenocarcinoma(44/48)rather than SCLC(13/26);Pleural retraction was mostly observed in adenocarcinoma(36/48)rather than SCC(10/36)and SCLC(5/26);Vascular involvement was mostly found in SCLC(19/26)rather than adenocarcinoma(15/48);Confluent mediastinal lymphadenopathy was more frequently found in SCLC(15/26)compared with adenocarcinoma(3/48)and SCC(4/36);Encasement of mediastinal structures was mostly found in SCLC(13/26)rather than adenocarcinoma(7/48);Homogeneous enhancement was more frequently found in SCLC(10/26)than SCC(6/36).No significant differences were observed in other CT features between any other two groups.Iodine density and iodine ratio were statistically different among three lung cancer subtypes(H=16.817,P<0.001;H=20.338,P<0.001).Iodine density of adenocarcinoma and SCC was(1.50±0.80)mg/ml and(1.40±0.40)mg/ml,respectively,higher than the(1.20±0.40)mg/ml for SCLC(Pa<0.01).Iodine ratio of adenocarcinoma and SCC was(16.10±7.02)%and(15.05±4.62)%,respectively,higher than the(11.55±3.15)mg/ml for SCLC(Ps<0.01).No significant difference was observed between adenocarcinoma and SCC.Accuracy of the model based on CT features was 69.1%,accuracy of the model based on CT features combined with DECT parameters was 80.9%.Conclusions:Quantitative DECT metrics are different among adenocarcinoma,SCC and SCLC,when combined with morphological CT features,higher diagnostic performance can be achieved.Objective:To investigate the feasibility of areal and volumetric iodine quantification metrics with dual-energy CT in predicting EGFR mutation status of non-small cell lung cancer(NSCLC)and the correlation between the two methods.Materials and methods:58 untreated NSCLC patients who underwent DECT in an arterial phase before biopsy or surgery were prospectively enrolled.For each lesion,areal iodine content(IC)and normalized iodine content(NIC)at maximum area among slices and volumetric IC and NIC of the whole-tumor were evaluated by two radiologists.In the volumetric analysis,tumor was further sectioned,volumetric parameters of every segment and peel were noted.The diagnostic performances of areal and volumetric iodine metrics in characterizing EGFR mutations were compared,and the two iodine quantification methods were correlated with each other.Results:EGFR mutations were found in 28 of 58 patients.NICareai of EGFR mutant group(0.16±0.06)was higher than that of wild-type group(0.12±0.05)(t=2.869,P=0.006).NICvolumetric of the inner segment and peel in EGFR mutant group were higher than that in wild-type group(t=2.415-2.699,P=0.009-0.019).However,volumetric parameters of the total lesion and marginal part showed no significant difference between the two groups.ROC curve analysis revealed that diagnostic performance of NICareal(AUC=0.693)was similar to that of NICvolumetric of inner segments and peels(AUC=0.655-0.677).NICareal was strongly correlated with inner segmental NICvolumetric(r=0.818-0.821).Conclusions:Areal and volumetric iodine metrics were applicable in predicting EGFR mutation status,the maximum area iodine quantification was suggested in clinical use due to its convenient access.