Objective To determine reasonable b values in diffusion weighted imaging of lung cancer with 1.5T MR.Methods 30 patients with lung cancer received DWI of the chest using a single shot EPI-SE pulse sequence with different b values(500 s/mm2 , 600 s/mm2 ,800 s/mm2 ,1 000 s/mm2 ),and the ADC values of the lesion were measured.The image quality of each group of DWI and ADC were analyzed and compared.Results The images of DWI and ADC of 30 patients were all captured clearly,and ADC val-ues of lesions were measured too.As b values increasing from 500 s/mm2 to 1 000 s/mm2 ,SNR of lung tissue and lesion decreased gradually.When b value was 600 s/mm2 ,the ADC value was highest,and then decreased gradually.When b value was500 s/mm2 , the reference rang of ADC value was stable too.Conclusion When b value is 600 s/mm2 ,the image quality of DWI and ADC map of lung cancer is satisfying with SNR and CNR,and this would provide accuracy information for lesion changing.

Objective To investigate the diagnostic values of CT and MRI by analysing the CT and MRI features of presacral tumor.Methods The CT and MRI imaging features of 37 cases of primary presacral tumor with surgical pathology were analyzed retrospectively,and the imaging findings were compared with the pathologic findings.All data were analyzed by Fishersχ2 test.Re-sults 9 cases of presacral tumors were cystic type,18 cases were solid type and 10 cases were cystic-solid type.90.3% (28/31)of benign tumors had round or oval shapes,83.3% (5/6)of malignant tumors were irregular form(χ2=16.093,P=0.001).The den-sity of lesions whether uniform or not,and the presence of enhancement showed no obvious statistical differences between benign and malignant lesions.In all 37 cases,28 cases of benign and 1 case of malignant tumor were found compressed the surrounding tissues and organs;4 cases of benign and 5 cases of malignant tumor invaded adjacent tissues and organs(χ2=13.547,P=0.002).Conclu-sion CT and MRI can differentiate benign and malignant tumor,and can make clear diagnosis in some cases.

Objective     To explore the correlation between the quantitative and qualitative features of CT images and the invasiveness of pulmonary ground-glass nodules, providing reference value for preoperative planning of patients with ground-glass nodules. Methods    The patients with ground-glass nodules who underwent surgical treatment and were diagnosed with pulmonary adenocarcinoma from September 2020 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were collected. Based on the pathological diagnosis results, they were divided into two groups: a non-invasive adenocarcinoma group with in situ and minimally invasive adenocarcinoma, and an invasive adenocarcinoma group. Imaging features were collected, and a univariate logistic regression analysis was conducted on the clinical and imaging data of the patients. Variables with statistical difference were selected for multivariate logistic regression analysis to establish a predictive model of invasive adenocarcinoma based on independent risk factors. Finally, the sensitivity and specificity were calculated based on the Youden index. Results     A total of 555 patients were collected. The were 310 patients in the non-invasive adenocarcinoma group, including 235 females and 75 males, with a meadian age of 49 (43, 58) years, and 245 patients in the invasive adenocarcinoma group, including 163 females and 82 males, with a meadian age of 53 (46, 61) years. The binary logistic regression analysis showed that the maximum diameter (OR=4.707, 95%CI 2.060 to 10.758), consolidation/tumor ratio (CTR, OR=1.027, 95%CI 1.011 to 1.043), maximum CT value (OR=1.025, 95%CI 1.004 to 1.047), mean CT value (OR=1.035, 95%CI 1.008 to 1.063), spiculation sign (OR=2.055, 95%CI 1.148 to 3.679), and vascular convergence sign (OR=2.508, 95%CI 1.345 to 4.676) were independent risk factors for the occurrence of invasive adenocarcinoma (P<0.05). Based on the independent predictive factors, a predictive model of invasive adenocarcinoma was constructed. The formula for the model prediction was: Logit(P)=–1.293+1.549×maximum diameter of lesion+0.026×CTR+0.025×maximum CT value+0.034×mean CT value+0.72×spiculation sign+0.919×vascular convergence sign. The area under the receiver operating characteristic curve of the model was 0.910 (95%CI 0.885 to 0.934), indicating that the model had good discrimination ability. The calibration curve showed that the predictive model had good calibration, and the decision analysis curve showed that the model had good clinical utility. Conclusion     The predictive model combining quantitative and qualitative features of CT has a good predictive ability for the invasiveness of ground-glass nodules. Its predictive performance is higher than any single indicator.