Objective To observe the value of PET/CT radiomics for predicting Ki-67 expression level of non-small cell lung carcinoma(NSCLC).Methods 18F-FDG PET/CT data of 139 NSCLC patients were retrospectively analyzed.The patients were divided into high-expression group(≥40%,n=75)and low-expression group(＜40%,n=64)according to Ki-67 expression level of NSCLC.CT,PET and PET/CT data were divided into training set and test set at a ratio of 7∶3 and make the distribution of Ki-67 expression levels balanced between sets,respectively.CT,PET and PET/CT radiomics features of NSCLC were extracted,and the optimal radiomics features were screened,then random forest(RF),categorical boosting(CatBoost)and extreme gradient boosting(XGBoost)algorithms were used to construct models,respectively.Receiver operating characteristic curve was plotted,and the area under the curve(AUC)was calculated to screen the radiomics model with the highest efficacy for predicting Ki-67 expression level of NSCLC.Results RF models had the highest performance among radiomics models constructed based on CT,PET and PET/CT.The efficacy of RFCT,RFPET and RFPET/CT models for predicting Ki-67 expression level of NSCLC in test set increased sequentially,with AUC of 0.830,0.870 and 0.940,respectively(all P＜0.05),and RFPET/CT was the best radiomics model.Conclusion PET/CT radiomics could be used to effectively predict Ki-67 expression level of NSCLC,and RFPET/CT model had the best performance.

Objective To observe the value of PET/CT radiomics for predicting Ki-67 expression level of non-small cell lung carcinoma(NSCLC).Methods 18F-FDG PET/CT data of 139 NSCLC patients were retrospectively analyzed.The patients were divided into high-expression group(≥40%,n=75)and low-expression group(＜40%,n=64)according to Ki-67 expression level of NSCLC.CT,PET and PET/CT data were divided into training set and test set at a ratio of 7∶3 and make the distribution of Ki-67 expression levels balanced between sets,respectively.CT,PET and PET/CT radiomics features of NSCLC were extracted,and the optimal radiomics features were screened,then random forest(RF),categorical boosting(CatBoost)and extreme gradient boosting(XGBoost)algorithms were used to construct models,respectively.Receiver operating characteristic curve was plotted,and the area under the curve(AUC)was calculated to screen the radiomics model with the highest efficacy for predicting Ki-67 expression level of NSCLC.Results RF models had the highest performance among radiomics models constructed based on CT,PET and PET/CT.The efficacy of RFCT,RFPET and RFPET/CT models for predicting Ki-67 expression level of NSCLC in test set increased sequentially,with AUC of 0.830,0.870 and 0.940,respectively(all P＜0.05),and RFPET/CT was the best radiomics model.Conclusion PET/CT radiomics could be used to effectively predict Ki-67 expression level of NSCLC,and RFPET/CT model had the best performance.

Objective:To investigate the clinicopathological features of Erdheim-Chester disease (ECD) initially diagnosed at extraskeletal locations.Methods:Clinical and pathological data of four cases of ECD diagnosed initially in extraskeletal locations were collected at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, from January 2013 to June 2023. BRAF V600E gene was detected by reverse transcription polymerase chain reaction (RT-PCR). Pertinent literatures were reviewed.Results:Four ECD patients included two males and two females ranging in ages from 2 years 11 months to 69 years. The lesions located in the lung (two cases), central nervous system (one case), and the testicle (one case) were collected in the study. One patient had occasional fever at night, one had nausea and vomiting, and two were asymptomatic. Radiologically, the two pulmonary ECD showed diffuse ground-glass nodules in both lungs, and the lesions in central nervous system and testicle both showed solid masses. Microscopically, there were infiltration of foamy histiocyte-like cells and multinucleated giant cells in a fibrotic background, accompanied by varying amounts of lymphocytes and plasma cells. The infiltration of tumor cells in pulmonary ECD was mainly seen in the subpleural area, interlobular septa, and perivascular and peribronchiolar areas. The fibrosis was more pronounced in the pleura and interlobular septa, and less pronounced in the alveolar septa. Immunohistochemical staining showed that all tumor cells expressed CD68, CD163 and F a; one case showed S-100 expression; three cases were positive for BRAF V600E; all were negative for CD1α and Langerin. RT-PCR in all four cases showed BRAF V600E gene mutation. Conclusions:Extraskeletal ECD is often rare and occult, and could be easily misdiagnosed, requiring biopsy confirmation. The radiologic findings of pulmonary ECD is significantly different from other types of ECD, and the histopathological features of pronounced infiltration in the subpleura area, interlobular septa, perivascular and peribronchiolar areas can be helpful in the differential diagnosis from other pulmonary diseases. Detection of BRAF V600E gene mutation by RT-PCR and its expression by immunohistochemical staining are also helpful in the diagnosis.

More than 80％ of lung cancer is non-small cell lung cancer (NSCLC),and the epidermal growth factor receptor (EGFR)-mediated signaling pathway is closely related to the occurrence and development of NSCLC.Small molecule EGFR-tyrosine kinase inhibitors (EGFR-TKI) targeting EGFR have been used in the clinical treatment of NSCLC,and positron emission tomography/computed tomgraphy (PET/CT) imaging can noninvasively monitor the expression and mutation status of EGFR in patients with NSCLC.18F-FDG PET/CT imaging has predictive value for the activation of EGFR mutation and EGFR-TKI treatment efficacy,and in vivo can be directly observed drugs and systemic tumor targeting EGFR combined with the specific circumstances,by PET/CT imaging before and after treatment,to achieve dynamic monitoring,guide the therapy before treatment and treatment of sensitive population screening process,to achieve NSCLC EGFR-TKI precise treatment is essential.

Objective To investigate the correlation of serum uric acid (SUA) level with the prevalence of metabolic syndrome (MS). Methods A random, multi-stage cross-sectional study was performed in 2364 resuden, aged from 20 to 74, in Lanzhou, Gansu province.The resudents were divided into groups according to the level of SUA or 4 components of MS. The relationship between SUA and MS was analyzed. Results The overall morbidity of MS was 20.13 % in Lanzhou , and the morbidity of MS was higher in female than that in male (23.22% vs. 17.37%, P < 0.05);The prevalences of MS was higher in the hyperuricemia (HUA) people than that in the healthy people (32.40 % vs. 17.70 %,P < 0.05); With the increase of SUA level, the morbidity rates of MS and its components increased;The risk of MS showed a gradual increase with the SUA level, the risk of MS(odds ratio,95%CI)in sex-specific quartiles of SUA was 2.33(1.45 ~ 3.71),2.33(1.45 ~3.71),2.44(1.53 ~ 3.89)in male;and 1.58(0.97~2.56),2.54(1.60 ~ 4.00),5.29(3.41 ~ 8.22)in female. The more the components of MS , the higher the SUA level was found for both the male and the female subjects , with the higher rate of HUA morbidity(P < 0.05). Conclusion There is a significant association between SUA level and MS, as well as the MS components. Comprehensive prevention and control should be taken for the reduction of the risk factors, and much attention should be paid to monitor the SUA level.

Objective:To explore the effects of body mass index (BMI) and gender on primary lung cancer 18F-FDG uptake param-eters, standardized uptake value (SUV), and standard uptake value of lean body mass (SUL). Methods:Data of 50 patients with prima-ry lung cancer confirmed by 18F-FDG positron emission tomography (PET)/computed tomography (CT) were retrospectively analyzed. AW4.6 workstation was employed to measure the SUVmean and SUVmax. Meanwhile, PETVCAR (PET Volume Computed Assisted Reading, GE Healthcare) software was used to automatically measure the SULmean, SULmax, and SULpeak. The SUVmean, SUV-max, SULmean, and SULmax of the liver (central region of the right lobe) were also measured automatically by PETVCAR. Afterward, T/N ratios (lesion SUVmax/liver SUVmean, lesion SULmax/liver SULmean, and lesion SULpeak/liver SULmean) of the lung cancer lesions were calculated. Correlations of the 18F-FDG metabolic parameters with BMI and gender of the patients were analyzed. Results:Liver SUVmean and SUVmax demonstrated significant positive correlations with BMI in all the patients (γ=0.38 and 0.36, P<0.05), and the SUVmean and SUVmax were positively correlated with BMI in male and female groups (γ=0.47 and 0.44, P<0.05), respective-ly. By contrast, no correlation existed between the liver SULmean and SULmax and BMI (P>0.05). No significant correlation was not-ed between the SUVmean, SUVmax, SULmean, SULmax, and SULpeak of the lung cancer lesions and BMI (P>0.05). The correlation trend is the same as that in different gender groups. Only the SUVmax T/N ratio of the lung cancer lesions showed a significant nega-tive correlation with BMI (γ=?0.29, P<0.05). The T/N ratios did not correlate with BMI in the different gender groups (P>0.05). Con-clusion:Patient BMI and gender mainly affect SUV values, particularly SUVmax, by contrast, patient BMI and gender did not signifi-cantly influence SUL and T/N ratio (SUL). Hence, SUL can be more suitable to quantitatively analyze and assess treatment response ob-jectively. This result will be helpful to the clinical application and promotion of PERCIST, which evaluates treatment response mainly by SUL.