Objective To study the effects of organ dose modulation (ODM) technique on dose reduction of the breasts and the related thoracic image quality in female chest CT.Methods One hundred and twelve female patients with chest CT were enrolled in this study and divided into two groups according to the order:control group (n =56,using conventional scan) and experimental group (n =56,using ODM technique).The tube currents in different directions (A/L/P/R) were analyzed in the two groups.The effects of ODM on the radiation dosage and image quality were assessed.Results The tubc currents in anterior and posterior direction were both (128 ± 43)mA in the control group.However,the tube current in the anterior was lower than that in the posterior in experimental group (t =-18.701,P ＜0.01).The tube currents in all direction in the experimental group were all lower than those in the control group (t =11.71-20.22,P ＜0.01).The CTDIvol and E in the experimental group were lower than those in the control group(t=3.58,3.55,P ＜0.05).There were no significant differences for the objective and the subjective scores between two groups (P ＞ 0.05).Conclusions ODM technique could protect the female breasts by reducing the radiation dose without image quality degrading during chest CT scan.

so higher in diabetic patients 4 h after the meal (all P<0. 05). Positive correlation existed between serum triglycerides and white blood cell counting, neutrophils, and high-sensitivity C-reactive protein(r were between 0.268 and 0.548, all P<0.05).

Objective To investigate the reproducibility and accuracy of spinal BMD (bone mineral density) by low mA using adaptive statistic iterative reconstruction based on phantom model.Methods European spine phantom (ESP) was scanned with 5 different tube currents (40,60,80,100 and 120 mA) on the GE Revolution prototype.All data were transferred to the quantitative CT (QCT) PRO workstation for measuring the bone mineral density (BMD).And all data were reconstructed using different adaptive statistical iterative reconstruction veo (ASiR-V) weighting percentages from ASiR-V 0 filtered back projection(FBP) to ASiR-V 100％,at interval of 20％.Quantitative measurements of CT value,noise,and contrast noise ratio (CNR) of L1,L2 and L3 were measured in each group.The singlefactor analysis of variance (ANOVA) was used to compare the bone mineral density values of different mA and ASiR-V weighting percentages.Results Volume CT dose index(CTDIvol) and dose length product (DLP) were positively correlated with tube current(r =1).The BMD of ESP phantoms had no statistically significant differences among the multi-center lumbar spines L1,L2 and L3 at different doses under the same ASiR-V weighting percentages (P ＞ 0.05),as well as at the same dose under different ASiR-V weighting percentages(P ＞ 0.05).The error of bone density accuracy was within 6％.Conclusions Low dosage of 120 kV and 40 mA using ASiR-V without affecting the accuracy of BMD has the potential effect to reduce radiation dose without compromising image quality.

Objective To investigate the influence of low-tube current in combination with simultaneous iterative reconstruction algorithm on bone mineral density (BMD) of T12 and image quality with a chest phantom.Methods An adult male chest phantom was selected.CT scan of the chest was performed at tube voltage of 120 kV and five different tube currents (20,30,40,50,60 mAs) in combination with filtered back projection (FBP),iDose4 (Level 4) and iterative model reconstruction (IMR,Level 2),respectively.BMD of T12 in chest phantom and objective evaluation results on different tube currents and simultaneous iterative reconstruction techniques were compared.The subjective scoring of mediastinum and lung window imaging qualities at tube current of 20 mAs with IMR and tube current of 60 mAs with FBP were compared.The consistency between two observers was evaluated.Results There was no significant difference between BMD values nor CT values on different tube currents and simultaneous iterative reconstruction techniques of chest phantom (all P＞ 0.05),but the differences between SD values were statistically significant (P＜ 0.001).SD values obtained with IMR were lower than those of iDose4 and FBP at same tube currents (all P＜0.001).At tube current of 60 mAs with FBP,the consistency of two observers in mediastinum window was the best (Kappa=1,P＜0.001),while in lung window was medium (Kappa=0.64,P=0.002).At tube current of 20 mAs with IMR,the consistency of two observers in mediastinum window was medium (Kappa=0.64,P=0.002),while in lung window was the best (Kappa=1.00,P＜0.001).Conclusion Low-tube current in combination with simultaneous iterative reconstruction algorithm can reduce radiation dose without affecting the accuracy of BMD.

Objective:To investigate the clinical efficacy of ultrasound-guided vacuum-assisted excision (VAE) in the treatment of breast benign phyllode tumor and the risk factors of local recurrence after operation.Methods:A total of 256 cases of patients with breast benign phyllode tumor admitted to Yuncheng Central Hospital from January 2012 to January 2020 were included in the retrospective study, they were all female, of which 160 cases received ultrasound-guided VAE surgical treatment and 96 cases received open surgical treatment. Measurement data were expressed as mean ± standard deviation ( ± s), and t-test was used for comparison between groups. The Chi-square test or Fisher exact probability method was used to compare the data groups. Univariate analysis was performed on the factors related to the local recurrence of benign phyllode tumor after surgery, and then the factors with statistically significant differences in the univariate analysis were further incorporated into multivariate Logistic regression analysis. Results:Univariate analysis results showed that the maximum diameter of tumor ≥25 mm and the history of ipsilateral breast fibroadenoma were associated with postoperative local recurrence of breast benign phyllodes tumor ( P<0.05). Multivariate Logistic regression analysis results showed that tumor diameter ≥25 mm was an independent risk factor for postoperative local recurrence of breast benign phyllodes tumor ( P<0.05). Conclusion:Ultrasound-guided VAE in the treatment of breast benign phyllodes tumor patients with maximum diameter less than 25 mm can reduce the postoperative local recurrence rate, and patients with tumor maximum diameter greater than 25 mm should have the higher local recurrence risk.

Objective: To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. Methods: The clinical data of 157 severely burned patients in August 2nd Kunshan factory aluminum dust explosion accident conforming to the inclusion criteria were collected. Patients suffering AKI within 90 days after admission were enrolled in group AKI, while the others were enrolled in non-AKI group. Single factor analysis was used to choose independent factors associated with AKI, including sex, age, admission time, features of basic injuries, initial score on admission, treatment condition, and mortality on post injury days 30, 60, and 90. Data were processed with Mann-Whitney U test, chi-square test, and Fisher′s exact test. Variables with P<0.1 in single factor analysis and those with possible clinical significance were brought into the establishment of prediction model. Logistic regression and XGBoost machine learning algorithm were used to build the prediction model of AKI. The area under receiver operating characteristic curve (AUC) was calculated, and the sensitivity and specificity for optimal threshold value were also calculated for each model. Nonparametric resampling test was used to compare the significance of difference of AUC of the two models. Results: (1) Eighty-nine (56.7%) patients developed AKI within 90 days from admission. Compared with 68 patients in non-AKI group, 89 patients in group AKI were older (Z=-2.203, P<0.05), with larger total burn area and full-thickness burn area (Z=-5.200, -6.297, P<0.01), worse acute physical and chronic health evaluation (APACHE) Ⅱ score, abbreviated burn severity index score, and sequential organ failure assessment (SOFA) score on admission (Z=-7.485, -4.739, -4.590, P<0.01), higher occurrence rate of sepsis (χ²=33.087, P<0.01), higher rates of accepting tracheotomy, mechanical ventilation, and continuous renal replacement therapy (χ²=12.373, 17.201, 43.763, P<0.01), larger first excision area (Z=-2.191, P<0.05), and higher mortality on post injury days 30, 60, and 90 (χ²=7.483, 37.259, 45.533, P<0.01). There were no statistically significant differences in sex, open decompression, admission time, 24-hour fluid volume after admission, 48-hour fluid volume after admission, the first 24-hour urine volume, the second 24 hour urine volume, the first excision time, and inhalation injury (χ²=0.529, 3.318, Z=-1.746, -0.016, -1.199, -1.824, -0.625, -1.747, P>0.05). The rates of deep vein catheterization of patients in the two groups were both 100%. (2) There were twenty possible prediction variables for preliminary establishment of model according to the difference results of single factor analysis and clinical significance of variables. (3) The logistic regression prediction model had three variables: APACHE Ⅱ score [odds ratio (OR)=1.36, 95% confidence interval (CI)=1.20-1.53, P<0.001], sepsis (OR=2.63, 95% CI=0.90-7.66, P>0.05), and the first 24-hour urine volume (OR=0.71, 95% CI=0.50-1.01, P>0.05). The AUC of the logistic regression prediction model was 0.875 (95% CI=0.821-0.930), with the specificity and sensitivity of optimal threshold value 84.4% and 77.7%, respectively. (4) XGBoost machine learning model had seven main predictive variables: APACHE Ⅱ score, full-thickness burn area, 24-hour fluid volume after admission, sepsis, the first 24-hour urine volume, SOFA score, and 48-hour fluid volume after admission. The AUC of machine learning model was 0.920 (95% CI=0.879-0.962), higher than that of logistic regression model (P<0.001), with the specificity and sensitivity of optimal threshold value 89.7% and 82.0%, respectively. Conclusions Sepsis and fluid resuscitation are two important predictive variables that can be intervened for AKI in severely burned patients. Machine learning method has a better performance and can provide more accurate prediction for individuals than logistic regression prediction model, and therefore has good clinical application prospect.

Objective    To compare the clinical effects of segmentectomy and lobectomy for ≤2 cm lung adenocarcinoma with micropapillary and solid subtype negative by intraoperative frozen sections. Methods    The patients with adenocarcinoma who received segmentectomy or lobectomy in multicenter from June 2020 to March 2021 were included. They were divided into two groups according to a random number table, including a segmentectomy group (n=119, 44 males and 75 females with an average age of 56.6±8.9 years) and a lobectomy group (n=115, 43 males and 72 females with an average of 56.2±9.5 years). The clinical data of the patients were analyzed. Results    There was no significant difference in the baseline data between the two groups (P>0.05). No perioperative death was found. There was no statistical difference in the operation time (111.2±30.0 min vs. 107.3±34.3 min), blood loss (54.2±83.5 mL vs. 40.0±16.4 mL), drainage duration (2.8±0.6 d vs. 2.6±0.6 d), hospital stay time (3.9±2.3 d vs. 3.7±1.1 d) or pathology staging (P>0.05) between the two groups. The postoperative pulmonary function analysis revealed that the mean decreased values of forced vital capacity and forced expiratory volume in one second percent predicted in the segmentectomy group were significantly better than those in the lobectomy group (0.2±0.3 L vs. 0.4±0.3 L, P=0.005; 0.3%±8.1% vs. 2.9%±7.4%, P=0.041). Conclusion    Segmentectomy is effective in protecting lungs function, which is expected to improve life quality of patients.