1.Safety evaluation of laparoscopic common bile duct exploration and lithotomy without placing drainage tube
Hongwei ZHANG ; Xuan LUO ; Jun CAO ; Wenda LI ; Changhao WU ; Yajin CHEN
Chinese Journal of Digestive Surgery 2014;13(9):691-693
Objective To investigate the safety of laparoscopic common bile duct exploration and lithotomy with primary closure and without placing drainage tube postoperatively.Methods Forty patients who received laparoscopic common bile duct exploration and lithotomy at the Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University from January 2011 to June 2013 were prospectively analyzed.All the patients were randomly divided into 2 groups according to the random number table.Twenty patients in the experimental group did not received drainage tube placement,and the other 20 patients in the control group had subhepatic drainage after operation.The operation time,duration of hospital stay and incidence of postoperative complications were compared between the 2 groups.Patients received computed tomography and B sonography at postoperative month 1 and 3,and then patients were reexamined every 6 months till postoperative year 3.The follow-up was ended on July 31,2013.The measurement data and the count data were analyzed using the independent sample t test and the Fisher exact probability,respectively.Results Patients in the 2 groups were cured after the operation.The operation time and duration of hospital stay were (117 ± 11) minutes and (5.6 ± 0.6) days in the experimental group,and (108 ± 12)minutes and (7.9 ± 0.7)days in the control group,with significant difference between the 2 groups (t =2.453,-ll.388,P < 0.05).No complications including bile leakage,residual stones,obstructive jaundice,abdominal bleeding and subphrenic infection were detected after the operation.Thirty-one patients were followed up for 1 month to 2 years,no bile duct stone recurrence or biliary stricture were detected during the follow-up.Conclusion Laparoscopic common bile duct exploration and lithotomy with primary closure and without placing drainage tube postoperatively is safe and feasible.
2.Exploring the predictive value of MRI-based clinical-radiomics models for biochemical recurrence after radical prostatectomy in prostate cancer
Yanting JI ; Jie BAO ; Xiaomeng QIAO ; Changhao CAO ; Chunhong HU ; Ximing WANG
Chinese Journal of Radiology 2023;57(11):1200-1207
Objective:To construct a clinical-radiomics model based on MRI, and to explore its predictive value for biochemical recurrence (BCR) after radical prostatectomy in prostate cancer patients.Methods:A total of 212 patients with prostate cancer who underwent radical prostatectomy in the First Affiliated Hospital of Soochow University from January 2015 to December 2018 and had complete follow-up data were retrospectively analyzed. The random toolkit of Python language was used to randomly sample the patients at a ratio of 7∶3 without replacement, and they were divided into a training set (149 cases) and a test set (63 cases). The endpoint of follow-up was BCR or at least 3 years. BCR occurred in 50 patients in the training group and 21 patients in the test group. The imaging features of the main lesion area in the preoperative T 2WI, diffusion-weighted imaging and apparent diffusion coefficient map of patients in the training set were extracted, and the unsupervised K means clustering algorithm was used to screen the features. The selected features were fitted by a multivariate Cox regression model, and the radiomics model was constructed. Univariate Cox regression analyses were used to screen the main clinical risk factors associated with BCR, and the clinical-radiomics model was constructed combined with RadScore. In the test set, the time-dependent receiver operating characteristic (ROC) curve was constructed, and the area under the curve (AUC) was calculated to evaluate the predictive efficacy of the radiomics model, clinical-radiomics model and prostate cancer risk assessment after radical resection (CAPRA-S) score for the occurrence of BCR. Harrell consistency index (C-index) was used to evaluate the model to predict BCR consistency. The calibration curve was used to evaluate the degree of variation of the model. The decision curve was used to evaluate the clinical application value of the prediction model. Results:A total of 26 radiomics features were screened to establish the radiomics model. The univariate Cox showed that the preoperative clinical features included preoperative prostate-specific antigen level (HR=1.006, 95%CI 1.002-1.009, P=0.001), Gleason score of biopsy (HR=1.422, 95%CI 1.153-1.753, P=0.001), clinical T stage (HR=1.501, 95%CI 1.238-1.822, P<0.001). The multivariate Cox showed that the RadScore was an independent predictor of BCR after radical prostatectomy (HR=51.214, 95%CI 18.226-143.908, P<0.001). The selected preoperative clinical features were combined with RadScore to construct a clinical-radiomics model. In the test set, the AUCs of the time (3 years)-dependent ROC curves of the radiomics model, the clinical-radiomics model, and the CAPRA-S score were 0.824 (95%CI 0.701-0.948), 0.841 (95%CI 0.714-0.968), and 0.662 (95%CI 0.518-0.806), respectively. The C-index of the radiomics model, clinical-radiomics model and CAPRA-S score were 0.784 (95%CI 0.660-0.891), 0.802 (95%CI 0.637-0.912) and 0.650 (95%CI 0.601-0.821), respectively. The calibration curve showed that the predicted probability and actual probability of BCR by radiomics model, clinical-radiomics model and CAPRA-S score were in good agreement (χ 2=7.64, 10.61, 6.37, P=0.465, 0.225, 0.498). The decision curve showed that the clinical net benefit of the clinical-radiomics model and the radiomics model was significantly higher than the CAPRA-S score. When the threshold probability was 0.20-0.30, 0.40-0.50, and >0.55, the clinical net benefit of the clinical radiomics model was higher than that of the radiomics model. Conclusions:The clinical-radiomics model can effectively predict the occurrence of BCR in patients with prostate cancer after radical prostate ctomy, and the prediction efficacy is better than the radiomics model and CAPRA-S score.