Objective To observe the value of CT radiomics machine learning(ML)model for predicting stone free rate(SFR)of urinary calculi after retrograde intrarenal surgery(RIRS).Methods Totally 216 patients with urinary calculi who underwent RIRS were retrospectively enrolled and divided into residual group(n=73)and non-residual group(n=143).Univariate and multivariate logistic regression(LR)were performed to analyze clinical data and CT manifestations of stones to screen independent predictors of SFR after RIRS.Window width and window level normalization combined with max-min normalization(denoted as method a),max-min normalization(denoted as method b),window width and window level normalization(denoted as method c)and non-normalization(denoted as method d)of pre-RIRS abdominal CT were performed,respectively,and the best radiomics features of stones were extracted and screened to establish ML models,including support vector machine(SVM),LR and stochastic gradient descent(SGD)models,and the best ML model was screened.RUSS and modified S.T.O.N.E scores were evaluated based on pre-RIRS CT for predicting SFR of urinary calculi after RIRS.A combined model was then constructed with the independent predictors and the best ML model.The predictive efficacy of each model and scoring system were assessed.Results The number of stones,CT value and volume of the maximum stone were all independent predictors of SFR after RIRS(all P＜0.05).The area under the curve(AUC)of SVM model constructed with images preprocessed by method b was the highest(0.861),higher than that of the total scores of RUSS and modified S.T.O.N.E(AUC=0.750,0.759,both P＜0.05)but not different from that of combined model(AUC=0.853,P=0.775).Conclusion Radiomics SVM model based on max-min normalization preprocessed CT could effectively predict SFR of urinary calculi after RIRS.

Objective To observe the value of CT radiomics machine learning(ML)model for predicting stone free rate(SFR)of urinary calculi after retrograde intrarenal surgery(RIRS).Methods Totally 216 patients with urinary calculi who underwent RIRS were retrospectively enrolled and divided into residual group(n=73)and non-residual group(n=143).Univariate and multivariate logistic regression(LR)were performed to analyze clinical data and CT manifestations of stones to screen independent predictors of SFR after RIRS.Window width and window level normalization combined with max-min normalization(denoted as method a),max-min normalization(denoted as method b),window width and window level normalization(denoted as method c)and non-normalization(denoted as method d)of pre-RIRS abdominal CT were performed,respectively,and the best radiomics features of stones were extracted and screened to establish ML models,including support vector machine(SVM),LR and stochastic gradient descent(SGD)models,and the best ML model was screened.RUSS and modified S.T.O.N.E scores were evaluated based on pre-RIRS CT for predicting SFR of urinary calculi after RIRS.A combined model was then constructed with the independent predictors and the best ML model.The predictive efficacy of each model and scoring system were assessed.Results The number of stones,CT value and volume of the maximum stone were all independent predictors of SFR after RIRS(all P＜0.05).The area under the curve(AUC)of SVM model constructed with images preprocessed by method b was the highest(0.861),higher than that of the total scores of RUSS and modified S.T.O.N.E(AUC=0.750,0.759,both P＜0.05)but not different from that of combined model(AUC=0.853,P=0.775).Conclusion Radiomics SVM model based on max-min normalization preprocessed CT could effectively predict SFR of urinary calculi after RIRS.

Objective To assess the clinical application value of phleboplasties combined with microvascular anastomotic device in venous anastomosis with diameter discrepancy in head and neck defects reconstruction.Methods Sixty-six pairs of veins with significant diameter discrepancy were anastomosed in head and neck reconstructive surgeries with free flaps.Forty of them were anastomosed with microvascular anastomotic device (the coupler group) after phleboplasties including lateral incision, Y-T enlargement and wedge excision while the other 26 pairs of veins were conventionally sutured (the sutured group).Diameter of each vein, anastomosis time, post-operative vascular crisis, flap survival and complications related to the microvascular anastomotic device were recorded.Results The average anastomosis time of the coupler group was (4.78 ± 1.14) min for lateral incision, (5.16 ± 2.07) min for Y-T enlargement and (11.09 ± 3.21) min for wedge excision, and all of them were significantly shorter than that of the sutured group.In the sutured group, all flaps survived except for 2 veins with poor blood flow were cut and re-anastomosed during the operation;1 flap with venous crisis within 72 hours after the operations was explored and replaced with the pectoralis major myocutaneous flap.All veins in the coupler group were successfully anastomosed in a single coupling procedure without anastomotic impatency, blood leak, vessel tearing and ring shedding.No vascular crisis occurred postoperatively.One patient underwent cervical haematoma 5 hours after the operation, and the flap blood supply was unaffected after the haematoma was removed.All flaps in the coupler group survived completely.Patients in both two groups were followed up 6 to 18 months.All flaps healed perfectly and no obvious surgical complications or microvascular anastomotic device rejection happened.Conclusion When anastomoses are carried out using microvascular anastomotic device between veins of different size, phleboplasties including lateral incision., Y-T enlargement and wedge excision can not only reduce the size discrepancy and the anastomosis time, but also ease the difficulty level and guarantee the patency of the venous anastomoses.Wedge excision enjoys the advantage of haemodynamics, and obstruction of venous reflux hardly occurred for size reduction.It should be considered preferentially when external jugular veins are used as the anastomotic vein of the recipient sites in head and neck reconstruction.