Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium...Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.展开更多
目的探讨双源CT双能量成像技术对体外泌尿系结石成分分析的价值。材料与方法收集97例已知化学成分的泌尿系结石标本,结石成分包括草酸钙55例、羟基磷灰石13例、尿酸9例、胱氨酸4例、磷酸铵镁2例、混合结石14例,将结石编号后放入猪肾中...目的探讨双源CT双能量成像技术对体外泌尿系结石成分分析的价值。材料与方法收集97例已知化学成分的泌尿系结石标本,结石成分包括草酸钙55例、羟基磷灰石13例、尿酸9例、胱氨酸4例、磷酸铵镁2例、混合结石14例,将结石编号后放入猪肾中进行双源CT双能量扫描,测量80 k V及140 k V下结石CT值,计算CT值差值及双能量指数(DEI),分析结石成分,计算每种结石利用双能量技术分析结石成分的敏感度、特异度及准确度。结果双能量分析结石成分结果为草酸钙59例、羟基磷灰石11例、尿酸9例、胱氨酸4例,混合结石14例。2例羟基磷灰石、2例磷酸镁铵双能量分析均为草酸钙结石,准确率为95.88%(93/97)。不同成分结石双能量扫描(80 k V与140 k V)CT值差值及DEI大小依次为:草酸钙结石>羟基磷灰石>尿酸结石>胱氨酸结石(F=24.09、11.80,P<0.01);双能量扫描分析草酸钙、羟基磷灰石、尿酸、胱氨酸结石的敏感度分别为100.00%、84.60%、100.00%、100.00%,特异度分别为85.70%、100.00%、100.00%、100.00%,准确度分别为95.18%、97.59%、100.00%、100.00%。结论双源CT双能量成像技术可以准确分析体外泌尿系结石成分,对体内结石成分分析具有重要的临床价值。展开更多
文摘Objective To observe the value of preoperative CT radiomics models for predicting composition of in vivo urinary calculi.Methods Totally 543 urolithiasis patients were retrospectively enrolled and divided into calcium oxalate monohydrate stone group(group A,n=373),anhydrous uric acid stone group(group B,n=86),carbonate apatite group(group C,n=30),ammonium urate stone group(group D,n=28)and ammonium magnesium phosphate hexahydrate stone group(group E,n=26)according to the composition of calculi,also divided into training set and test set at the ratio of 7∶3.Radiomics features were extracted and screened based on plain CT images of urinary system.Five binary task models(model A—E corresponding to group A—E)and a quinary task model were constructed using least absolute shrinkage and selection operator algorithm for predicting the composition of calculi in vivo.Then receiver operating characteristic curves were drawn,and the area under the curves(AUC)were calculated to evaluate the predictive efficacy of binary task models,while the accuracy,precision,recall and F1 score were used to evaluate the predictive efficacy of the quinary task model.Results All binary task models had good efficacy for predicting the composition of urinary calculi in vivo,with AUC of 0.860—0.948 in training set and of 0.856—0.933 in test set.The accuracy,precision,recall and F1 score of the quinary task model for predicting the composition of in vivo urinary calculi was 82.25%,83.79%,46.23%and 0.596 in training set,respectively,while was 80.63%,75.26%,43.48%and 0.551 in test set,respectively.Conclusion Binary task radiomics models based on preoperative plain CT had good efficacy for predicting the composition of in vivo urinary calculi,while the quinary task radiomics model had high accuracy but relatively poor stability.
文摘目的探讨双源CT双能量成像技术对体外泌尿系结石成分分析的价值。材料与方法收集97例已知化学成分的泌尿系结石标本,结石成分包括草酸钙55例、羟基磷灰石13例、尿酸9例、胱氨酸4例、磷酸铵镁2例、混合结石14例,将结石编号后放入猪肾中进行双源CT双能量扫描,测量80 k V及140 k V下结石CT值,计算CT值差值及双能量指数(DEI),分析结石成分,计算每种结石利用双能量技术分析结石成分的敏感度、特异度及准确度。结果双能量分析结石成分结果为草酸钙59例、羟基磷灰石11例、尿酸9例、胱氨酸4例,混合结石14例。2例羟基磷灰石、2例磷酸镁铵双能量分析均为草酸钙结石,准确率为95.88%(93/97)。不同成分结石双能量扫描(80 k V与140 k V)CT值差值及DEI大小依次为:草酸钙结石>羟基磷灰石>尿酸结石>胱氨酸结石(F=24.09、11.80,P<0.01);双能量扫描分析草酸钙、羟基磷灰石、尿酸、胱氨酸结石的敏感度分别为100.00%、84.60%、100.00%、100.00%,特异度分别为85.70%、100.00%、100.00%、100.00%,准确度分别为95.18%、97.59%、100.00%、100.00%。结论双源CT双能量成像技术可以准确分析体外泌尿系结石成分,对体内结石成分分析具有重要的临床价值。
