Background:Dual-energy computed tomography(DECT)is purported to accurately distinguish uric acid stones from non-uric acid stones.However,whether DECT can accurately discriminate ammonium urate stones from uric acid s...Background:Dual-energy computed tomography(DECT)is purported to accurately distinguish uric acid stones from non-uric acid stones.However,whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown.Therefore,we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods:This research included two steps.For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones,178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled.For model construction,93,40,and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training,internal validation,and external validation sets,respectively.Radiomics features were extracted from non-contrast CT images,and the least absolute shrinkage and selection operator(LASSO)algorithm was used to develop a radiomics signature.Then,a radiomics model incorporating the radiomics signature and clinical predictors was constructed.The performance of the model(discrimination,calibration,and clinical usefulness)was evaluated.Results:When patients with ammonium urate stones were included in the analysis,the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased.Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT.A radiomics model incorporating the radiomics signature,urine pH value,and urine white blood cell count was constructed.The model achieved good calibration and discrimination{area under the receiver operating characteristic curve(AUC;95%confidence interval[CI]),0.944(0.899-0.989)},which was internally and externally validated with AUCs of 0.895(95%CI,0.796-0.995)and 0.870(95%CI,0.769-0.972),respectively.Decision curve analysis revealed the clinical usefulness of the model.Conclusions:DECT cannot accurately differentiate ammonium urate stones from uric acid stones.Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.展开更多
目的探讨双源CT双能量扫描线性融合技术对消除腰椎金属植入物伪影的临床应用价值。方法对33例腰椎金属植入术后复查的患者使用双源CT双能量扫描,对获得的80 k V及140 k V数据进行线性融合成像,所得图像为A组,模拟常规120 k V重建为B组,...目的探讨双源CT双能量扫描线性融合技术对消除腰椎金属植入物伪影的临床应用价值。方法对33例腰椎金属植入术后复查的患者使用双源CT双能量扫描,对获得的80 k V及140 k V数据进行线性融合成像,所得图像为A组,模拟常规120 k V重建为B组,分别进行多平面重建技术、容积显示和最大密度投影,并对重建后图像质量及伪影进行评估。结果线性融合像质量为优者分别为90%和33%;无伪影图像分别占91%和36%,两者差异有统计学意义(分别为Z=-5.74,P=0.00;Z=-6.74,P=0.00)。结论双源CT双能量线性融合技术能够非常准确有效的去除金属伪影,清晰显示腰椎金属内固定物的位置、形态及其他细微结构,双侧腰大肌不受伪影干扰显示清楚,图像质量较高,可满足诊断要求。展开更多
基金supported by the China Postdoctoral Science Foundation(Nos.2021TQ0387,2022M713625,and 2021M703709)the National Natural Science Foundation of China(Nos.82203188 and 81825016)+1 种基金Guangdong Provincial Clinical Research Center for Urological Diseases(No.2020B1111170006)the Guangdong Basic and Applied Basic Research Foundation(No.2020A1515111119)
文摘Background:Dual-energy computed tomography(DECT)is purported to accurately distinguish uric acid stones from non-uric acid stones.However,whether DECT can accurately discriminate ammonium urate stones from uric acid stones remains unknown.Therefore,we aimed to explore whether they can be accurately identified by DECT and to develop a radiomics model to assist in distinguishing them.Methods:This research included two steps.For the first purpose to evaluate the accuracy of DECT in the diagnosis of uric acid stones,178 urolithiasis patients who underwent preoperative DECT between September 2016 and December 2019 were enrolled.For model construction,93,40,and 109 eligible urolithiasis patients treated between February 2013 and October 2022 were assigned to the training,internal validation,and external validation sets,respectively.Radiomics features were extracted from non-contrast CT images,and the least absolute shrinkage and selection operator(LASSO)algorithm was used to develop a radiomics signature.Then,a radiomics model incorporating the radiomics signature and clinical predictors was constructed.The performance of the model(discrimination,calibration,and clinical usefulness)was evaluated.Results:When patients with ammonium urate stones were included in the analysis,the accuracy of DECT in the diagnosis of uric acid stones was significantly decreased.Sixty-two percent of ammonium urate stones were mistakenly diagnosed as uric acid stones by DECT.A radiomics model incorporating the radiomics signature,urine pH value,and urine white blood cell count was constructed.The model achieved good calibration and discrimination{area under the receiver operating characteristic curve(AUC;95%confidence interval[CI]),0.944(0.899-0.989)},which was internally and externally validated with AUCs of 0.895(95%CI,0.796-0.995)and 0.870(95%CI,0.769-0.972),respectively.Decision curve analysis revealed the clinical usefulness of the model.Conclusions:DECT cannot accurately differentiate ammonium urate stones from uric acid stones.Our proposed radiomics model can serve as a complementary diagnostic tool for distinguishing them in vivo.
文摘目的探讨双源CT双能量扫描线性融合技术对消除腰椎金属植入物伪影的临床应用价值。方法对33例腰椎金属植入术后复查的患者使用双源CT双能量扫描,对获得的80 k V及140 k V数据进行线性融合成像,所得图像为A组,模拟常规120 k V重建为B组,分别进行多平面重建技术、容积显示和最大密度投影,并对重建后图像质量及伪影进行评估。结果线性融合像质量为优者分别为90%和33%;无伪影图像分别占91%和36%,两者差异有统计学意义(分别为Z=-5.74,P=0.00;Z=-6.74,P=0.00)。结论双源CT双能量线性融合技术能够非常准确有效的去除金属伪影,清晰显示腰椎金属内固定物的位置、形态及其他细微结构,双侧腰大肌不受伪影干扰显示清楚,图像质量较高,可满足诊断要求。
