目的观察CT影像组学机器学习(ML)模型预测泌尿系结石经逆行输尿管软镜碎石术(RIRS)后清石率(SFR)的价值。方法 回顾性纳入216例接受RIRS的泌尿系结石患者并将其分为残余组(n=73)及无残余组(n=143)。以单因素及多因素logistic回归分析临...目的观察CT影像组学机器学习(ML)模型预测泌尿系结石经逆行输尿管软镜碎石术(RIRS)后清石率(SFR)的价值。方法 回顾性纳入216例接受RIRS的泌尿系结石患者并将其分为残余组(n=73)及无残余组(n=143)。以单因素及多因素logistic回归分析临床资料及结石CT表现,筛选RIRS后SFR独立预测因素。分别利用窗宽窗位归一化联合最大最小归一化(记为方法 a)、最大最小归一化(记为方法 b)、窗宽窗位归一化(记为方法 c)及无归一化(记为方法 d)对RIRS前腹部CT进行预处理,基于结石最佳影像组学特征建立ML模型[包括支持向量机(SVM)、逻辑回归(LR)和随机梯度下降(SGD)模型]并筛选其中最佳者;行RUSS及改良S. T. O. N. E评分预测RIRS后泌尿系结石SFR;联合独立预测因素及最佳ML模型构建联合模型。评估各模型及评分系统的预测效能。结果 结石数量、最大结石CT值及体积均为RIRS后SFR的独立预测因素(P均<0.05)。以方法 b预处理后图像构建SVM模型的曲线下面积(AUC)最高(0.861),高于RUSS及改良S. T. O. N. E总评分(AUC=0.750、0.759,P均<0.05)而与联合模型的AUC差异无统计学意义(AUC=0.853,P=0.775)。结论 基于最大最小归一化法预处理CT图像构建的影像组学SVM模型可有效预测泌尿系结石经RIRS后SFR。展开更多
The nucleation, growth and aggregation of calcium oxalate(CaC 2O 4) crystals were comparatively investigated in five different mimetic systems: water, NaCl solution, artificial urine, healthy urine and lithogenic urin...The nucleation, growth and aggregation of calcium oxalate(CaC 2O 4) crystals were comparatively investigated in five different mimetic systems: water, NaCl solution, artificial urine, healthy urine and lithogenic urine by using scanning electron microscopy(SEM). The effects of original concentration of calcium ion and oxalate ion and crystallization time on the morphology, density and the size of CaC 2O 4 crystals were discussed. In lithogenic urine, calcium oxalate monohydrate(COM) crystals were the dominant phase. However, a mixture of COM and calcium oxalate dihydrate(COD) with a molar ratio of about 3∶2 was obtained in the healthy urine. COD has a less affinity for renal tubule cell surface, so COD is easy to be expelled out from body and there is a less probability of stone-forming in the healthy urine. The fastest nucleation and growth of CaC 2O 4 crystals were obtained in water and NaCl solution, respectively. The size of CaC 2O 4 crystals decreases in the following order: NaCl solution>artificial urine>lithogenic urine>healthy urine>water.展开更多
目的采用Meta分析探讨双能CT对体内尿酸盐结石及草酸盐结石的诊断价值。方法检索2005年1月—2015年12月中国学术期刊网络出版总库、维普期刊数据库、中国生物医学文献数据库、万方数据库、Cochrane图书馆、web of science、PubMed及Else...目的采用Meta分析探讨双能CT对体内尿酸盐结石及草酸盐结石的诊断价值。方法检索2005年1月—2015年12月中国学术期刊网络出版总库、维普期刊数据库、中国生物医学文献数据库、万方数据库、Cochrane图书馆、web of science、PubMed及Elsevier-SDOL,提取运用双能CT分析体内泌尿系结石成分的相关文献。采用诊断准确性研究的质量评价工具-2对纳入文献进行质量评估,Meta-disc 1.4软件进行Meta分析。结果纳入中英文文献共12篇。诊断尿酸盐结石汇总敏感度、特异度分别为0.97[95%CI为(0.91,0.99)]、0.99[95%CI为(0.98,1.00)];诊断草酸盐结石汇总敏感度、特异度分别为0.99[95%CI为(0.97,1.00)]、0.90[95%CI为(0.85,0.93)]。结论双能CT诊断体内尿酸盐、草酸盐结石具有较高的敏感度和特异度,有助于指导临床选择治疗方案。展开更多
文摘目的观察CT影像组学机器学习(ML)模型预测泌尿系结石经逆行输尿管软镜碎石术(RIRS)后清石率(SFR)的价值。方法 回顾性纳入216例接受RIRS的泌尿系结石患者并将其分为残余组(n=73)及无残余组(n=143)。以单因素及多因素logistic回归分析临床资料及结石CT表现,筛选RIRS后SFR独立预测因素。分别利用窗宽窗位归一化联合最大最小归一化(记为方法 a)、最大最小归一化(记为方法 b)、窗宽窗位归一化(记为方法 c)及无归一化(记为方法 d)对RIRS前腹部CT进行预处理,基于结石最佳影像组学特征建立ML模型[包括支持向量机(SVM)、逻辑回归(LR)和随机梯度下降(SGD)模型]并筛选其中最佳者;行RUSS及改良S. T. O. N. E评分预测RIRS后泌尿系结石SFR;联合独立预测因素及最佳ML模型构建联合模型。评估各模型及评分系统的预测效能。结果 结石数量、最大结石CT值及体积均为RIRS后SFR的独立预测因素(P均<0.05)。以方法 b预处理后图像构建SVM模型的曲线下面积(AUC)最高(0.861),高于RUSS及改良S. T. O. N. E总评分(AUC=0.750、0.759,P均<0.05)而与联合模型的AUC差异无统计学意义(AUC=0.853,P=0.775)。结论 基于最大最小归一化法预处理CT图像构建的影像组学SVM模型可有效预测泌尿系结石经RIRS后SFR。
文摘The nucleation, growth and aggregation of calcium oxalate(CaC 2O 4) crystals were comparatively investigated in five different mimetic systems: water, NaCl solution, artificial urine, healthy urine and lithogenic urine by using scanning electron microscopy(SEM). The effects of original concentration of calcium ion and oxalate ion and crystallization time on the morphology, density and the size of CaC 2O 4 crystals were discussed. In lithogenic urine, calcium oxalate monohydrate(COM) crystals were the dominant phase. However, a mixture of COM and calcium oxalate dihydrate(COD) with a molar ratio of about 3∶2 was obtained in the healthy urine. COD has a less affinity for renal tubule cell surface, so COD is easy to be expelled out from body and there is a less probability of stone-forming in the healthy urine. The fastest nucleation and growth of CaC 2O 4 crystals were obtained in water and NaCl solution, respectively. The size of CaC 2O 4 crystals decreases in the following order: NaCl solution>artificial urine>lithogenic urine>healthy urine>water.
文摘目的采用Meta分析探讨双能CT对体内尿酸盐结石及草酸盐结石的诊断价值。方法检索2005年1月—2015年12月中国学术期刊网络出版总库、维普期刊数据库、中国生物医学文献数据库、万方数据库、Cochrane图书馆、web of science、PubMed及Elsevier-SDOL,提取运用双能CT分析体内泌尿系结石成分的相关文献。采用诊断准确性研究的质量评价工具-2对纳入文献进行质量评估,Meta-disc 1.4软件进行Meta分析。结果纳入中英文文献共12篇。诊断尿酸盐结石汇总敏感度、特异度分别为0.97[95%CI为(0.91,0.99)]、0.99[95%CI为(0.98,1.00)];诊断草酸盐结石汇总敏感度、特异度分别为0.99[95%CI为(0.97,1.00)]、0.90[95%CI为(0.85,0.93)]。结论双能CT诊断体内尿酸盐、草酸盐结石具有较高的敏感度和特异度,有助于指导临床选择治疗方案。
