目的探讨基于增强计算机断层扫描(computed tomography,CT)影像组学在鉴别超声甲状腺成像报告和数据系统(thyroid imaging reporting and data system,TI-RADS)诊断为4A、4B类甲状腺微小结节良恶性的价值。方法回顾性入组2018年1月至202...目的探讨基于增强计算机断层扫描(computed tomography,CT)影像组学在鉴别超声甲状腺成像报告和数据系统(thyroid imaging reporting and data system,TI-RADS)诊断为4A、4B类甲状腺微小结节良恶性的价值。方法回顾性入组2018年1月至2022年1月经过术后病理证实甲状腺结节患者300例(115例良性,185例恶性)。从增强CT图像中提取影像组学特征分别构建动脉期、静脉期、延迟期及多期联合(动脉期+静脉期+延迟期)影像组学模型,联合诊断效能最高的影像组学模型和临床特征构建综合诊断模型并绘制诺莫图。使用接受者工作特征曲线下面积(area under the receiver operating characteristic curve,AUC)评估模型的诊断性能,决策曲线分析(decision curve analysis,DCA)评价模型的临床效用。结果多期联合组学模型的诊断表现(训练集AUC vs测试集AUC:0.814 vs 0.718)优于单一期像组学模型(动脉期:0.730 vs 0.601;静脉期:0.794 vs 0.678;延迟期:0.793 vs 0.622);与临床模型(训练集AUC:0.732;测试集AUC:0.766)和多期联合组学模型相比,综合诊断模型在训练集(AUC:0.876)和测试集(AUC:0.813)均具有更好的诊断表现。决策曲线分析表明,该综合诊断模型具有更高的临床应用价值。结论增强CT影像组学能够在术前有效鉴别TI-RADS 4A和4B类甲状腺微小结节的良恶性。展开更多
Purpose: The complexity of chest radiography (CXR) is a source of variability in its interpretation. We assessed the effect of an interpretation grid on the detection of CXR anomalies and radio- graphic diagnosis of t...Purpose: The complexity of chest radiography (CXR) is a source of variability in its interpretation. We assessed the effect of an interpretation grid on the detection of CXR anomalies and radio- graphic diagnosis of tuberculosis in an endemic area for tuberculosis. Methods: The study was conducted in Yaounde (Cameroon). Six observers (2 pulmonologists, 2 radiologists and 2 senior residents in medical imaging) interpreted 47 frontal CXR twice two months apart without (R1) and with (R2) the aid of an interpretation grid. We focused on the detection of micro nodules (n = 16), cavitations (n = 12), pleural effusion (n = 6), adenomegaly (n = 6), and diagnosis of tuberculosis (n = 23) and cancer (n = 7). Results: The average score for accurate detection of elementary lesions was 40.4% [95%CI: 25% - 58.3%] in R1 and 52.1% [36.9% - 65.3%] in R2. The highest im- provement was observed for micro nodules (19.8%). Cavitations had the highest proportions of accurate detections (58.3% in R1 and 65.3% in R2). The average score of accurate diagnosis was 46.1% in R1 and 57.4% in R2. Accurate diagnosis improved by 3.6% for tuberculosis and 19% for cancer between R1 and R2. Intra-observer agreement was higher for the diagnosis of cancers (0.22 ≤ k ≤ 1) than for diagnosing tuberculosis (0.21 ≤ k ≤ 0.68). Inter-observer agreement was highly variable with a modest improvement for the diagnosis of tuberculosis in R2. Conclusion: Standardized interpretation scheme improved the detection of CXR anomalies and diagnosis of tuberculosis. It significantly improved inter-observer’s agreement in diagnosing tuberculosis but not in detecting most lesions.展开更多
文摘目的探讨基于增强计算机断层扫描(computed tomography,CT)影像组学在鉴别超声甲状腺成像报告和数据系统(thyroid imaging reporting and data system,TI-RADS)诊断为4A、4B类甲状腺微小结节良恶性的价值。方法回顾性入组2018年1月至2022年1月经过术后病理证实甲状腺结节患者300例(115例良性,185例恶性)。从增强CT图像中提取影像组学特征分别构建动脉期、静脉期、延迟期及多期联合(动脉期+静脉期+延迟期)影像组学模型,联合诊断效能最高的影像组学模型和临床特征构建综合诊断模型并绘制诺莫图。使用接受者工作特征曲线下面积(area under the receiver operating characteristic curve,AUC)评估模型的诊断性能,决策曲线分析(decision curve analysis,DCA)评价模型的临床效用。结果多期联合组学模型的诊断表现(训练集AUC vs测试集AUC:0.814 vs 0.718)优于单一期像组学模型(动脉期:0.730 vs 0.601;静脉期:0.794 vs 0.678;延迟期:0.793 vs 0.622);与临床模型(训练集AUC:0.732;测试集AUC:0.766)和多期联合组学模型相比,综合诊断模型在训练集(AUC:0.876)和测试集(AUC:0.813)均具有更好的诊断表现。决策曲线分析表明,该综合诊断模型具有更高的临床应用价值。结论增强CT影像组学能够在术前有效鉴别TI-RADS 4A和4B类甲状腺微小结节的良恶性。
文摘Purpose: The complexity of chest radiography (CXR) is a source of variability in its interpretation. We assessed the effect of an interpretation grid on the detection of CXR anomalies and radio- graphic diagnosis of tuberculosis in an endemic area for tuberculosis. Methods: The study was conducted in Yaounde (Cameroon). Six observers (2 pulmonologists, 2 radiologists and 2 senior residents in medical imaging) interpreted 47 frontal CXR twice two months apart without (R1) and with (R2) the aid of an interpretation grid. We focused on the detection of micro nodules (n = 16), cavitations (n = 12), pleural effusion (n = 6), adenomegaly (n = 6), and diagnosis of tuberculosis (n = 23) and cancer (n = 7). Results: The average score for accurate detection of elementary lesions was 40.4% [95%CI: 25% - 58.3%] in R1 and 52.1% [36.9% - 65.3%] in R2. The highest im- provement was observed for micro nodules (19.8%). Cavitations had the highest proportions of accurate detections (58.3% in R1 and 65.3% in R2). The average score of accurate diagnosis was 46.1% in R1 and 57.4% in R2. Accurate diagnosis improved by 3.6% for tuberculosis and 19% for cancer between R1 and R2. Intra-observer agreement was higher for the diagnosis of cancers (0.22 ≤ k ≤ 1) than for diagnosing tuberculosis (0.21 ≤ k ≤ 0.68). Inter-observer agreement was highly variable with a modest improvement for the diagnosis of tuberculosis in R2. Conclusion: Standardized interpretation scheme improved the detection of CXR anomalies and diagnosis of tuberculosis. It significantly improved inter-observer’s agreement in diagnosing tuberculosis but not in detecting most lesions.
