Reverter Jordi L, Vázquez Federico, Puig-Domingo Manuel
Endocrinology and Nutrition Service, Department of Medicine, Germans Trias i Pujol Health Science Research Institute and Hospital, Universitat Autònoma de Barcelona, Badalona, Spain.
Center for Biomedical Network Research on Rare Diseases (CIBERER), Instituto Carlos III, Madrid, Spain.
AJR Am J Roentgenol. 2019 Jul;213(1):169-174. doi: 10.2214/AJR.18.20740. Epub 2019 Apr 11.
Ultrasound-based stratification of the malignancy risk of thyroid nodules has potential variability. The purpose of this study is to evaluate the diagnostic effectiveness of the first commercially available system for computer-aided diagnosis (CADx) imaging analysis. Ultrasound images of 300 thyroid nodules (135 of which were malignant) acquired before surgical treatment were retrospectively reviewed by a thyroid expert, and his classification of each image was then compared with the classification rendered by an image analysis program (AmCAD-UT, AmCAD Biomed). The American Thyroid Association (ATA) classification system, the European Thyroid Imaging Reporting and Data System (EU-TIRADS), and the classification system jointly proposed by American and Italian associations of clinical endocrinologists (the American Association of Clinical Endocrinologists [AACE], the American College of Endocrinology [ACE], and Associazione Medici Endocrinologi [AME]) were used for risk stratification. The diagnostic performance of the thyroid expert when the ATA system was used was as follows: sensitivity, 87.0%; specificity, 91.2%; positive predictive value, 90.5%; and negative predictive value, 90.9%. Compared with the expert, the CADx program, when used with the three classification systems, had a similar sensitivity but a lower specificity and positive predictive value. Regarding the negative predictive value, the results of the expert did not differ from those of the CADx program when it applied the ATA classification system (90.9% vs 86.3%; = 0.07). The ROC AUC value was 0.88 for the expert clinician and 0.72 for the CADx program when the ATA classification system was used. The CADx ultrasound image analysis program described in the present study is useful for risk stratification of thyroid nodules, but it does not perform better than a sonography expert.
基于超声对甲状腺结节恶性风险进行分层存在潜在变异性。本研究旨在评估首个商用计算机辅助诊断(CADx)成像分析系统的诊断效能。一位甲状腺专家对300个甲状腺结节(其中135个为恶性)手术治疗前获取的超声图像进行回顾性分析,然后将其对每个图像的分类与图像分析程序(AmCAD-UT,AmCAD Biomed)给出的分类进行比较。采用美国甲状腺协会(ATA)分类系统、欧洲甲状腺影像报告和数据系统(EU-TIRADS)以及美国和意大利临床内分泌学家协会联合提出的分类系统(美国临床内分泌学家协会[AACE]、美国内分泌学会[ACE]和意大利内分泌医师协会[AME])进行风险分层。当使用ATA系统时,甲状腺专家的诊断性能如下:灵敏度为87.0%;特异度为91.2%;阳性预测值为90.5%;阴性预测值为90.9%。与专家相比,CADx程序在使用这三种分类系统时,灵敏度相似,但特异度和阳性预测值较低。关于阴性预测值,当应用ATA分类系统时,专家的结果与CADx程序的结果无差异(90.9%对86.3%;P = 0.07)。当使用ATA分类系统时,专家临床医生的ROC曲线下面积(AUC)值为0.88,CADx程序的为0.72。本研究中描述的CADx超声图像分析程序对甲状腺结节的风险分层有用,但性能不比超声专家更好。