Paper Info
Title
Differential diagnosis and feature visualization for thyroid nodules using computer-aided ultrasonic diagnosis system: initial clinical assessment
Abstract
To assess the diagnostic efficacy of the computer-aided ultrasonic diagnosis system (CAD system) in differentiating benign and malignant thyroid nodules. The images of 296 thyroid nodules were included in validation sets. The diagnostic efficacy of the CAD system was compared with that of junior physicians and senior physicians, as well as that of the combination diagnosis of the CAD system with junior physicians. The diagnostic efficacy of the CAD system for different sizes of thyroid nodules was compared. The diagnostic sensitivity and accuracy of the CAD system were higher than those of junior physicians (83.4% vs. 72.2%, 73.0% vs. 69.6%), but the diagnostic specificity of the CAD system was lower than that of junior physicians (62.1% vs. 66.9%). The diagnostic accuracy of the CAD system was lower than that of senior physicians (73.0% vs. 83.8%). However, the combination diagnosis of the CAD system with junior physicians had higher accuracy (81.8%) and AUC (0.842) than those of either the CAD system or junior physicians alone, and comparable diagnostic performance with those of senior physicians. The Kappa was 0.635 in the combination diagnosis of the CAD system with junior physicians, showing good consistency with the pathological results. The accuracy (76.4%) of the CAD system was the highest for nodules of 1–2 cm. The CAD system can effectively assist physicians to identify malignant and benign thyroid nodules, reduce the overdiagnosis and overtreatment of thyroid nodules, avoid unnecessary invasive fine needle aspiration, and improve the diagnostic accuracy of junior physicians.
Year
DOI
Venue
2022
10.1186/s12880-022-00874-7
BMC Medical Imaging
Keywords
DocType
Volume
Computer-aided diagnosis, Thyroid nodule, Ultrasonography, Diagnostic efficacy
Journal
22
Issue
ISSN
Citations 
1
1471-2342
0
PageRank 
References 
Authors
0.34
0
10
Name
Order
Citations
PageRank
Fang Xie100.34
Yu-Kun Luo211.30
Yu Lan300.34
Xiao-Qi Tian400.34
Ya-Qiong Zhu500.34
Zhuang Jin600.34
Ying Zhang716325.25
Ming-Bo Zhang800.34
Qing Song910.96
Yan Zhang1011518.87