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- Title
Clinical Value of Artificial Intelligence‐Based Computer‐Aided Diagnosis System Versus Contrast‐Enhanced Ultrasound for Differentiation of Benign From Malignant Thyroid Nodules in Different Backgrounds.
- Authors
Liu, Ting; Wu, Chuang; Wang, Guojuan; Jia, Yingying; Zhu, Yangyang; Nie, Fang
- Abstract
Objectives: The aim of this study was to compare the value of the AI‐SONIC ultrasound‐assisted diagnosis system versus contrast‐enhanced ultrasound (CEUS) for differential diagnosis of thyroid nodules in diffuse and non‐diffuse backgrounds. Methods: A total of 555 thyroid nodules with pathologically confirmed diagnosis were included in this retrospective study. The diagnostic efficacies of AI‐SONIC and CEUS for differentiating benign from malignant nodules in diffuse and non‐diffuse backgrounds were evaluated, with pathological diagnosis as the gold standard. Results: The agreement between AI‐SONIC diagnosis and pathological diagnosis was moderate in diffuse backgrounds (κ = 0.417) and almost perfect in non‐diffuse backgrounds (κ = 0.81). The agreement between CEUS diagnosis and pathological diagnosis was substantial in diffuse backgrounds (κ = 0.684) and moderate in non‐diffuse backgrounds (κ = 0.407). In diffuse backgrounds, AI‐SONIC had slightly higher sensitivity (95.7 vs 89.4%, P =.375), but CEUS had significantly higher specificity (80.0 vs 40.0%, P =.008). In non‐diffuse background, AI‐SONIC had significantly higher sensitivity (96.2 vs 73.4%, P <.001), specificity (82.9 vs 71.2%, P =.007), and negative predictive value (90.3 vs 53.3%, P <.001). Conclusion: In non‐diffuse backgrounds, AI‐SONIC is superior to CEUS for differentiating malignant from benign thyroid nodules. In diffuse backgrounds, AI‐SONIC could be useful for screening of cases to detect suspicious nodules requiring further examination by CEUS.
- Subjects
THYROID cancer; CONTRAST-enhanced ultrasound; ARTIFICIAL intelligence; THYROID nodules; DIFFERENTIAL diagnosis; SPACE surveillance
- Publication
Journal of Ultrasound in Medicine, 2023, Vol 42, Issue 8, p1757
- ISSN
0278-4297
- Publication type
Article
- DOI
10.1002/jum.16195