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False-Positive Malignant Diagnosis of Nodule Mimicking Lesions by Computer-Aided Thyroid Nodule Analysis in Clinical Ultrasonography Practice

Overview
Specialty Radiology
Date 2020 Jun 11
PMID 32517227
Citations 2
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Abstract

This study aims to test computer-aided diagnosis (CAD) for thyroid nodules in clinical ultrasonography (US) practice with a focus towards identifying thyroid entities associated with CAD system misdiagnoses. Two-hundred patients referred to thyroid US were prospectively enrolled. An experienced radiologist evaluated the thyroid nodules and saved axial images for further offline blinded analysis using a commercially available CAD system. To represent clinical practice, not only true nodules, but mimicking lesions were also included. Fine needle aspiration biopsy (FNAB) was performed according to present guidelines. US features and thyroid entities significantly associated with CAD system misdiagnosis were identified along with the diagnostic accuracy of the radiologist and the CAD system. Diagnostic specificity regarding the radiologist was significantly ( < 0.05) higher than when compared with the CAD system (88.1% vs. 40.5%) while no significant difference was found in the sensitivity (88.6% vs. 80%). Focal inhomogeneities and true nodules in thyroiditis, nodules with coarse calcification and inspissated colloid cystic nodules were significantly ( < 0.05) associated with CAD system misdiagnosis as false-positives. The commercially available CAD system is promising when used to exclude thyroid malignancies, however, it currently may not be able to reduce unnecessary FNABs, mainly due to the false-positive diagnoses of nodule mimicking lesions.

Citing Articles

Artificial intelligence in thyroid ultrasound.

Cao C, Li Q, Tong J, Shi L, Li W, Xu Y Front Oncol. 2023; 13:1060702.

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Diagnostic accuracy of S-Detect in distinguishing benign and malignant thyroid nodules: A meta-analysis.

Zhong L, Wang C PLoS One. 2022; 17(8):e0272149.

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