4.6 Article

A computer-aided diagnosis system for the assessment and characterization of low-to-high suspicion thyroid nodules on ultrasound

Journal

RADIOLOGIA MEDICA
Volume 124, Issue 2, Pages 118-125

Publisher

SPRINGER-VERLAG ITALIA SRL
DOI: 10.1007/s11547-018-0942-z

Keywords

Computer-aided diagnosis; Nodule; Thyroid; Ultrasound

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Aim of the studyTo compare the diagnostic performance of a commercially available computer-aided diagnosis (CAD) system for thyroid ultrasound (US) with that of a non-computer-aided radiologist in the characterization of low-to-high suspicion thyroid nodules.MethodsThis retrospective study included a consecutive series of adult patients referred for US-guided fine-needle aspiration biopsy (FNAB) of a thyroid nodule. All patients were eligible for thyroid nodule FNAB according to the current international guidelines. An interventional radiologist experienced in thyroid imaging acquired the US images subsequently used for post-processing, performed FNAB and provided the US features of each nodule. A radiology resident and an endocrinology resident in consensus performed post-processing using the CAD system to assess the same nodule characteristics. The diagnostic performance and agreement of US features between the CAD system and the radiologist were compared.ResultsSixty-two patients (50 F; age 6012years) were enrolled: 77.4% (48/62) of thyroid nodules were benign, 22.6% (14/62) were undetermined to malignant and required follow-up or surgery. Interobserver agreement between the CAD system and the radiologist was substantial for orientation (K=0.69), fair for composition (K=0.36), echogenicity (K=0.36), K-TIRADS (K=0.29), and slight for margins (K=0.03). The radiologist demonstrated a significantly higher sensitivity than the CAD system (78.6% vs. 21.4%; P=0.008), while there was no statistical difference in specificity (66.7% vs. 81.3%; P=0.065).Conclusion This CAD system is less sensitive than an experienced radiologist and showed slight-to-substantial agreement with the radiologist for the characterization of thyroid nodules. Although it is an innovative tool with good potential, additional efforts are needed to improve its diagnostic performance.

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