Computer-Aided Diagnosis of Thyroid Nodules via Ultrasonography: Initial Clinical Experience
Korean Journal of Radiology
; : 665-672, 2018.
Article
Dans En
| WPRIM
| ID: wpr-716269
Responsable en Bibliothèque :
WPRO
ABSTRACT
OBJECTIVE: To prospectively evaluate the diagnostic performance of computer-aided diagnosis (CAD) for detection of thyroid cancers via ultrasonography (US). MATERIALS AND METHODS: This study included 50 consecutive patients with 117 thyroid nodules on US during the period between June 2016 and July 2016. A radiologist performed US examinations using real-time CAD integrated into a US scanner. We compared the diagnostic performance of radiologist, the CAD system, and the CAD-assisted radiologist for the detection of thyroid cancers. RESULTS: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of the CAD system were 80.0, 88.1, 83.3, 85.5, and 84.6%, respectively, and were not significantly different from those of the radiologist (p > 0.05). The CAD-assisted radiologist showed improved diagnostic sensitivity compared with the radiologist alone (92.0% vs. 84.0%, p = 0.037), while the specificity and PPV were reduced (85.1% vs. 95.5%, p = 0.005 and 82.1% vs. 93.3%, p = 0.008). The radiologist assisted by the CAD system exhibited better diagnostic sensitivity and NPV than the CAD system alone (92.0% vs. 80.0%, p = 0.009 and 93.4% vs. 88.9%, p = 0.013), while the specificities and PPVs were not significantly different (88.1% vs. 85.1%, p = 0.151 and 83.3% vs. 82.1%, p = 0.613, respectively). CONCLUSION: The CAD system may be an adjunct to radiological intervention in the diagnosis of thyroid cancer.
Texte intégral:
1
Indice:
WPRIM
Sujet Principal:
Glande thyroide
/
Tumeurs de la thyroïde
/
Intelligence artificielle
/
Études prospectives
/
Échographie
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Sensibilité et spécificité
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Nodule thyroïdien
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Diagnostic
Type d'étude:
Diagnostic_studies
/
Observational_studies
Limites du sujet:
Humans
langue:
En
Texte intégral:
Korean Journal of Radiology
Année:
2018
Type:
Article