Trial reportPloS one2021
Diagnostic performance evaluation of different TI-RADS using ultrasound computer-aided diagnosis of thyroid nodules: An experience with adjusted settings.
Trial report in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 21 citations in OpenAlex.
- Diagnostic Performance of Ultrasound vs Ultrasound-Guided FNAC in Thyroid Nodules: Data From the ElaTION Trial.The Journal of clinical endocrinology and metabolism · 2025Trial
- Artificial intelligence in thyroid nodules and cancer: clinical validation and real-world performance.Endocrine connections · 2026Article
- Article
- Article
- ChatGPT-4 Vision: a promising tool for diagnosing thyroid nodules.Frontiers in medicine · 2025Article
- Monitoring Thyrotropin in Veterans With Thyroid Nodules.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2023Article
- Combined Shear Wave Elastography and EU TIRADS in Differentiating Malignant and Benign Thyroid Nodules.Cancers · 2022Article
- Concordance between TIRADS and Cytology in Thyroid Nodule.Iranian journal of otorhinolaryngology · 2022Article
- The Use of Internet of Things and Cloud Computing Technology in the Performance Appraisal Management of Innovation Capability of University Scientific Research Team.Computational intelligence and neuroscience · 2022Article
- Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThyroid cancer diagnosis has evolved to include computer-aided diagnosis (CAD) approaches to overcome the limitations of human ultrasound feature assessment. This study aimed to evaluate the diagnostic performance of a CAD system in thyroid nodule differentiation using varied settings.
methodsUltrasound images of 205 thyroid nodules from 198 patients were analysed in this retrospective study. AmCAD-UT software was used at default settings and 3 adjusted settings to diagnose the nodules. Six risk-stratification systems in the software were used to classify the thyroid nodules: The American Thyroid Association (ATA), American College of Radiology Thyroid Imaging, Reporting, and Data System (ACR-TIRADS), British Thyroid Association (BTA), European Union (EU-TIRADS), Kwak (2011) and the Korean Society of Thyroid Radiology (KSThR). The diagnostic performance of CAD was determined relative to the histopathology and/or cytology diagnosis of each nodule.
resultsAt the default setting, EU-TIRADS yielded the highest sensitivity, 82.6% and lowest specificity, 42.1% while the ATA-TIRADS yielded the highest specificity, 66.4%. Kwak had the highest AUROC (0.74) which was comparable to that of ACR, ATA, and KSThR TIRADS (0.72, 0.73, and 0.70 respectively). At a hyperechoic foci setting of 3.5 with other settings at median values; ATA had the best-balanced sensitivity, specificity and good AUROC (70.4%; 67.3% and 0.71 respectively).
conclusionThe default setting achieved the best diagnostic performance with all TIRADS and was best for maximizing the sensitivity of EU-TIRADS. Adjusting the settings by only reducing the sensitivity to echogenic foci may be most helpful for improving specificity with minimal change in sensitivity.
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