Hormone and Metabolic Research · 2018 · 29 citations · 6 references
MedicineOncologyRadiologyDiagnostic ImagingDiagnostic Nuclear MedicineDiagnostic RadiologyBenign Thyroid DiseaseThyroid CancerThyroid DisordersThyroid ImagingThyroid UltrasonographyThyroid UltrasoundFollicular Neoplasm DiagnosisFollicular Thyroid Neoplasm ImagingRadiology ReportingRadiology Reporting SystemsRisk Of Malignancy ReportingThyroid Imaging Interpretation CriteriaThyroid Imaging Reporting And Data SystemsThyroid Nodule Classification Systems
Recently, the American College of Radiology (ACR) proposed a Thyroid Imaging Reporting and Data System (TI-RADS) for thyroid nodules based on ultrasonographic features. It is important to validate this classification in different centres. The present study evaluated the risk of malignancy in solid nodules>1 cm using ACR TI-RADS. The risk of malignancy was defined including noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) and after its exclusion from malignant tumours. For the present study, the original images were revised, and each nodule was assigned to one of the TI-RADS levels proposed for solid nodules: TR3, TR4, or TR5. This risk of malignancy was significantly different for the three levels: 1.7%, 11.2%, and 60.6% for TR3, TR4, and TR5, respectively, when NIFTP was included, and 0.6%, 7.9%, and 60.2% for TR3, TR4, and TR5, respectively, when NIFTP was excluded from malignant tumours. The nodules corresponding to NIFTP were classified according to ACR as TR3 in 28.5% of cases, TR4 in 67.8%, and TR5 in only 3.5%. The nodules corresponding to cancer were classified according to ACR as TR3 in only 2.3% of cases, TR4 in 27%, and TR5 in 70.5%. In conclusion, this study shows the validity of the ACR TI-RADS for solid thyroid nodules, even after the exclusion of NIFTP from malignant tumours.
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William D. Middleton, Sharlene A. Teefey, Carl C. Reading et al. · American Journal of Roentgenology · 2018 · 202 citations
William D. Middleton, Sharlene A. Teefey, Carl C. Reading et al. · American Journal of Roentgenology · 2017 · 189 citations
Medicine, Biostatistics, Radiology +16
Angelo Lauria Pantano, Ernesto Maddaloni, Silvia Briganti et al. · European Journal of Endocrinology · 2018 · 113 citations
Medicine, Biostatistics, Pathology +17