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Autor(en) / Beteiligte
Titel
Additional Value of Superb Microvascular Imaging for Thyroid Nodule Classification with the Thyroid Imaging Reporting and Data System
Ist Teil von
  • Ultrasound in medicine & biology, 2019-08, Vol.45 (8), p.2040-2048
Ort / Verlag
England: Elsevier Inc
Erscheinungsjahr
2019
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • Superb microvascular imaging (SMI) is an innovative vascular imaging technique for ultrasound (US). Compared with conventional color Doppler imaging (CDI) and power Doppler imaging (PDI), SMI can detect more blood flow in thyroid nodules. In this study, a total of 203 thyroid nodules (160 benign nodules, 43 malignant nodules) in 195 patients were assessed with the Thyroid Imaging Reporting and Data System (TI-RADS) published by the American College of Radiology in 2017) and SMI. With TI-RADS alone, 24 (15.0%), 76 (47.5%), 65 (40.6%) and 39 (24.4%) thyroid nodules were classified as TR2, TR3, TR4 and TR5, respectively. However, with the combination of TI-RADS and SMI, 31 (19.4%), 79 (49.4%), 44 (27.5%) and 49 (30.6%) thyroid nodules were classified as TR2, TR3, TR4 and TR5, respectively. The area under the receiver operating characteristic curves for the combination (0.952) was larger than that for TI-RADS alone (0.883) (Z = 3.478, p = 0.001). The efficiency of TI-RADS alone and the TI-RADS + SMI combination in diagnosing thyroid nodules was determined for all except TR2 nodules. Although no significant differences between the methods were observed for TR3 and TR5 thyroid nodules (p > 0.05), the diagnostic efficiency of TI-RADS + SMI for TR4 thyroid nodules was higher than that of TI-RADS alone for TR4 nodules (p < 0.05). This study indicated that the vascularity of thyroid nodules can be well characterized using SMI, and the combined use of gray-scale US and SMI can improve the diagnostic performance of TI-RADS for TR4 thyroid nodules.
Sprache
Englisch
Identifikatoren
ISSN: 0301-5629
eISSN: 1879-291X
DOI: 10.1016/j.ultrasmedbio.2019.05.001
Titel-ID: cdi_proquest_miscellaneous_2232116306

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