Literature DB >> 21075018

An ultrasound model to discriminate the risk of thyroid carcinoma.

José Miguel Domínguez1, René Baudrand, Jaime Cerda, Claudia Campusano, Carlos Fardella, Eugenio Arteaga, Francisco Cruz, Antonieta Solar, Tatiana Arias, Lorena Mosso.   

Abstract

RATIONALE AND
OBJECTIVES: Thyroid nodules are common on ultrasonographic examination and are mostly benign. Ultrasound characteristics may help discriminate thyroid carcinoma (TC) from benign nodules. The aims of this study were to identify ultrasonographic characteristics associated with TC and to validate a previously proposed model based on the presence of three ultrasonographic characteristics.
MATERIALS AND METHODS: From a protocolized prospective registry of 1108 fine needle aspiration biopsies performed during a 16-month period at an ambulatory center, the ultrasonographic characteristics of TC and non-TC biopsies were compared. Adjusted odds ratios (ORs) and likelihood ratios for TC were estimated for eight combinations of three previously identified characteristics (microcalcifications, hypoechogenicity, and irregular borders).
RESULTS: Microcalcifications (OR, 6.6; 95% confidence interval [CI], 4.4-9.9), hypoechogenicity (OR, 4.7; 95% CI, 2.8-8.0), and irregular borders (OR, 4.3; 95% CI, 2.8-6.5) were independently associated with TC. When added to a logistic regression model, the three ultrasonographic characteristics remained statistically significant. In the absence of these three features, the likelihood ratio for TC was 0.1 (95% CI, 0.0-0.2), while in their simultaneous presence, the likelihood ratio was 11 (95% CI, 6.6-19.0).
CONCLUSIONS: The absence or simultaneous presence of three simple ultrasonographic characteristics generates a large change of pretest probability of TC and could avoid unnecessary fine needle aspiration biopsy. Copyright Â
© 2011 AUR. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21075018     DOI: 10.1016/j.acra.2010.09.018

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  4 in total

1.  Distribution patterns of microcalcifications in suspected thyroid carcinoma: a classification method helpful for diagnosis.

Authors:  Chun-Ping Ning; Qing-Lian Ji; Shi-Bao Fang; Hong-Qiao Wang; Yan-Mi Zhong; Hai-Tao Niu
Journal:  Eur Radiol       Date:  2018-01-08       Impact factor: 5.315

2.  Thyroid nodule ultrasound: technical advances and future horizons.

Authors:  Andrew S McQueen; Kunwar S S Bhatia
Journal:  Insights Imaging       Date:  2015-03-05

3.  Evaluating thyroid nodules: predicting and selecting malignant nodules for fine-needle aspiration (FNA) cytology.

Authors:  Ravi Kumar Lingam; Mohammad Haroon Qarib; Neil Samuel Tolley
Journal:  Insights Imaging       Date:  2013-05-28

4.  A new computational model for human thyroid cancer enhances the preoperative diagnostic efficacy.

Authors:  Tuo Li; Jianguo Sheng; Weiqin Li; Xin Zhang; Hongyu Yu; Xueyun Chen; Jianquan Zhang; Quancai Cai; Yongquan Shi; Zhimin Liu
Journal:  Oncotarget       Date:  2015-09-29
  4 in total

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