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Published on: November 10, 2014
Ultrasonographic characteristics of thyroid nodules: prediction of malignancy
E Koike1, S Noguchi, H Yamashita
1Noguchi Thyroid Clinic and Hospital Foundation, 6-33 Noguchi Naka-machi, Beppu, Oita, 874-0932, Japan.
Background:
High-resolution real-time ultrasonography (US) can detect characteristics of thyroid nodules, but the US differentiation between malignant nodules and benign nodules is not well described.
Hypothesis:
Ultrasonography is useful for predicting malignancy of thyroid nodules.
Design:
A retrospective study of 329 thyroid nodules (> or =5 mm) in 309 patients comparing US characteristics and pathological results.
Setting:
A center for the treatment of thyroid diseases where about 1400 thyroid operations are performed per year.
Patients:
Between January 1 and June 30, 1999, 309 patients were examined by US before thyroidectomy.
Main Outcome Measure:
The US characteristics to predict malignancy for both follicular and nonfollicular neoplasms by means of multiple logistic regression analysis.
Results:
The sensitivity of preoperative US diagnosis was 86.5% for nonfollicular neoplasms and 18.2% for follicular neoplasms. The specificity was 92.3% and 88.7%, respectively. According to multiple logistic regression analysis, margin, shape, echo structure, echogenicity, and calcification were reliable indication of malignancy in nonfollicular neoplasms. According to a receiver operating characteristic curve constructed from this multiple logistic regression analysis, the best point not to overlook malignancy is the point at which sensitivity is 94% and specificity is 87%. The probability of malignancy at this point is greater than 0.2. For follicular neoplasms, ultrasonographic diagnosis was unreliable, even when multiple logistic regression analysis was applied.
Conclusion:
We can predict malignancy of nonfollicular neoplasms of the thyroid by using multiple logistic regression analysis based on only 5 features: margin, shape, echo structure, echogenicity, and calcification.
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