Ultrasonographic characteristics of thyroid nodules - Prediction of malignancy

Citation
E. Koike et al., Ultrasonographic characteristics of thyroid nodules - Prediction of malignancy, ARCH SURG, 136(3), 2001, pp. 334-337
Citations number
21
Categorie Soggetti
Surgery,"Medical Research Diagnosis & Treatment
Journal title
ARCHIVES OF SURGERY
ISSN journal
00040010 → ACNP
Volume
136
Issue
3
Year of publication
2001
Pages
334 - 337
Database
ISI
SICI code
0004-0010(200103)136:3<334:UCOTN->2.0.ZU;2-5
Abstract
Background: High-resolution real-time ultrasonography (US) can detect chara cteristics 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 (greater than or equal to5 mm) in 309 patients comparing US characteristics and pathological resu lts. Setting: A center for the treatment of thyroid diseases where about 1400 th yroid operations are performed per year. Patients: Between January 1 and June 30, 1999, 309 patients were examined b y US before thyroidectomy. Main Outcome Measure: The US characteristics to predict malignancy for both follicular and nonfollicular neoplasms by means of multiple logistic regre ssion analysis. Results: The sensitivity of preoperative US diagnosis was 86.5% for nonfoll icular neoplasms and 18.2% for follicular neoplasms. The specificity was 92 .3% and 88.7%, respectively. According to multiple logistic regression anal ysis, margin, shape, echo structure, echogenicity, and calcification were r eliable indication of malignancy in nonfollicular neoplasms. According to a receiver operating characteristic curve constructed from this multiple log istic 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 reg ression analysis was applied. Conclusion: We can predict malignancy of nonfollicular neoplasms of the thy roid by using multiple logistic regression analysis based on only 5 feature s: margin, shape, echo structure, echogenicity, and calcification.