TITLE

Binary logistic regression analysis of solid thyroid nodules imaged by high-frequency ultrasonography, acoustic radiation force impulse, and contrast-enhanced ultrasonography

AUTHOR(S)
LIANG, X.-N.; GUO, R.-J.; LI, S.; ZHENG, Z.-M.; LIANG, H.-D.
PUB. DATE
December 2014
SOURCE
European Review for Medical & Pharmacological Sciences;Dec2014, Vol. 18 Issue 23, p3601
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
OBJECTIVE: The common clinical techniques used for examining thyroid tumors include palpation, imaging, immunoassays and tissue biopsy. Ultrasonogra-phy is easy, non-invasive, non-radioactive and highly reproducible imaging technique; however, due to the disease polytropism, diagnosis may become difficult sometimes. Ultrasound elastography, particularly acoustic radiation force impulse (ARFI) imaging and contrast-enhanced ultrasonography (CEUS) have been successfully used to diagnose the thyroid tumors. The objective of this retrospective study was to analyze and compare the solid thyroid nodules imaged by high-frequency ultrasonography (HFUS), ARFI imaging, and CEUS. PATIENTS AND METHODS: For this purpose, images of the 80 solid thyroid nodules (58 benign and 22 malignant) with surgical pathology were obtained and data were compared using binary logistic regression analysis. RESULTS: Morphology (p < 0.001), and internal calcification (p = 0.007) were statistically different. The mean shear wave velocity (SWV) measured by ARFI was significantly different (p = 0.029). Three sets of comparison on CEUS (p = 0.019) and time to peak (TTP) of CEUS were significantly different (p = 0.001). The logistic regression analysis indicated that the morphology, mean SWV of ARFI and TTP were independent risk factors for malignancy. The diagnostic accuracy for solid thyroid nodules was 85.1% (68/80) and the area under the receiver operating characteristic (ROC) curve was 0.945±0.033. CONCLUSIONS: Logistic regression analysis can effectively screen significant parameters for the differential diagnosis of solid thyroid nodules imaged by ultrasonography.
ACCESSION #
100109619

 

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