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

OBJECTIVE

The common clinical techniques used for examining thyroid tumors include palpation, imaging, immunoassays and tissue biopsy. Ultrasonography 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.