Evaluation of Ultrasound Elastography Combined With Chi-Square Automatic Interactive Detector in Reducing Unnecessary Fine-Needle Aspiration on TIRADS 4 Thyroid Nodules

Abstract

Background: Conventional ultrasound diagnosis of thyroid nodules (TNs) had a high false-positive rate, resulting in many unnecessary fine-needle aspirations (FNAs). Objective: This study aimed to establish a simple algorithm to reduce unnecessary FNA on TIRADS 4 TNs using different quantitative parameters of ultrasonic elasticity and chi-square automatic interactive detector (CHAID) method. Methods: From January 2020 to May 2021, 432 TNs were included in the study, which were confirmed by FNA or surgical pathology. Each TN was examined using conventional ultrasound, sound touch elastography, and Shell measurement function. The quantitative parameters E and Eshell were recorded, and the Eshell/E values were calculated for each TN. The diagnostic performance of the quantitative parameters was evaluated using the receiver operating characteristic curves. The CHAID was used to classify and analyze the quantitative parameters, and the prediction model was established. Results: A total of 226 TNs were malignant and 206 were benign. Eshell and Eshell/E ratio were included in the classification algorithm, which showed a depth of two ramifications (Eshell/E ≤ 0.988 or 0.988–1.043 or >1.043; if Eshell/E ≤ 0.988, then Eshell ≤ 64.0 or 64.0–74.0 or >74.0; if Eshell/E = 0.988–1.043, then Eshell ≤ 66.0 or > 66.0; if Eshell/E >1.043, then Eshell ≤ 69.0 or >69.0). The unnecessary FNAs could have been avoided in 57.3% of the cases using this algorithm. Conclusion: The prediction model using quantitative parameters had high diagnostic performance; it could quickly distinguish benign lesions and avoid subjective influence to some extent.