APPLICATION OF SHELL TECHNIQUE IN C-TIRADS COMBINED WITH STE IN DIAGNOSIS OF C-TIRADS GRADE 4-5 NODULES

To analyze the diagnostic value of the Shell technique in the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS) combined with Shear Wave Elastography (STE) for differentiating benign and malignant C-TIRADS grade 4-5 nodules.

A retrospective analysis was performed on 279 patients (with a total of 286 C-TIRADS grade 4-5 nodules) who underwent thyroid fine-needle aspiration biopsy (FNA) or surgery. Nodules were differentiated as benign or malignant using C-TIRADS classification, STE, and their combination. Taking cytopathological or postoperative pathological diagnosis as the gold standard, Receiver Operating Characteristic (ROC) curves were plotted, and the Area Under the Curve (AUC), sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated to compare the diagnostic efficacy.

Pathological results showed that among 286 nodules, 94 were benign and 192 were malignant. C-TIRADS diagnosed 122 benign and 164 malignant nodules; STE diagnosed 115 benign and 171 malignant nodules; the combination diagnosed 108 benign and 178 malignant nodules. The AUC of the combined diagnosis for C-TIRADS grade 4-5 nodules was significantly larger than that of C-TIRADS classification and STE alone (Z=5.195, P<0.001; Z=3.602, P<0.001). The sensitivity of the combined diagnosis was higher than that of C-TIRADS classification and STE alone (χ²=8.649, P=0.003; χ²=5.488, P=0.019). The accuracy of the combined diagnosis was higher than that of C-TIRADS classification and STE alone (χ²=11.457, P<0.001; χ²=9.527, P=0.002). The NPV of the combined diagnosis was higher than that of C-TIRADS classification and STE alone (χ²=6.685, P=0.010; χ²=4.997, P=0.025).

Compared with single application, C-TIRADS combined with the Shell technique in STE significantly improves the diagnostic sensitivity, accuracy, and NPV for C-TIRADS grade 4-5 thyroid nodules, demonstrating certain clinical application value.