Establishment and Comparison of Piecewise Linear Regression Models to Measure Thyroid Volume by 2D and 3D Ultrasound

Abstract

Objective: Compared thyroid volumes measured by 2-D and 3-D US with those of resected specimens and proposed new models to improve measurement accuracy. Methods: This study included 80 patients who underwent total thyroidectomy. One 2D_model and one 3D_model were developed using piecewise linear regression analysis. The accuracy of these models was compared using an ellipsoid model (2-D_US value × 0.5), 3-D_US value, and Ying’s model [1.76 + (2-D_US value × 0.38)]. Results: The new 2D_model was: V=2.66 + (0.71 * X1) - (1.51 * X2). In this model, if 2-D_US value <= 228.39, X1 = 2-D_US value and X2 = 0; otherwise, X1 = 2-D_US value and X2 = 2-D_US value - 228.39. The 3D_model was: V= 2.90 + (1.08 * X1) + (2.43 * X2). In this model, if 3-D_US value <= 102.06, X1 = 3-D_US value and X2 = 0; otherwise, X1 = 3-D_US value and X2 = 3-D_US value - 102.06. The accuracy of the new models was higher than that of the 3-D_US value, the ellipsoid model, and Ying’s model (P<0.05). Conclusion: The models established are more accurate than the traditional ones and can accurately measure thyroid volume.