Classification and Regression Tree (CART) model of sonographic signs in predicting thyroid nodules malignancy

Abstract

Purpose: To develop a Classification and Regression Tree (CART) model in order to recognize the most suspicious sonographic features of thyroid nodules and efficiently guide their management. Methods: 791 thyroid fine needle aspiration cytology (FNAC) performed under ultrasound guidance between January 2015 and January 2017 were reviewed. Retrieved data consisted in qualitative (patient’s gender, composition, echogenicity, shape, margins and echogenic foci of the nodule) and quantitative (patient’s age and maximal diameter of the nodule) variables as well as the Bethesda score. Results: Patients were 48.5 ± 13.7 years old with female to male ratio of 8:2. The nodules had median size of 2.3 (1.5–3.5) cm with a majority of solid (62.5 %) and isoechoic (50.8 %) features. 700 nodules (88.5 %) had a wider-than-tall shape, 600 (75.9 %) smooth margins and 113 (14.3 %) ill-defined ones. Echogenic foci were absent in 388 nodules (49.1 %) and, when present, largely dominated by punctate foci (32.5 %). Bethesda classes 3, 4 and 5, which require surgery, represented only 10.6 % of cases. They were significantly correlated with the taller-than-wide shape and with solid or predominantly solid features. There was no significant correlation between echostructure and Bethesda scores but we did find more nodules classified Bethesda 4 and 5 in the categories hypoechoic and severely hypoechoic. In the CART model we developed, the sequence leading to most nodules classified Bethesda 4 and 5 is: taller-than-wide shape, solid composition and hypoechoic or severely hypoechoic feature. Conclusions: Taller-than-wide, solid or predominantly solid, hypoechoic or severely hypoechoic nodules are likely to require surgery and might benefit from FNAC. Keywords: Thyroid nodule, Thyroid neoplasms, Biopsy, Fine-needle, Ultrasonography