Abstract

FRANCO, C.P; PARDO, F.J; LABORDA, R  and  PEREZ, C. Using Classification and Regression Trees in the ultrasound evaluation of thyroid nodules. Rev. argent. radiol. [online]. 2017, vol.81, n.1, pp.17-27. ISSN 1852-9992.  http://dx.doi.org/10.1016/j-rard.2017.01.004.

Objective: To evaluate the use of Classification and Regression Trees (CART) in the ultrasound evaluation of malignant thyroid nodules. Materials and methods: A study was performed on 404 fine needle aspirates (FNA), with biopsies being performed on 384. The information collected about the thyroid nodules was: ultrasound features (location, size, morphology, contour, consistency, echo-structure, echogenicity, calcification, and vascularisation) and elastography results. The CART technique was used to investigate the relationship between ultrasound findings and the thyroid cancer. Results: The CART analysis showed that elastography does not provide any relevant data, and that the homogeneous areas could classified the thyroid nodules into: 1^st area) characterised by the absence of colloid degeneration areas and a hypo-echogenicity associated with malignancy; 2^nd area) differentiated by the presence of colloid degeneration areas combined with absence of microcalcifications, constituting a reliable indicator of benign thyroid nodules; and a 3^rd area) the absence of hypo-echogenicity and a lesion wider than it is long that provides a reliable indicator of being benign. The optimum tree produced a sensitivity of 87.5% and negative predictive value of 98.8%. Discussion: The CART technique demonstrated a high predictive capacity for malignant nodules compared to other linear techniques. Conclusion: The use of classification trees provides us with a simple tool for clinical decision making, in order to reduce unnecessary FNA biopsies, as well as achieving a high sensitivity.

Keywords : Thyroid nodule; Ultrasound; Biopsy; Elastography.

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