The Role of Computer-aided Detection and Diagnosis System in the Differential Diagnosis of Thyroid Lesions in Ultrasonography

Abstract

To avoid abuse of fine-needle aspiration cytology (FNAC) and to save the time of a learning curve, a computer-aided detection and diagnosis (CAD) system to detect suspicious lesions for FNAC from thyroid ultrasonography has been developed by the Department of Industrial Engineering, cooperative with the Department of Surgery at the National Taiwan University, Taipei, Taiwan. The purposes of this article are to introduce how to utilize the CAD system in thyroid ultrasonography, and to outline the real role of the CAD system. After marking the apparently transverse (extending across) axis and longitudinal axis of the nodule appearing by ultrasonography, four parameters are calculated and displayed by the computer system automatically, which include microcalcifications, hypoechoic lesion, heterogeneity, and indistinct margin. The results are displayed by the pointers in the semilunar figures. The necessity of FNAC is dependent on the size and numbers of positive findings (pointers displayed in the right side). This CAD system is objective and easy to use. It may supply an easy method to determine the necessity for FNAC, but what we must keep in mind is that this method can reduce the necessity of FNAC, not replace FNAC for the diagnosis of thyroid cancer.

Keywords

• computer-aided detection and diagnosis system
• fine-needle aspiration cytology
• thyroid cancer
• thyroid nodule
• thyroid ultrasonography