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Updated: Jul 20, 2026

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Microarray analysis of thyroid nodule fine-needle aspirates accurately classifies benign and malignant lesions
Carrie C Lubitz1, Stacy K Ugras, J Jacob Kazam
1Department of Surgery, Weill Cornell Medical College, Room A-983, 510 East 70th St., New York, NY 10021, USA. cclubitz@yahoo.com
Abstract:
Current preoperative diagnostic procedures for thyroid nodules rely mainly on the cytological interpretation of fine-needle aspirates (FNAs). DNA microarray analysis has been shown to reliably distinguish benign and malignant thyroid nodules in surgically resected specimens, but its diagnostic potential in thyroid FNA has not been examined. In the present study, the expression profiles of 50 benign thyroid lesions and papillary thyroid carcinoma tissue samples were compared, generating a list of 25 differentially expressed genes from this training set. A test set of 22 FNA specimens was evaluated by unsupervised hierarchical cluster analysis using this gene list, and the results were compared to FNA cytology. FNA specimens were found to fall into three clusters: malignant (n = 10), benign (n = 7), and indeterminate (n = 5). The benign and malignant groups showed complete concordance with the final histological diagnosis except for one histologically benign lesion, which was rediagnosed as follicular variant of papillary thyroid carcinoma on histological review. Paired analysis between FNA and matched tissues samples illustrated adequate sampling with FNA. These results illustrate that microarray analysis of FNA is feasible and has the potential to improve the accuracy of FNA in categorizing benign from malignant lesions beyond routine cytological evaluation.