Coexistence of Hyalinizing Trabecular Tumor and Papillary Thyroid Carcinoma: A Diagnostic Challenge

Hyalinizing trabecular tumor (HTT) of the thyroid is an uncommon follicular cell-derived neoplasm. Histologically, it shares several nuclear features with papillary thyroid carcinoma (PTC), such as nuclear grooves and pseudoinclusions, making accurate diagnosis challenging, particularly in cytology. Coexistence of HTT and PTC within the same thyroid gland is exceptionally rare and can further complicate clinical interpretation.

A 54-year-old woman presented with a gradually enlarging anterior neck swelling. Ultrasound revealed 2 nodules in the right thyroid lobe with differing echogenic features. Fine-needle aspiration cytology was reported as Bethesda Category III (Atypia of Undetermined Significance). A right lobectomy was performed for definitive diagnosis. Histopathology revealed 2 distinct lesions: a 1.2 cm hyalinizing trabecular tumor showing trabecular architecture, hyalinized stroma, CD56 positivity, and characteristic membranous Ki-67 staining; and an incidental 0.1 cm papillary thyroid carcinoma exhibiting fibrovascular cores with nuclear clearing and grooves, CK19 positivity, and CD56 loss. No capsular, vascular, or extrathyroidal invasion was identified. The patient recovered uneventfully and remains disease-free after 2.5 years of follow-up.

The coexistence of HTT and PTC within the same thyroid gland is a rare but documented phenomenon, reported in only a few cases worldwide. The morphologic overlap between HTT and PTC frequently leads to diagnostic uncertainty in cytology. Immunohistochemistry and, when available, molecular testing for GLIS1/GLIS3 rearrangements provide essential diagnostic clarity.

This case underscores the importance of integrating cytologic, histopathologic, and molecular features when evaluating thyroid nodules with overlapping characteristics. Recognition of this rare coexistence prevents misclassification and unnecessary aggressive management, ensuring accurate diagnosis and optimal patient outcomes.