Related Experiment Video
Updated: Jun 24, 2026
Spontaneous Murine Model of Anaplastic Thyroid Cancer
Published on: February 3, 2023
Cytomorphologic features of poorly differentiated thyroid carcinoma: a multi-institutional analysis of 40 cases
Massimo Bongiovanni1, Leonard Bloom, Jeffrey F Krane
1Department of Pathology, University Hospital of Geneva, Geneva, Switzerland.
Background:
Poorly differentiated thyroid carcinoma (PDTC) is an uncommon and aggressive malignancy. Despite the significant clinical implications of a diagnosis of PDTC, its cytomorphologic features have not been well defined. Statistical analysis was applied to a series of 40 PDTCs to identify a specific set of cytomorphologic features that characterized these tumors on fine-needle aspiration biopsy (FNAB).
Methods:
In total, 40 thyroid FNABs that were highly diagnosed histologically as PDTC (19 insular carcinomas and 21 noninsular carcinomas) comprised the study group. A control group of 40 well differentiated thyroid neoplasms were selected for comparison. All FNABs were reviewed and scored for a series of 32 cytomorphologic features. The results were evaluated using univariate and stepwise logistic regression (SLR) analyses.
Results:
In univariate analysis, 17 cytomorphologic features were identified that characterized the 40 PDTCs: insular, solid, or trabecular cytoarchitecture (P < .001); high cellularity (P = .007); necrosis (P = .025) or background debris (P = .025); plasmacytoid appearance (P = .0007); single cells (P < .0001); high nuclear/cytoplasmic ratio (P < .0001); scant cytoplasm (P = .03); nuclear atypia (P < .0001), including nuclear pleomorphism (P = .0052) and anisokaryosis (P < .0001); granular/coarse chromatin (P = .026); naked nuclei (P = .01); mitotic activity (P = .0001) and apoptosis (P < .0001); endothelial wrapping (P = .0053); and severe crowding (P < .0001). In logistic regression analysis, severe crowding (P = .0008) and cytoarchitecture (P < .0001) were identified as the most significant cytomorphologic features of PDTCs, and the combination of cytoarchitecture, severe crowding, single cells, and high nuclear/cytoplasmic ratio was the most predictive of PDTC.
Conclusions:
PDTCs have characteristic cytomorphologic features. By using logistic regression analysis, the features that were identified as the most predictive of PDTC were severe crowding, insular/solid/trabecular morphology, single cells, and high nuclear/cytoplasmic ratio.
