| Literature DB >> 28639242 |
Anna Cipolletta Campanile1, Maria Gabriella Malzone2, Nunzia Simona Losito1, Gerardo Botti1, Maria Grazia Chiofalo3, Antongiulio Faggiano3, Roberta Siciliano4, Annamaria Colao5, Luciano Pezzullo3, Franco Fulciniti6.
Abstract
Fine needle cytology (FNC) is a crucial procedure in the preoperative diagnosis of thyroid tumors. Papillary thyroid carcinoma (PTC), in its classic variant (cPTC), is the most common malignant neoplasm of the thyroid. Several histological variants of PTC have been described, each one with its own characteristics and prognosis. The ability of FNC to identify the variants represents a challenge even for a skilled pathologist. The aim of this study was to evaluate the diagnostic cytological accuracy of FNC in PTC and to look for specific features that could predict the different variants. This was a single center prospective study on 128 patients who received a diagnosis of PTC on FNC. The smears were blindly reviewed by two cytopathologists to create a frequency score (0, 1, 2, 3) of the features for each variant. The cytological parameters were divided into three groups: architectural, nucleo-cytoplasmic, and background features. Univariate analysis was performed by chi-square test with Yates correction and Fisher exact test as appropriate. Multiple regression analysis was performed among the variables correlated at the linear correlation. The correlation study between cytology and histology showed an accuracy of FNC in classic, follicular, and oncocytic PTC variants of 63.5, 87.5, and 87% respectively. Familiarity with cytological features may allow an early diagnosis of a given PTC variant on FNC samples. This is fundamental in a preoperative evaluation for the best surgical approach and subsequent treatment.Entities:
Keywords: Cytohistological correlation; Cytological variants; Fine needle cytology; Papillary thyroid carcinoma
Mesh:
Year: 2017 PMID: 28639242 DOI: 10.1007/s12022-017-9488-1
Source DB: PubMed Journal: Endocr Pathol ISSN: 1046-3976 Impact factor: 3.943