1. International Academy of Cytology standardized reporting of breast fine-needle aspiration cytology with cyto-histopathological correlation of breast carcinoma
- Author
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Shweta Pai
- Subjects
international academy of cytology ,robinson’s grading ,scarff-bloom-richardson grading ,breast neoplasms ,fine-needle aspirations ,Pathology ,RB1-214 - Abstract
Background The International Academy of Cytology (IAC) has developed a standardized approach for reporting the findings of breast fine-needle aspiration cytology (FNAC). Accordingly, there are five chief categories of breast lesions, C1 (insufficient material), C2 (benign), C3 (atypical), C4 (suspicious), and C5 (malignant). The prognostication and management of breast carcinoma can be performed readily on the basis of this classification system. The aim of this study was to classify various breast lesions into one of the above-named categories and to further grade the C5 lesions specifically using the Robinson system. The latter grades were then correlated with modified Scarff-Bloom-Richardson (SBR) grades. Methods This retrospective study was undertaken in the pathology department of a hospital located in the urban part of the city of Bangalore. All FNAC procedures performed on breast lumps spanning the year 2020 were included in the study. Results A total of 205 breast lesions was classified according to the IAC guidelines into C1 (6 cases, 2.9%), C2 (151 cases, 73.7%), C3 (13 cases, 6.3%), C4 (5 cases, 2.5%), and C5 (30 cases, 14.6%) groups. The C5 cases were further graded using Robinson’s system. The latter showed a significant correlation with the SBR system (concordance=83.3%, Spearman correlation=0.746, Kendall’s tau-b=0.736, kappa=0.661, standard error=0.095, p≤.001). Conclusions A standardized approach for FNAC reporting of breast lesions, as advocated for by the IAC, improves the quality and clarity of the reports and assures diagnostic reproducibility on a global scale. Further, the cytological grading of C5 lesions provides reliable cyto-prognostic scores that can help assess a tumor’s aggressiveness and predict its histological grade.
- Published
- 2024
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