Breast fine needle aspiration cytology practices and commonly perceived diagnostic significance of cytological features: A pan- India survey

印度全国范围内的调查:乳腺细针穿刺细胞学检查实践及细胞学特征的常见诊断意义

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Abstract

BACKGROUND: Methodical and meticulous understanding of clinico-pathological procedures and decision making process of cancer diagnosis and identification of aspects that are well-suited for computer-aided analysis are first steps toward development of assistive computational tool for analysis of breast fine needle aspiration cytology (FNAC) slides. AIMS: To identify variables in practice of FNAC as used for diagnosis of breast lesions and commonly perceived diagnostic significance of cytological features for diagnosis of benign or malignant condition of breast lesions. MATERIALS AND METHODS: An India-wide questionnaire-based survey of cytopathologists/pathologists' breast FNAC reporting practices and their opinion on diagnostic significance of cytological features in diagnosis of benign or malignant nature of breast lesion were conducted. RESULTS: Fifty-one experts working with various medical education institutes (~52% of participants), oncological tertiary care centers (~28%) and primary care centers/private diagnostic pathology laboratories (~20%) spread over 13 states of India have participated in the survey. Constants and variables observed in clinico-cytopathological practices and combined opinion of the participants on diagnostic significance of cytological features are presented here. CONCLUSIONS: There exist analogous as well as varied components in clinico-pathological procedures and diagnostic interpretation by individuals. These constants and variables in the practice of breast FNAC should be considered, when drawing up specifications for an assistive computational tool for analysis of breast FNAC slides. The estimate for commonly perceived significance of cytological features obtained through this study will help in their selection for computer-aided analysis of breast FNAC slides and further in selection of corresponding feature quantification techniques.

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