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Image Analysis-Assisted Nuclear Morphometric Study of Benign and Malignant Breast Aspirates
Dayal Johan Niranjan Pandian1, Anita Ramdas1, M Moses Ambroise1
1Department of Pathology, Pondicherry Institute of Medical Sciences, Kalapet, Puducherry, India.
Journal of Microscopy and Ultrastructure
|November 3, 2021
Summary
Nuclear morphometry using Image J software aids in distinguishing benign from malignant breast aspirates. Key nuclear size and density parameters effectively differentiate between these conditions, improving diagnostic accuracy.
Area of Science:
- Cytopathology
- Oncology
- Medical Imaging Analysis
Background:
- Fine-needle aspiration cytology (FNAC) of the breast is a widely used diagnostic tool.
- While accurate, FNAC interpretation can be subjective, necessitating objective assessment methods.
Purpose of the Study:
- To evaluate the utility of nuclear morphometry in differentiating benign and malignant breast aspirates.
- To assess the effectiveness of nuclear density parameters analyzed with Image J software.
Main Methods:
- Nuclear morphometry was performed on 20 benign and 20 malignant breast aspirates using Image J software.
- Six parameters were measured: nuclear area, diameter, perimeter, axis ratio, integrated density, and raw integrated density.
- Analysis included 1000 cells per case, with 50 intact nuclei assessed per case.
Main Results:
- Significant differences were observed in nuclear area, perimeter, diameter, and density between benign and malignant lesions.
- The axis ratio showed no significant difference between the groups.
- Receiver operating characteristic curve analysis confirmed the discriminatory power of size and density parameters.
Conclusions:
- Image J software is a valuable tool for evaluating nuclear size and chromasia in breast cytology.
- Nuclear size and density parameters can establish cutoff values to differentiate benign and malignant breast cells.
