Acta Scientific Agriculture

Research Article Volume 6 Issue 6

Canine Mammary Tumor Fine Needle Aspirate Cytology and Identification of Tumor Types

Komal Basra and Ratan K Choudhary*

Animal Stem Cells Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, India

*Corresponding Author: Ratan K Choudhary, Animal Stem Cells Lab, College of Animal Biotechnology, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, India.

Received: April 11, 2022 Published: May 27, 2022

Abstract

Fine needle aspiration cytology (FNAC) is a technique that can be used to diagnose canine mammary gland tumors early and easy. This technique may allow a preliminary test for diagnosing and differentiating mammary tumor types in canines. We hypothesize that cells of FNA from canine mammary tumors have tumor-specific cells, and cytomorphological investigation could distinguish between simple vs. complex and benign vs. malignant tumors. In this study, we planned to collect fine-needle aspirates from canine mammary tumors (CMT) and study morphological features of the cells present in FNA to distinguish types of tumors. Additionally, using image analysis software, a comprehensive investigation of quantitative cytomorphological data like cell shape, cell size, nucleus size, size of vacuolar cytoplasm, variable number of the nucleolus, and others will be analyzed. This technique can potentially act as a first-hand diagnostic tool for identifying mammary tumors in canines. Setting up this technique in the veterinary hospital is easy, quick, non-invasive, and cheaper. We can locate simple vs. complex tumors or benign vs. malignant tumors using FNAC without undergoing invasive mammary tissue biopsy.

Keywords: Fine Needle Aspiration; Canine; Mammary Tumor; Cytomorphology

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Citation

Citation: Komal Basra and Ratan K Choudhary. “Canine Mammary Tumor Fine Needle Aspirate Cytology and Identification of Tumor Types". Acta Scientific Agriculture Sciences 6.6 (2022): 23-28.

Copyright

Copyright: © 2022 Komal Basra and Ratan K Choudhary. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




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Acceptance rate35%
Acceptance to publication20-30 days
Impact Factor1.008

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