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Evaluation of Mammary Gland Calcification in Dogs; Radiography and Computed Tomography

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  • معلومة اضافية
    • بيانات النشر:
      The Korean Society of Animal Reproduction and Biotechnology, 2017.
    • الموضوع:
      2017
    • Collection:
      LCC:Biotechnology
      LCC:Medicine (General)
      LCC:Internal medicine
    • نبذة مختصرة :
      The mammary gland tumor (MGT) is the most common neoplasia in intact female dogs. Of these, 50% are malignant and metastasis to the other sites are often occurred. Therefore, it is very important for decision of treatment plan and prognosis to differentiate benign tumor from malignancies. Calcification of MGT is a very important imaging finding. The purpose of this study was to investigate the radiological and computed tomographic images of the MGT and the morphology and distribution of calcifications in the MGT using the Breast Imaging Reporting and Data System classification. A total of 42 dogs with MGT were included in this study. The dogs were divided into two groups into benign and malignant groups based upon histologic or cytologic results. The appearance of calcification in the tumor on radiographs and CT images was analyzed for the HU value of pre- and post-contrast injection, margin, surface, and shape of the tumor and the lymph node abnormalities. On radiographs, the positive predictive value of malignant and benign tumors was 72.72 and 85.71%, respectively. On CT examinations, the positive predictive value of malignant and benign tumors was the same value of 83.33%. The maximum diameter of the tumor and the presence of abnormal lymph nodes on CT images showed a strong correlation with malignancies. Therefore, it is thought that radiographs and CT provide useful information for evaluating MGT in dogs.
    • File Description:
      electronic resource
    • ISSN:
      2671-4639
      2671-4663
    • Relation:
      http://www.e-jarb.org/journal/view.html?uid=397&vmd=Full; https://doaj.org/toc/2671-4639; https://doaj.org/toc/2671-4663
    • الرقم المعرف:
      10.12750/JET.2017.32.3.183
    • الرقم المعرف:
      edsdoj.7f6979ddbf354844ac3720fefda2c345