• African health sciences · Dec 2017

    Mammographic classification of breast lesions amongst women in Enugu, South East Nigeria.

    • Uchechukwu I Nwadike, Charles U Eze, Kelvin Agwuna, and Chibuzo Mouka.
    • Department of Medical Radiography and Radiological Sciences, Faculty of Health Sciences and Technology, College of Medicine, University of Nigeria Enugu Campus, Nigeria.
    • Afr Health Sci. 2017 Dec 1; 17 (4): 1044-1050.

    ObjectivesThe study was to classify lesions identified on mammograms using Breast Imaging Reporting and Data System (BIRADS) grading method. This was in view of ascertaining the rate of occurrence of breast malignancy of the studied population.MethodsA retrospective cohort study of 416 mammographic reports of women was undertaken. The reports were written by consultant radiologists of 10 years' experience and above. The reports were evaluated and characterised using Breast Imaging Reporting and Data system (BIRADS). Demographic data of patients were sourced from the request cards. The data was entered into a proforma and analysed using SPSS version 17. All request cards with incomplete data were excluded from the study.ResultsUsing the BI-RADS Classification, the mammographic reports shows that 29.57% of the lesions were benign, and 4.57% were suspicious and biopsy recommended, while 3.60% were highly suggestive of malignancy. The right breast was predominantly affected with 42.7% of the patients (P<0.05).ConclusionClassification of breast lesion using BI-RADS grading system is a veritable tool in the diagnosis of the breast lesion. The present study shows that 3.6% of the population has a high index of malignancy.

      Pubmed     Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.