dc.contributor.author | Kuppuswamy, Naaila B | |
dc.date.accessioned | 2022-12-02T10:16:44Z | |
dc.date.available | 2022-12-02T10:16:44Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://erepository.uonbi.ac.ke/handle/11295/161923 | |
dc.description.abstract | Introduction: Breast cancer ranks second after lung cancer in both sexes globally, and the commonest occurring cancer in women worldwide. Africa has been recorded as having the highest age-standardized breast cancer mortality rate globally with sub-Saharan Africa reporting the highest incidence rates. Mammography is used for both screening and diagnosis of breast malignancy worldwide with high sensitivity in fatty breasts (80-98%), but limited in depicting lesions in dense breasts (30-48% sensitivity). Combined mammography and breast ultrasound imaging have a 100% sensitivity in depicting lesions in dense breasts. Digital breast tomosynthesis (DBT) eliminates glandular tissue superposition in dense breasts allowing easier detection and characterization of breast lesions. The diagnostic performance of DBT to characterize mammographic lesions, compared to that of breast US has not been well documented.
Objective: To compare the diagnostic accuracy of Digital Breast Tomosynthesis to that of Ultrasound as adjuncts to mammography in the characterization of mammographic breast lesions at the Kenyatta National Hospital using histopathology as the gold standard.
Methodology: A cross-sectional matched pairs design was used for a 6 month study period. The study sites were The Radiology department of the Kenyatta National Hospital and the Department of Diagnostic Imaging and Radiation Medicine at The University of Nairobi. The sample size was 92. The study population was clients who sought screening and diagnostic mammography services and with lesions detected on digital mammograms. The collected data were checked for completeness and accuracy before being entered into Microsoft Excel for analysis using STATA software version 15. The diagnostic accuracy of DBT and ultrasound was determined using cross-tabulation. Fisher's exact test and Chi-square were used to compare the diagnostic performance of DBT and ultrasound.
Results: Of the 92 female participants, the majority were aged between 50-59. 82 were symptomatic with a majority (75.6%) having breast lumps. On histopathology, 73 patients had malignant lesions, the commonest malignancy being invasive ductal carcinoma in 70 women, with fibroadenoma the commonest benign lesion in 14 patients. The sensitivity and specificity of the DBT were 95.8% and 80.0% respectively, with a Positive Predictive value of 94.5% and a Negative Predictive Value of 84.2%. The diagnostic accuracy was 92.4%. For breast US, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 98.6%, 78.9%, 94.76%, 93.8%, and 94.6% respectively. The p-
xi
values comparing sensitivity and specificity for DBT and US were 0.251 and 0.854 respectively (not statistically significant).
Conclusion: The diagnostic accuracy of DBT compared to that of breast ultrasound in the characterization of breast lesions depicted on mammography was found to be similar.
Recommendations: Correlative US or DBT to be done for patients in the same sitting for inconclusive findings on mammography to save the patients cost and time. | en_US |
dc.language.iso | en | en_US |
dc.publisher | University of Nairobi | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | Key Words: Tomosynthesis, Ultrasound, Diagnostic performance, | en_US |
dc.title | A Comparison Between Digital Breast Tomosynthesis and Ultrasound in the Characterization of Mammographic Breast Lesions Using Histopathology as the Gold Standard at Kenyatta National Hospital a Cross-sectional Matched Pairs Design | en_US |
dc.type | Thesis | en_US |
dc.description.department | a
Department of Psychiatry, University of Nairobi, ; bDepartment of Mental Health, School of Medicine,
Moi University, Eldoret, Kenya | |