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American Journal of PharmTech Research

Published

Quality Control in Mammography; An Assessment of System's Performance of 3D Breast Tomosynthesis

Published in August 2023 Issue 4 (Vol. 13, Issue 4, 2023)

Quality Control in Mammography; An Assessment of System's Performance of 3D Breast Tomosynthesis - Issue cover

Abstract

Breast tomosynthesis has become a well-established imaging technique for clinical assessment of breast cancer. This Tree-Dimensions (3D) imaging technique is one of a major recently used method for early breast cancer detection particularly for women with a dense breast. It can also aid in the clarifying of a breast cancer diagnosis, whether by initial screening or following up after a suspicious area in the breast has been found. The image of such technique must have an optimal contrast to display mass densities and speculated fibrous structures, in order to diagnose breast cancer accurately at the earliest feasible stage. Furthermore, the spatial resolution must be sufficient to reveal the size and form of micro calcifications. To improve the accuracy of imaging diagnosis system, an effective Quality Control (QC) program can be implemented to optimize the accurate diagnosis of mammographic imaging. The main aim of this study is to evaluate the QC of 3D Tomosynthesis system, including Kilo voltages peak (kVp) accuracy, mAs linearity, Half Value Layer (HVL), Automatic Exposure Control (AEC), radiation output and mean glandular dose (MGD). Image quality assessment also included to check of spatial resolution, Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR). Accreditation phantoms have been used during the study. This study reveals that international standard guidelines which contain basic requirements for QC are obtained.

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Article Information

Article ID:
AJPTR134001
Paper ID:
AJPTR-01-002205
Published Date:
2023-08-01

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How to Cite

A., M., & M., R. (2023). Quality Control in Mammography; An Assessment of System's Performance of 3D Breast Tomosynthesis. American Journal of PharmTech Research, 13(4), xx-xx. DOI:https://doi.org/10.5281/zenodo.8260371

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