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Optimization of Image Quality and Dose in Digital Mammography
Agnes M F Fausto1, M C Lopes2,3, M C de Sousa2
1Departamento de Ciências Exatas e Tecnológicas-DCET/CPqCTR, Universidade Estadual de Santa Cruz, Ilhéus, Bahia, Brazil, CEP 45662-900. amffausto@uesc.br.
Journal of Digital Imaging
|November 30, 2016
Summary
Optimizing digital mammography exposure parameters is crucial for early breast cancer detection. This study introduces a new Figure of Merit (FOM) to balance image quality and radiation dose, improving diagnostic accuracy, especially for smaller breasts.
Area of Science:
- Radiology
- Medical Imaging
- Diagnostic Radiology
Background:
- Digital mammography optimization is a key challenge in diagnostic radiology.
- Detecting micro-calcifications and differentiating tissues with similar densities is difficult due to close linear attenuation coefficients.
- Digital technology introduces new factors impacting image quality and diagnostic accuracy.
Purpose of the Study:
- To develop an optimized methodology for digital mammography exposure parameters.
- To introduce a novel Figure of Merit (FOM) balancing image quality and average glandular dose (AGD).
- To compare optimized parameters against the mammography unit's automatic exposure system.
Main Methods:
- Utilized a Senographe DS/GE digital mammography system.
- Employed CDMAM and TORMAM phantoms for objective assessment.
- Characterized clinical practice by varying breast thickness, exposure parameters, and image processing options.
- Evaluated a new FOM: (Inverse Image Quality Factor) squared divided by Average Glandular Dose.
Main Results:
- Optimized parameters differed from the automatic system's settings, particularly for small breast sizes.
- The proposed optimized parameters yielded superior image quality compared to the automatic system.
- Enhanced detection of breast structures was observed with optimized parameters when analyzed by radiologists.
Conclusions:
- The developed methodology offers improved digital mammography optimization.
- Optimized exposure parameters enhance diagnostic accuracy by improving image quality and detectability.
- This approach is particularly beneficial for optimizing mammograms of smaller breasts.
