Optimization of contrast-enhanced breast imaging: Analysis using a cascaded linear system model.

Area of Science:

• Medical Imaging Physics
• Radiological Sciences
• Biomedical Engineering

Background:

• Contrast-enhanced (CE) breast imaging, using agents like iodine, enhances lesion conspicuity with digital mammography (DM) or digital breast tomosynthesis (DBT).
• Optimization of CE-DM and CE-DBT requires careful consideration of physical factors like x-ray spectra and subtraction techniques for improved image quality and detectability.

Purpose of the Study:

• To develop and utilize a cascaded linear system model (CLSM) for optimizing contrast-enhanced digital breast tomosynthesis (CE-DBT) and digital mammography (CE-DM).
• To evaluate the impact of dual-energy (DE) and temporal (TE) subtraction techniques on image quality and lesion detectability in CE breast imaging.

Main Methods:

• Extended a previously developed CLSM for DBT to incorporate CE imaging, tracking image quality metrics (MTF, NPS) through the imaging chain.
• Quantified the effects of x-ray spectra and DE/TE subtraction on breast structural noise, incorporating it as a noise source within the CLSM.
• Calculated the ideal observer signal-to-noise ratio (detectability index, d') to assess optimization for detecting iodinated contrast objects.

Main Results:

• Increasing x-ray energy reduced structural noise magnitude; DE subtraction lowered structural noise but increased stochastic noise.
• TE subtraction effectively eliminated residual structural noise, albeit with higher quantum noise than DE subtraction.
• Optimal parameters for detecting a 5 mm lesion included specific kVp and spectra for low- and high-energy views; TE subtraction yielded significantly higher detectability (d') than DE subtraction.

Conclusions:

• Increasing x-ray energy and employing projection domain subtraction techniques significantly impact breast structural noise in CE imaging.
• The CLSM is effective for optimizing DE and TE subtraction CE imaging parameters (x-ray energy, subtraction weighting) for improved contrast and noise characteristics.
• TE subtraction demonstrates superior performance for lesion detection in CE breast imaging compared to DE subtraction.