Acquisition of Ktrans perfusion parameter maps from DCE-MRI in breast cancer using a deep learning approach

Key Points

• Ktrans perfusion maps are synthesized from DCE-MRI using a deep learning-based approach, enabling more accurate imaging.
• The proposed method enhances the feasibility of generating Ktrans maps for breast cancer assessments, improving diagnostic capabilities.
• Dynamic contrast-enhanced magnetic resonance imaging—commonly used in cancer diagnosis—provides essential data for this analysis.
• This method may enable more precise evaluations of breast cancer, but further validation through clinical applications is needed.

Abstract