The potential of predictive and prognostic breast MRI (P2-bMRI)

Area of Science:

• Radiology
• Oncology
• Biomarker Discovery

Background:

• Magnetic resonance imaging (MRI) is crucial for breast cancer diagnosis and management.
• It offers excellent soft tissue contrast for analyzing tumor pathophysiology.
• Emerging applications focus on predictive and prognostic capabilities.

Purpose of the Study:

• To introduce the concept and clinical applications of Predictive and Prognostic Breast MRI (P2-bMRI).
• To highlight P2-bMRI's potential in personalizing breast cancer treatment through predictive and prognostic biomarkers.
• To explore the use of semantic criteria in P2-bMRI.

Main Methods:

• Utilizing standard and advanced multiparametric MRI sequences.
• Employing structured reporting criteria like BI-RADS descriptors.
• Leveraging artificial intelligence, including machine learning (radiomics) and deep learning.

Main Results:

• P2-bMRI enables in vivo examination of the whole tumor and surrounding tissue.
• It establishes a link between pathophysiology and therapy response (prediction).
• It connects pathophysiology to patient outcomes (prognostication).

Conclusions:

• P2-bMRI holds significant clinical potential for personalized breast cancer care.
• It can optimize clinical workflow, reduce costs, and improve treatment personalization.
• The integration of AI and advanced imaging techniques enhances P2-bMRI's utility.