Imaging evaluation focused on microstructural tissue changes using tensor-valued diffusion encoding in breast cancers...

Area of Science:

• Medical Imaging
• Oncology
• Biophysics

Background:

• Single diffusion encoding is limited in assessing breast tumor microenvironment complexity.
• Tensor-valued diffusion encoding (QTI) offers advanced insights into tissue microstructure.
• Evaluating microstructural changes in breast cancer after neoadjuvant chemotherapy (NAC) is crucial.

Purpose of the Study:

• To investigate the clinical utility of QTI for assessing microstructural changes in breast cancer following NAC.
• To correlate QTI parameters with histopathological prognostic factors.

Main Methods:

• Retrospective analysis of 23 invasive breast cancer patients treated with NAC.
• Breast MRI with QTI performed pre- and post-NAC.
• Estimation and comparison of QTI parameters (MK_T, MK_A, µFA, MD) with histopathological data (Ki-67, PR status).

Main Results:

• Significant decreases in MK_T, MK_A, and µFA observed post-NAC compared to pre-NAC.
• High Ki-67 expression correlated with lower pre-NAC MD and higher pre-NAC µFA.
• Negative PR status associated with lower post-NAC MK_T, MK_A, and isotropic mean kurtosis.

Conclusions:

• QTI parameters effectively reflect NAC-induced microstructural changes in breast cancer.
• QTI serves as a noninvasive imaging biomarker for breast cancer prognosis.
• QTI findings correlate with key prognostic factors, aiding treatment assessment.