OBJECTIVE. Neoadjuvant chemotherapy is becoming the standard of care for patients with
locally advanced breast cancer. Conventional imaging modalities used for the assessment …

Purpose The aim of this meta-analysis was to determine the diagnostic accuracy of machine
learning (ML) models with MRI in predicting pathological response to neoadjuvant …

Objectives To investigate machine learning approaches for radiomics-based prediction of
prognostic biomarkers and molecular subtypes of breast cancer using quantification of tumor …

Background Previous studies have suggested that texture analysis is a promising tool in the
diagnosis, characterization, and assessment of treatment response in various cancer types …

Purpose To predict pathological response of breast cancer to neoadjuvant chemotherapy
(NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement …

Background For breast cancer patients undergoing neoadjuvant chemotherapy (NAC),
pathologic complete response (pCR; no invasive or in situ) cannot be assessed non …

Background Ultrafast dynamic contrast-enhanced (DCE) MRI parameters are associated
with breast cancer aggressiveness. However, the role of these parameters as predictive …

Abstract Nowadays, Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI)
has demonstrated to be a valid complementary diagnostic tool for early detection and …

Neoadjuvant chemotherapy (NAC) involves administration of chemotherapeutic agents to
patients with newly diagnosed breast cancer prior to definitive surgical treatment …

Breast tumor morphological and vascular characteristics can be changed during
neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be …