Radiomics in breast MRI: Current progress toward clinical application in the era of artificial intelligence

H Satake, S Ishigaki, R Ito, S Naganawa - La radiologia medica, 2022 - Springer
Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …

Recent radiomics advancements in breast cancer: lessons and pitfalls for the next future

F Pesapane, A Rotili, GM Agazzi, F Botta, S Raimondi… - Current …, 2021 - mdpi.com
Radiomics is an emerging translational field of medicine based on the extraction of high-
dimensional data from radiological images, with the purpose to reach reliable models to be …

Longitudinal MRI-based fusion novel model predicts pathological complete response in breast cancer treated with neoadjuvant chemotherapy: a multicenter …

YH Huang, T Zhu, XL Zhang, W Li, XX Zheng… - …, 2023 - thelancet.com
Background Accurate identification of pCR to neoadjuvant chemotherapy (NAC) is essential
for determining appropriate surgery strategy and guiding resection extent in breast cancer …

Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study

J Gu, T Tong, C He, M Xu, X Yang, J Tian, T Jiang… - European …, 2022 - Springer
Objectives Breast cancer (BC) is the most common cancer in women worldwide, and
neoadjuvant chemotherapy (NAC) is considered the standard of treatment for most patients …

Factors affecting pathologic complete response following neoadjuvant chemotherapy in breast cancer: development and validation of a predictive nomogram

SY Kim, N Cho, Y Choi, SH Lee, SM Ha, ES Kim… - Radiology, 2021 - pubs.rsna.org
Background There is an increasing need to develop a more accurate prediction model for
pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast …

Artificial intelligence in multiparametric magnetic resonance imaging: A review

C Li, W Li, C Liu, H Zheng, J Cai, S Wang - Medical physics, 2022 - Wiley Online Library
Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …

Prediction of the pathological response to neoadjuvant chemotherapy in breast cancer patients with MRI-radiomics: a systematic review and meta-analysis

F Pesapane, GM Agazzi, A Rotili, F Ferrari… - Current Problems in …, 2022 - Elsevier
We performed a systematic review and a meta-analysis of studies using MRI-radiomics for
predicting the pathological complete response in breast cancer patients undergoing …

The accuracy of breast MRI radiomic methodologies in predicting pathological complete response to neoadjuvant chemotherapy: A systematic review and network …

JPM O'Donnell, SA Gasior, MG Davey… - European Journal of …, 2022 - Elsevier
Background Achieving pathological complete response (pCR) to neoadjuvant
chemotherapy (NAC) improves survival outcomes for breast cancer patients. Currently …

Prediction of tumor shrinkage pattern to neoadjuvant chemotherapy using a multiparametric MRI-based machine learning model in patients with breast cancer

Y Huang, W Chen, X Zhang, S He, N Shao… - … in Bioengineering and …, 2021 - frontiersin.org
Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more
reasonable outcome to decide a possible breast-conserving surgery (BCS) than …

Radiomics of MRI for the prediction of the pathological response to neoadjuvant chemotherapy in breast cancer patients: a single referral centre analysis

F Pesapane, A Rotili, F Botta, S Raimondi, L Bianchini… - Cancers, 2021 - mdpi.com
Simple Summary Nowadays, the only widely recognized method for evaluating the efficacy
of neoadjuvant chemotherapy is the assessment of the pathological response through …