Hyperpolarized 13C MRI of Tumor Metabolism Demonstrates                     Early Metabolic Response to Neoadjuvant Chemotherapy in Breast                     Cancer

Metabolic Response ◽

Tumor Metabolism ◽

Hyperpolarized 13C ◽

Early Metabolic Response ◽

Early metabolic response using FDG PET/CT and molecular phenotypes of breast cancer treated with neoadjuvant chemotherapy

BMC Cancer ◽

10.1186/1471-2407-11-452 ◽

2011 ◽

Vol 11 (1) ◽

Cited By ~ 45

Author(s):

Bhumsuk Keam ◽

Seock-Ah Im ◽

Youngil Koh ◽

Sae-Won Han ◽

Do-Youn Oh ◽

...

Keyword(s):

Breast Cancer ◽

Fdg Pet ◽

Metabolic Response ◽

Pet Ct ◽

Molecular Phenotypes ◽

Fdg Pet Ct ◽

Early Metabolic Response

3 / The value of tumour infiltrating lymphocytes (TILs) for predicting response to neoadjuvant chemotherapy in breast cancer: a study in a hospital complex

10.26226/morressier.5b4709876f4cb30010951a18 ◽

2018 ◽

Author(s):

Alicia Cordoba ◽

Alicia ['Tania'] ◽

David Guerrero Setas

Keyword(s):

Breast Cancer ◽

Tumour Infiltrating Lymphocytes ◽

Infiltrating Lymphocytes ◽

64P Mammographic density to predict response to neoadjuvant chemotherapy for breast cancer

Annals of Oncology ◽

10.1016/j.annonc.2021.03.078 ◽

2021 ◽

Vol 32 ◽

pp. S49

Author(s):

S. Di Cosimo ◽

C. Depretto ◽

R. Miceli ◽

P. Baili ◽

M. Sant ◽

...

Keyword(s):

Breast Cancer ◽

Mammographic Density ◽

Tumor‐stroma ratio is associated with Miller‐Payne score and pathological response to neoadjuvant chemotherapy in HER2‐negative early breast cancer.

International Journal of Cancer ◽

10.1002/ijc.33700 ◽

2021 ◽

Author(s):

Sophie C. Hagenaars ◽

Stefanie Groot ◽

Danielle Cohen ◽

Tim J.A. Dekker ◽

Ayoub Charehbili ◽

...

Keyword(s):

Breast Cancer ◽

Early Breast Cancer ◽

Tumor Stroma ◽

Pathological Response ◽

Multicontrast MRI-based radiomics for the prediction of pathological complete response to neoadjuvant chemotherapy in patients with early triple negative breast cancer

Magnetic Resonance Materials in Physics Biology and Medicine ◽

10.1007/s10334-021-00941-0 ◽

2021 ◽

Author(s):

Angeline Nemeth ◽

Pierre Chaudet ◽

Benjamin Leporq ◽

Pierre-Etienne Heudel ◽

Fanny Barabas ◽

...

Keyword(s):

Breast Cancer ◽

Triple Negative Breast Cancer ◽

Triple Negative ◽

Pathological Complete Response ◽

Complete Response ◽

Quantitative ultrasound radiomics in predicting response to neoadjuvant chemotherapy in patients with locally advanced breast cancer: Results from multi‐institutional study

Cancer Medicine ◽

10.1002/cam4.3255 ◽

2020 ◽

Vol 9 (16) ◽

pp. 5798-5806

Author(s):

Daniel DiCenzo ◽

Karina Quiaoit ◽

Kashuf Fatima ◽

Divya Bhardwaj ◽

Lakshmanan Sannachi ◽

...

Keyword(s):

Breast Cancer ◽

Advanced Breast Cancer ◽

Quantitative Ultrasound ◽

Locally Advanced Breast Cancer ◽

Locally Advanced ◽

Advanced Breast ◽

Predictive Markers of Response to Neoadjuvant Chemotherapy in Breast Cancer: A Monocentric Study of Salah Azaiez Institute

European Journal of Surgical Oncology ◽

10.1016/j.ejso.2019.11.062 ◽

2020 ◽

Vol 46 (2) ◽

pp. e37-e38

Author(s):

Imen Zawati ◽

Sabrine Boukhris ◽

Marwa Manai ◽

Aida Goucha ◽

Ilhem Bettaieb ◽

...

Keyword(s):

Breast Cancer ◽

Predictive Markers ◽

Tumour-stroma ratio is associated with Miller-Payne grading system and pathological response to neoadjuvant chemotherapy in HER2-negative breast cancer

European Journal of Surgical Oncology ◽

10.1016/j.ejso.2020.11.194 ◽

2021 ◽

Vol 47 (2) ◽

pp. e18-e19

Author(s):

Sophie Hagenaars ◽

Stefanie de Groot ◽

Danielle Cohen ◽

Tim Dekker ◽

Marjolijn Duijm-de Carpentier ◽

...

Keyword(s):

Breast Cancer ◽

Pathological Response ◽

Grading System ◽

Tumour Stroma ◽

Prediction of pathologic complete response to neoadjuvant chemotherapy using machine learning models in patients with breast cancer

Breast Cancer Research and Treatment ◽

10.1007/s10549-021-06310-8 ◽

2021 ◽

Author(s):

Ji-Yeon Kim ◽

Eunjoo Jeon ◽

Soonhwan Kwon ◽

Hyungsik Jung ◽

Sunghoon Joo ◽

...

Keyword(s):

Breast Cancer ◽

Machine Learning ◽

Pathologic Complete Response ◽

Complete Response ◽

Learning Models ◽

Response To Neoadjuvant Chemotherapy ◽

Machine Learning Models

Estrogen receptor positive breast cancer identified by 95-gene classifier as at high risk for relapse shows better response to neoadjuvant chemotherapy

Cancer Letters ◽

10.1016/j.canlet.2012.04.017 ◽

2012 ◽

Vol 324 (1) ◽

pp. 42-47 ◽

Cited By ~ 6

Author(s):

Ryo Tsunashima ◽

Yasuto Naoi ◽

Kazuki Kishi ◽

Yosuke Baba ◽

Atsushi Shimomura ◽

...

Keyword(s):

Breast Cancer ◽

Estrogen Receptor ◽

High Risk ◽

Estrogen Receptor Positive ◽

Response To Neoadjuvant Chemotherapy ◽

Positive Breast Cancer