MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer-Reference-Cited by-同舟云学术

MRI texture features from tumor core and margin in the prediction of response to neoadjuvant chemotherapy in patients with locally advanced breast cancer

Published:2021-07-06 Issue:14 Volume:12 Page:1354-1365
ISSN:1949-2553
Container-title:Oncotarget
language:en
Short-container-title:Oncotarget

Author:

Kolios Christopher¹²³⁴,Sannachi Lakshmanan¹²³⁴,Dasgupta Archya¹²⁴,Suraweera Harini¹²,DiCenzo Daniel¹²,Stanisz Gregory¹³,Sahgal Arjun²⁴,Wright Frances⁵⁶,Look-Hong Nicole⁵⁶,Curpen Belinda⁷⁸,Sadeghi-Naini Ali⁹,Trudeau Maureen¹⁰¹¹,Gandhi Sonal¹⁰¹¹,Kolios Michael C.¹²,Czarnota Gregory J.¹²³⁴¹²

Affiliation:

1. Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Canada

2. Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada

3. Department of Medical Biophysics, University of Toronto, Toronto, Canada

4. Department of Radiation Oncology, University of Toronto, Toronto, Canada

5. Department of Surgery, Sunnybrook Health Sciences Centre, Toronto, Canada

6. Department of Surgery, University of Toronto, Toronto, Canada

7. Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada

8. Department of Medical Imaging, University of Toronto, Toronto, Canada

9. Department of Electrical and Computer Engineering, York University, North York, Canada

10. Division of Medical Oncology, Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Canada

11. Department of Medicine, University of Toronto, Toronto, Canada

12. Department of Physics, Ryerson University, Toronto, Canada

Publisher

Impact Journals, LLC

Subject

Oncology

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1. A priori prediction of breast cancer response to neoadjuvant chemotherapy using quantitative ultrasound, texture derivative and molecular subtype;Scientific Reports;2023-12-19

2. Predicting Head and Neck Cancer Treatment Outcomes using Textural Feature Level Fusion of Quantitative Ultrasound Spectroscopic and Computed Tomography: A Machine Learning Approach;2023 IEEE International Ultrasonics Symposium (IUS);2023-09-03

3. A hierarchical self‐attention‐guided deep learning framework to predict breast cancer response to chemotherapy using pre‑treatment tumor biopsies;Medical Physics;2023-07-05

4. A Priori Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy using Quantitative Ultrasound, Texture Derivative and Molecular Subtype;2023-04-21

5. Review of Intelligent Algorithms for Breast Cancer Control: a Latin America Perspective;IEEE Latin America Transactions;2023-02