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

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

Abstract Background This study was conducted in order to develop a model for predicting response to neoadjuvant chemotherapy (NAC) in patients with locally advanced breast cancer (LABC) using pretreatment quantitative ultrasound (QUS) radiomics. Methods This was a multicenter study involving four si...

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Bibliographic Details
Main Authors:	Daniel DiCenzo, Karina Quiaoit, Kashuf Fatima, Divya Bhardwaj, Lakshmanan Sannachi, Mehrdad Gangeh, Ali Sadeghi‐Naini, Archya Dasgupta, Michael C. Kolios, Maureen Trudeau, Sonal Gandhi, Andrea Eisen, Frances Wright, Nicole Look Hong, Arjun Sahgal, Greg Stanisz, Christine Brezden, Robert Dinniwell, William T. Tran, Wei Yang, Belinda Curpen, Gregory J. Czarnota
Format:	Article
Language:	English
Published:	Wiley 2020-08-01
Series:	Cancer Medicine
Subjects:	imaging biomarker locally advanced breast cancer machine learning neoadjuvant chemotherapy quantitative ultrasound radiomics
Online Access:	https://doi.org/10.1002/cam4.3255

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