Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

Validation of Quantitative Ultrasound and Texture Derivative Analyses-Based Model for Upfront Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer

This work was conducted in order to validate a pre-treatment quantitative ultrasound (QUS) and texture derivative analyses-based prediction model proposed in our previous study to identify responders and non-responders to neoadjuvant chemotherapy in patients with breast cancer. The validation cohort...

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Bibliographic Details
Main Authors: Adrian Wai Chan, Lakshmanan Sannachi, Daniel Moore-Palhares, Archya Dasgupta, Sonal Gandhi, Rossanna Pezo, Andrea Eisen, Ellen Warner, Frances C. Wright, Nicole Look Hong, Ali Sadeghi-Naini, Mia Skarpathiotakis, Belinda Curpen, Carrie Betel, Michael C. Kolios, Maureen Trudeau, Gregory J. Czarnota
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Journal of Imaging
Subjects:
radiomics
machine learning
quantitative ultrasound
Online Access:https://www.mdpi.com/2313-433X/11/4/109
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