Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer

2024/11/06 by Casey E. Stowers, Chengyue Wu, Zhan Xu +7 · 1 voice
Biochemistry, Genetics and Molecular Biology · Medicine · #Breast Cancer Treatment Studies #MRI in cancer diagnosis #Radiomics and Machine Learning in Medical Imaging

paper · doi:10.1148/ryai.240124

openalex publication_date 2024/11/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

A convolutional neural network combined with a biology-based mathematical model showed good performance in predicting the triple-negative breast cancer response to neoadjuvant chemotherapy using only pretreatment MRI data.

Citations

• Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set
• Pembrolizumab for Early Triple-Negative Breast Cancer

Discussions

• Integrating a biology-based mathematical model with a CNN to provide spatio-temporal predictions of #BreastCancer response to treatment https://doi.org/10.1148/ryai.240124 @rsnasky.bsky.social #OncoRa [bsky, 3 points, 0 comments]

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