Sanaz Pashapoor
The University of Texas MD Anderson Cancer Center(US)
Publications by Year
Research Areas
MRI in cancer diagnosis, Radiomics and Machine Learning in Medical Imaging, Medical Imaging Techniques and Applications, Breast Cancer Treatment Studies, AI in cancer detection
Most-Cited Works
- → Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI(2023)41 cited
- → Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI(2023)23 cited
- → Multiparametric MRI–based radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer(2024)13 cited
- → Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer(2023)8 cited
- → Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer(2023)6 cited
- → Diffusion Tensor Imaging for Characterizing Changes in Triple‐Negative Breast Cancer During Neoadjuvant Systemic Therapy(2024)4 cited
- → Abstract P6-01-06: Multi-Parametric MRI-Based Radiomics Models from Tumor and Peritumoral Regions as Potential Predictors of Treatment Response to Neoadjuvant Systemic Therapy in Triple Negative Breast Cancer Patients(2023)2 cited
- → Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs(2023)2 cited
- → Deep learning models for predicting responses to neoadjuvant systemic therapy in triple-negative breast cancer using pre-treatment MRI(2024)
- → Early tumor volume reduction by breast DCE MRI predicts pathologic complete response to neoadjuvant therapy in triple negative breast cancer(2025)