ArticleFrontiers in molecular biosciences2021
Radiomics of Tumor Heterogeneity in Longitudinal Dynamic Contrast-Enhanced Magnetic Resonance Imaging for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.
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Who cites it
40 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Delta radiomics: a systematic review.La Radiologia medica · 2021Pooled it
- AI- and Deep Learning-Based Radiomics: A State-of-the-Art Review.Journal of the Korean Society of Radiology · 2026Review
- Prediction of pathological complete response to neoadjuvant therapy in breast cancer integrating intratumoral and peritumoral delta radiomics with clinical features: a study based on multiparametric MRI.BMC medical imaging · 2026Article
- Joint synthesis of longitudinal MRI and enhanced prediction of neoadjuvant chemotherapy response in breast cancer: a multicohort study.BMC cancer · 2026Article
- Longitudinal MRI-based deep learning model for predicting pathological complete response in breast cancer: a multicenter, retrospective cohort study.NPJ precision oncology · 2026Article
- Development and validation of a delta ultrasomics model for predicting treatment response to neoadjuvant chemotherapy in breast cancer.Translational cancer research · 2025Article
- Predicting breast cancer response to neoadjuvant therapy by integrating radiomic and deep-learning features from early-and-peak phases of DCE-MRI.BMC cancer · 2025Article
- Classification of Molecular Subtypes of Breast Cancer Using Radiomic Features of Preoperative Ultrasound Images.Journal of imaging informatics in medicine · 2025Article
- Development and validation of an MRI spatiotemporal interaction model for early noninvasive prediction of neoadjuvant chemotherapy response in breast cancer: a multicentre study.EClinicalMedicine · 2025Article
- Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.Breast cancer research : BCR · 2025Article
- DCE-MRI radiomics of primary breast lesions combined with ipsilateral axillary lymph nodes for predicting efficacy of NAT.BMC cancer · 2025Article
- MRI-based artificial intelligence models for post-neoadjuvant surgery personalization in breast cancer: a narrative review of evidence from Western Pacific.The Lancet regional health. Western Pacific · 2025Review
- Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer.Tomography (Ann Arbor, Mich.) · 2025Article
- Prediction of tumor response to neoadjuvant chemotherapy in high-grade osteosarcoma using clustering-based analysis of magnetic resonance imaging: an exploratory study.La Radiologia medica · 2025Article
- Predicting histological grade in invasive ductal carcinoma of the breast: a radiomics-based machine learning model using DCE-MRI.Frontiers in oncology · 2025Article
- Development and Validation of Machine Learning Models in Predicting Prognosis of Breast Cancer Patients with Lymph Nodes Metastasis Following Neoadjuvant Chemotherapy.Breast cancer (Dove Medical Press) · 2025Article
- Monitoring Over Time of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Patients Through an Ensemble Vision Transformers-Based Model.Cancer medicine · 2024Article
- Review
- Integrative radiomics clustering analysis to decipher breast cancer heterogeneity and prognostic indicators through multiparametric MRI.NPJ breast cancer · 2024Article
- Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).Quantitative imaging in medicine and surgery · 2024Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast tumor morphological and vascular characteristics can be changed during neoadjuvant chemotherapy (NACT). The early changes in tumor heterogeneity can be quantitatively modeled by longitudinal dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), which is useful in predicting responses to NACT in breast cancer. In this retrospective analysis, 114 female patients with unilateral unifocal primary breast cancer who received NACT were included in a development (
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.