ArticleFrontiers in oncology2023
Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03501394 (What Are the Factors Affecting Neoadjuvant Chemotherapy Efficacy in Breast Cancer? A Non-invasive in Vivo Study Using Specialist Magnetic Resonance), which is not on this map. Cited by 4 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
What Are the Factors Affecting Neoadjuvant Chemotherapy Efficacy in Breast Cancer? A Non-invasive in Vivo Study Using Specialist Magnetic Resonance (MR) Methods
Who cites it
4 citing papers in PubMed.
- Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025Review
- Radiomics-based Machine Learning Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Using Physiologically Decomposed Diffusion-weighted MRI.Radiology. Imaging cancer · 2025Article
- Understanding cellular proliferation activity in breast cancer using multi-compartment model of transverse relaxation time mapping on 3T MRI.Frontiers in oncology · 2025Article
- Peri-Tumoural Lipid Composition and Hypoxia for Early Immune Response to Neoadjuvant Chemotherapy in Breast Cancer.International journal of molecular sciences · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Introduction: The early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response. Materials and methods: Seventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy. Results: The perfusion fraction showed a significant difference ( Conclusion: The alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT. Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394.
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