ArticleBMC medical imaging2022
Quantitative DCE-MRI prediction of breast cancer recurrence following neoadjuvant chemotherapy: a preliminary study.
Article in BMC medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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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.
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Who cites it
7 citing papers in PubMed.
- Colour maps for representation of quantitative metrics in radiology: meaningful or misleading?Insights into imaging · 2026Review
- Early response evaluation of radiosurgery in intracranial meningiomas: insights from dynamic contrast‑enhanced MRI.Neuroradiology · 2026Article
- Dual-input spatio-temporal transformer model: Predicting the efficacy of NACT in breast cancer based on DCE-MRI images.iScience · 2026Article
- Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.Radiology. Artificial intelligence · 2025Article
- Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models.Diagnostics (Basel, Switzerland) · 2025Article
- Prediction of HIF-1α expression in endometrial carcinoma by enhanced TFrontiers in oncology · 2024Article
- Whole Transcriptome Analysis of Breast Cancer Tumors during Neoadjuvant Chemotherapy: Association with Hematogenous Metastasis.International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
introductionBreast cancer patients treated with neoadjuvant chemotherapy (NACT) are at risk of recurrence depending on clinicopathological characteristics. This preliminary study aimed to investigate the predictive performances of quantitative dynamic contrast-enhanced (DCE) MRI parameters, alone and in combination with clinicopathological variables, for prediction of recurrence in patients treated with NACT.
methodsForty-seven patients underwent pre- and post-NACT MRI exams including high spatiotemporal resolution DCE-MRI. The Shutter-Speed model was employed to perform pharmacokinetic analysis of the DCE-MRI data and estimate the K
resultsPre- and post-NACT DCE-MRI parameters performed better than tumor size measurement in prediction of recurrence, whether alone or in combination with clinicopathological variables. Combining post-NACT K
conclusionAccurate prediction of recurrence pre- and/or post-NACT through integration of imaging markers and clinicopathological variables may help improve clinical decision making in adjusting NACT and/or adjuvant treatment regimens to reduce the risk of recurrence and improve survival outcome.
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