ArticleQuantitative imaging in medicine and surgery2023
Nomogram based on quantitative dynamic contrast-enhanced magnetic resonance imaging, apparent diffusion coefficient, and clinicopathological features for early prediction of pathologic complete response in breast cancer patients receiving neoadjuvant chemotherapy.
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Diagnostic Accuracy of Post-Treatment ADC and MRI Response Assessment for Predicting Pathological Complete Response in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy.Journal of clinical medicine · 2026Article
- Hemodynamic Inflow-Outflow Profiling as an Integrated DCE-MRI Biomarker for Diagnosis and Risk Stratification in Breast Cancer: A Multicenter Retrospective Study.Breast cancer (Dove Medical Press) · 2026Article
- Percentage apparent diffusion coefficient change for early prediction of response to neoadjuvant chemotherapy in breast cancer: a systematic review and meta-analysis, and a retrospective study.Quantitative imaging in medicine and surgery · 2025Article
- Article
- Defining the optimal Ki67 cutoff values for survival prediction in neoadjuvant chemotherapy-treated patients with breast cancer.Frontiers in surgery · 2025Article
- Model based on ultrasound and clinicopathological characteristics for early prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer.Quantitative imaging in medicine and surgery · 2024Article
- Ki-67 With MRI in Predicting the Complete Pathological Response Post-neoadjuvant Chemotherapy.Cureus · 2024Review
- Tumor enhancement and shrinkage pattern in dynamic contrast-enhanced magnetic resonance imaging for predicting pathologic complete response after human epidermal growth factor receptor 2 (HER2)-targeted therapy in breast cancer.Quantitative imaging in medicine and surgery · 2024Article
- Article
- Value of mammographic microcalcifications and MRI-enhanced lesions in the evaluation of residual disease after neoadjuvant therapy for breast cancer.Quantitative imaging in medicine and surgery · 2023Article
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Abstract
Background: The aim of this study was to develop two nomograms for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) for breast cancer based on quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), and clinicopathological characteristics at two time-points: before and after two cycles of NACT, respectively. Methods: 3.0 T MRI scans were performed before and after 2 cycles of NACT in 215 patients. A total of 74 female patients with stage II-III breast cancer were included. According to univariate and multivariate logistic regression analysis, nomogram model 1 and nomogram model 2 were developed based on the independent predictors for pCR before and after 2 cycles of NACT, respectively. Nomogram performance was assessed with the area under the receiver operating characteristic curve (AUC) and calibration slope. Results: The independent predictors of pCR were different at the two time points. Both nomograms were found to effectively predict pCR: nomogram model 2 based on Ki67, ΔK Conclusions: Nomograms based on quantitative DCE-MRI parameters, ADC, and clinicopathological characteristics can predict pCR in breast cancer and facilitate individualized decision-making for NACT.
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