ArticleBreast cancer research : BCR2025
Biomechanical parameters quantified by MR elastography for predicting response to neoadjuvant chemotherapy and disease-free survival in breast cancer: a prospective longitudinal study.
Article in Breast cancer research : BCR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Magnetic Resonance Elastography in Breast Cancer: A Prospective Study on Optimal Imaging Frequency Selection and Differentiation of Molecular Subtypes.Journal of magnetic resonance imaging : JMRI · 2026Article
- Editorial for "Magnetic Resonance Elastography in Breast Cancer: A Prospective Study on Optimal Imaging Frequency Selection and Differentiation of Molecular Subtypes".Journal of magnetic resonance imaging : JMRI · 2026Article
- Beyond pCR Prediction: Subtype-Specific Artificial Intelligence for Treatment Tailoring in Breast Cancer Neoadjuvant Therapy.Cancers · 2026Review
- Correlation Between Breast Parenchymal Stiffness Measured by 3T Magnetic Resonance Elastography and CT-Derived Hounsfield Units.Medical science monitor : international medical journal of experimental and clinical research · 2026Article
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Abstract
backgroundLittle is known regarding biomechanical properties derived from multifrequency MR elastography temporal changes during neoadjuvant chemotherapy (NAC) and associated with pathologic complete response (pCR) and disease-free survival (DFS) in breast cancer. We aimed to investigate temporal changes in NAC-associated biomechanical parameters and assess biomechanical parameters as a predictor of pCR and DFS in breast cancer.
methodsIn this prospective longitudinal study, participants with breast cancer who received NAC were enrolled from February 2021 to May 2023. All participants underwent multifrequency MR-elastography at four timepoints: before NAC (T1) and after 2 (T2), 4 (T3), and 6 (T4) cycles. Tomoelastography postprocessing provided biomechanical maps of shear-wave-speed (c) and loss-angle (φ) as proxies of stiffness and viscosity. The biomechanical parameters were validated by means of correlation with histopathologic measurements. Generalized estimating equations were used to compare temporal changes in biomechanical parameters at four time points. Logistic regression was used for pCR analysis and Cox proportional hazards regression was used for survival analysis. Predictive performance was assessed with area under the receiver operating characteristic curve (AUC) analysis.
resultsA total of 235 women (50.6 ± 7.9 years) with 964 scans were enrolled. Biomechanical parameters were supported by positive correlations with pathologic examination-based stroma fraction (c: r =.76, P <.001; φ: r =.49, P =.008) and cellularity (c: r =.58, P =.001; φ: r =.40, P =.035). Progesterone receptor, human epidermal growth factor receptor-2 (HER2), T2-c, and T2-φ were independently associated with pCR (all P <.05). Estrogen receptor, HER2, clinical stage, and change in φ at the early stage of NAC were associated with PFS (all P <.05). The predictive model, which incorporated biomechanical parameters and clinicopathologic characteristics significantly outperformed the clinicopathologic model in predicting pCR (AUC: 0.95, 95% confidence interval [CI]: 0.92, 0.98 vs. 0.79, 95%CI: 0.73, 0.84; P <.001). The predictive model also showed good discrimination ability for DFS (C-index = 0.82, 95%CI: 0.72, 0.90) and stratified prognosis into low-risk and high-risk groups (log-rank, P <.001).
conclusionsDuring NAC, patients with higher tumor stiffness and viscosity are less likely to achieve DFS and pCR. The biomechanical parameters exhibit excellent biological interpretability and serve as valuable biomarkers for predicting pCR and DFS in patients with breast cancer.
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