ArticleLa Radiologia medica2018
Role of DCE-MR in predicting breast cancer subtypes.
Article in La Radiologia medica, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- The association of magnetic resonance imaging features with five molecular subtypes of breast cancer.European journal of radiology open · 2024Article
- Diffusion-time dependent diffusion MRI: effect of diffusion-time on microstructural mapping and prediction of prognostic features in breast cancer.European radiology · 2023Article
- The value, diagnostic efficacy and clinical significance of functional magnetic resonance imaging in evaluating the efficacy of neoadjuvant chemotherapy in patients with triple negative breast cancer.Frontiers in oncology · 2023Article
- Breast Cancer Subtypes and Quantitative Magnetic Resonance Imaging: A Systemic Review.Life (Basel, Switzerland) · 2022Review
- Quantitative Parameters of Diffusion Spectrum Imaging: HER2 Status Prediction in Patients With Breast Cancer.Frontiers in oncology · 2022Article
- Apparent diffusion coefficient magnetic resonance imaging (ADC-MRI) in the axillary breast cancer lymph node metastasis detection: a narrative review.Gland surgery · 2020Review
- Development of a risk-stratification scoring system for predicting lymphovascular invasion in breast cancer.BMC cancer · 2020Article
- Preoperative loco-regional staging of invasive lobular carcinoma with contrast-enhanced digital mammography (CEDM).La Radiologia medica · 2019Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of this retrospective study is to find a correlation between dynamic contrast-enhanced MR features with histological, immunohistochemical and loco-regional characteristics of breast cancer. MATERIALS AND
methodsA total of 149 patients with histopathologically confirmed invasive breast carcinoma underwent MR imaging. Histological analysis included: histological features (histological type, necrosis, vascular invasion and Mib-1), immunohistochemical characterization (immunophenotype, receptor status, HER2-neu and grading) and loco-regional characteristics (T and N). The kinetic MR features analyzed were: curve type, maximum enhancement, time to peak, wash-in and wash-out rate, brevity of enhancement and area under curve.
resultsMRI kinetic parameters and immunohistological features were compared using chi square test, two-tailed student t test and Anova test, with p = 0.05 level of significance. Vascular invasion was shown to be significantly related to time to peak (p = 0.02). The immunohistotype was shown to be significantly related with maximum enhancement (p = 0.05), time to peak (p = 0.04) and wash-in rate (p = 0.01). ER status correlates with maximum and relative enhancement (p = 0.004 and p = 0.028), wash-in rate (p = 0.0018) and area under curve (p = 0.006). PR status was significantly related to time to peak (p = 0.048) and wash-in rate (p = 0.05).
conclusionMaximum enhancement absolute and relative, time to peak, wash-in rate and area under the curve significantly correlate with several prognostic factors, like ER status, immune profile and tumoral vascular invasion, and may predict the aggressiveness of the tumor.
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