ArticleScientific reports2023
Synthetic MRI in breast cancer: differentiating benign from malignant lesions and predicting immunohistochemical expression status.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 20 citations in OpenAlex.
- The value of non-enhanced magnetic resonance imaging based on T2-weighted imaging and apparent diffusion coefficient in the study of three-tiered HER2 status in patients with breast cancer.Quantitative imaging in medicine and surgery · 2026Article
- Multiparametric magnetic resonance imaging (MRI) integrating amide proton transfer-weighted (APTw) imaging, synthetic MRI, and multiplexed sensitivity encoding diffusion-weighted imaging (MUSE DWI) in the diagnosis and grading of prostate cancer.Quantitative imaging in medicine and surgery · 2026Article
- Article
- The role of magnetic resonance imaging (MRI) in breast cancer molecular subtypes.Polish journal of radiology · 2026Review
- A novel biomarker for identifying HER2-low breast cancer using synthetic MRI.Scientific reports · 2025Article
- Rapid multiparametric quantitative MRI for predicting the activity of thyroid-associated ophthalmopathy: combination with clinical characteristics.European radiology · 2025Article
- Impact of the Magnetization Transfer Effect on T1 Measurements in Quantitative MR Imaging: Comparison of the Two-dimensional Multidynamic Multiecho (2D-MDME) and Three-dimensional Quantification Using an Interleaved Look-Locker Acquisition Sequence (3D-QALAS) Protocols on Two Systems.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Article
- Whole-tumor histogram analysis of synthetic MRI relaxation maps for nasopharyngeal carcinoma: correlations with histopathologic components.Japanese journal of radiology · 2025Article
- Differentiating triple-negative breast cancer and atypical fibroadenomas using an ultrasound-based radiomics nomogram.BMC medical imaging · 2025Article
- Deep learning reconstruction for accelerating synthetic magnetic resonance imaging of the breast: a comparative analysis of accelerated and standard protocols.Quantitative imaging in medicine and surgery · 2025Article
- Diagnostic accuracy of a machine learning model using radiomics features from breast synthetic MRI.BMC medical imaging · 2025Article
- B1 corrected T1 mapping in the differentiation and prediction of breast cancer.Scientific reports · 2025Article
- Differentiation of breast cancer subtypes and correlation with biological status using functional magnetic resonance imaging: comparison with amide proton transfer-weighted imaging and diffusion-weighted imaging.Quantitative imaging in medicine and surgery · 2025Article
- Technical aspects and clinical applications of synthetic MRI: a scoping review.Diagnosis (Berlin, Germany) · 2025Article
- FROP-1 peptide-conjugated ultrasmall superparamagnetic nanoparticles as a targeted T1-weighted MR contrast agent for breast cancer: in vitro study.BMC biomedical engineering · 2025Article
- XGBoost Enhances the Performance of SAFE: A Novel Microwave Imaging System for Early Detection of Malignant Breast Cancer.Cancers · 2025Article
- The Role of Synthetic MRI and Radiomics in Breast Cancer: A Review.Advanced biomedical research · 2025Review
- Quantitative MR Imaging of the Breast.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2025Review
- Multiparametric approach with synthetic MR imaging for diagnosing salivary gland lesions.Japanese journal of radiology · 2024Article
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9 authors at 2 institutions in 1 country.
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Abstract
To evaluate and compare the performance of synthetic magnetic resonance imaging (SyMRI) in classifying benign and malignant breast lesions and predicting the expression status of immunohistochemistry (IHC) markers. We retrospectively analysed 121 patients with breast lesions who underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and SyMRI before surgery in our hospital. DCE-MRI was used to assess the lesions, and then regions of interest (ROIs) were outlined on SyMRI (before and after enhancement), and apparent diffusion coefficient (ADC) maps to obtain quantitative values. After being grouped according to benign and malignant status, the malignant lesions were divided into high and low expression groups according to the expression status of IHC markers. Logistic regression was used to analyse the differences in independent variables between groups. The performance of the modalities in classification and prediction was evaluated by receiver operating characteristic (ROC) curves. In total, 57 of 121 lesions were benign, the other 64 were malignant, and 56 malignant lesions performed immunohistochemical staining. Quantitative values from proton density-weighted imaging prior to an injection of the contrast agent (PD-Pre) and T2-weighted imaging (T2WI) after the injection (T2-Gd), as well as its standard deviation (SD of T2-Gd), were valuable SyMRI parameters for the classification of benign and malignant breast lesions, but the performance of SyMRI (area under the curve, AUC = 0.716) was not as good as that of ADC values (AUC = 0.853). However, ADC values could not predict the expression status of breast cancer markers, for which SyMRI had excellent performance. The AUCs of androgen receptor (AR), estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), p53 and Ki-67 were 0.687, 0.890, 0.852, 0.746, 0.813 and 0.774, respectively. SyMRI had certain value in distinguishing between benign and malignant breast lesions, and ADC values were still the ideal method. However, to predict the expression status of IHC markers, SyMRI had an incomparable value compared with ADC values.
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