ArticleMedical physics2008
DCEMRI of breast lesions: is kinetic analysis equally effective for both mass and nonmass-like enhancement?
Article in Medical physics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Diagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach.PloS one · 2014Trial
- Advances in breast cancer diagnosis: a comprehensive review of imaging, biosensors, and emerging wearable technologies.Frontiers in oncology · 2025Review
- A risk prediction stratification for non-mass breast lesions, combining clinical characteristics and imaging features on ultrasound, mammography, and MRI.Frontiers in oncology · 2024Article
- Correlation between dynamic contrast-enhanced MRI characteristics and apparent diffusion coefficient with Ki-67-positive expression in non-mass enhancement of breast cancer.Scientific reports · 2023Article
- Sigmoid model analysis of breast dynamic contrast-enhanced MRI: Distinguishing between benign and malignant breast masses and breast cancer subtype prediction.Journal of applied clinical medical physics · 2022Article
- Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.Journal of medical imaging (Bellingham, Wash.) · 2022Article
- Current State of Breast Cancer Diagnosis, Treatment, and Theranostics.Pharmaceutics · 2021Review
- Dynamic contrast enhanced-MRI and diffusion-weighted image as predictors of lymphovascular invasion in node-negative invasive breast cancer.World journal of surgical oncology · 2021Article
- Diffusion-weighted imaging or dynamic contrast-enhanced curve: a retrospective analysis of contrast-enhanced magnetic resonance imaging-based differential diagnoses of benign and malignant breast lesions.European radiology · 2020Article
- Discrimination of malignant and benign breast masses using automatic segmentation and features extracted from dynamic contrast-enhanced and diffusion-weighted MRI.Oncology letters · 2018Article
- Grading system to categorize breast MRI using BI-RADS 5th edition: a statistical study of non-mass enhancement descriptors in terms of probability of malignancy.Japanese journal of radiology · 2018Article
- Breast Dynamic Contrast Enhanced MRI: Fibrocystic Changes Presenting as a Non-mass Enhancement Mimicking Malignancy.Radiology and oncology · 2017Article
- Using quantitative features extracted from T2-weighted MRI to improve breast MRI computer-aided diagnosis (CAD).PloS one · 2017Article
- Evaluation of Kinetic Entropy of Breast Masses Initially Found on MRI using Whole-lesion Curve Distribution Data: Comparison with the Standard Kinetic Analysis.European radiology · 2015Observational
- Intravoxel incoherent motion diffusion-weighted MRI at 3.0 T differentiates malignant breast lesions from benign lesions and breast parenchyma.Journal of magnetic resonance imaging : JMRI · 2014Article
- Article
- The added diagnostic value of dynamic contrast-enhanced MRI at 3.0 T in nonpalpable breast lesions.PloS one · 2014Article
- Optimization of apparent diffusion coefficient measured by diffusion-weighted MRI for diagnosis of breast lesions presenting as mass and non-mass-like enhancement.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2013Article
- Classification of breast lesions pre-contrast injection using water resonance lineshape analysis.NMR in biomedicine · 2013Article
- The diverse pathology and kinetics of mass, nonmass, and focus enhancement on MR imaging of the breast.Journal of magnetic resonance imaging : JMRI · 2011Article
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7 authors.
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Abstract
To perform a pilot study investigating whether the sensitivity and specificity of kinetic parameters can be improved by considering mass and nonmass breast lesions separately. The contrast media uptake and washout kinetics in benign and malignant breast lesions were analyzed using an empirical mathematical model (EMM), and model parameters were compared in lesions with mass-like and nonmass-like enhancement characteristics. 34 benign and 78 malignant breast lesions were selected for review. Dynamic MR protocol: 1 pre and 5 postcontrast images acquired in the coronal plane using a 3D T1-weighted SPGR with 68 s timing resolution. An experienced radiologist classified the type of enhancement as mass, nonmass, or focus, according to the BI-RADS lexicon. The kinetic curve obtained from a radiologist-drawn region within the lesion was analyzed quantitatively using a three parameter EMM. Several kinetic parameters were then derived from the EMM parameters: the initial slope (Slope(ini)), curvature at the peak (kappa(peak)), time to peak (T(peak)), initial area under the curve at 30 s (iAUC30), and the signal enhancement ratio (SER). The BI-RADS classification of the lesions yielded: 70 mass lesions, 38 nonmass, 4 focus. For mass lesions, the contrast uptake rate (alpha), contrast washout rate (beta), iAUC30, SER, Slope(ini), T(peak) and kappa(peak) differed substantially between benign and malignant lesions, and after correcting for multiple tests of significance SER and T(peak) demonstrated significance (p < 0.007). For nonmass lesions, we did not find statistically significant differences in any of the parameters for benign vs. malignant lesions (p > 0.5). Kinetic parameters could distinguish benign and malignant mass lesions effectively, but were not quite as useful in discriminating benign from malignant nonmass lesions. If the results of this pilot study are validated in a larger trial, we expect that to maximize diagnostic utility, it will be better to classify lesion morphology as mass or nonmass-like enhancement prior to kinetic analysis.
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