ArticleJournal of translational medicine2018
Feasibility study of dual parametric 2D histogram analysis of breast lesions with dynamic contrast-enhanced and diffusion-weighted MRI.
Article in Journal of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Diagnostic performance of breast tumor tissue selection in diffusion weighted imaging: A systematic review and meta-analysis.PloS one · 2020Pooled it
- Can apparent diffusion coefficient (ADC) distinguish breast cancer from benign breast findings? A meta-analysis based on 13 847 lesions.BMC cancer · 2019Pooled it
- Benign and Malignant Breast Lesions: Differentiation Using Microstructural Metrics Derived from Time-Dependent Diffusion MRI.Radiology. Imaging cancer · 2025Trial
- Article
- DWI in the Differentiation of Malignant and Benign Breast Lesions Presenting with Non-Mass Enhancement on CE-MRI.Cancers · 2024Article
- The value of multimodality MR in T staging evaluation after neoadjuvant therapy for rectal cancer.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundThis study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions.
methodsThis study included 116 patients with 72 malignant and 44 benign breast lesions who underwent CAIPIRINHA-Dixon-TWIST-VIBE dynamic contrast-enhanced (CDT-VIBE DCE) and readout-segmented diffusion-weighted magnetic resonance examination. The volume of interest (VOI), which encompassed the entire lesion, was segmented from the last phase of DCE images. For each VOI, a 1D histogram analysis (mean, median, 10th percentile, 90th percentile, kurtosis and skewness) was performed on apparent diffusion coefficient (ADC) and volume transfer constant (Ktrans) maps; a 2D histogram image (Ktrans-ADC) was generated from the pixelwise aligned maps, and its kurtosis and skewness were calculated. Each parameter was correlated with pathological results using the Mann-Whitney test and receiver operating characteristic curve analysis.
resultsFor the Ktrans histogram, the area under the curve (AUC) of the mean, median, 90th percentile and kurtosis had statistically diagnostic values (mean: 0.760; median: 0.661; 90th percentile: 0.781; and kurtosis: 0.620). For the ADC histogram, the AUC of the mean, median, 10th percentile, skewness and kurtosis had statistically diagnostic values (mean: 0.661; median: 0.677; 10th percentile: 0.656; skewness: 0.664; and kurtosis: 0.620). For the 2D Ktrans-ADC histogram, the skewness and kurtosis had statistically higher diagnostic values (skewness: 0.831, kurtosis: 0.828) than those of the 1D histogram (all P < 0.05).
conclusionsThe dual-parametric 2D histogram analysis revealed better diagnostic accuracy for breast lesions than single parametric histogram analysis of either Ktrans or ADC maps.
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