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.
Highlights
This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions
Pharmacokinetic parameters based on the Tofts model [3] derived from Dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) have shown to have a good correlation with tumor angiogenesis [4, 5], and among these parameters, the volume transfer constant (Ktrans) has potential for differentiating of breast lesions
With the two state of the art acquisition sequences, CAIPIRINHA-DixonTWIST (CDT)-volumetric interpolated breath-hold examination (VIBE) DCE and readout-segmented diffusion-weighted (RS-Diffusion-weighted imaging (DWI)) MRI, we proposed a dual parametric 2D histogram to combine Ktrans and apparent diffusion coefficient (ADC) in this study and hypothesized that this histogram would perform better than single parametric histogram for differentiating breast lesions
Summary
This study aimed to investigate the diagnostic value of a dual-parametric 2D histogram classification method for breast lesions. Pharmacokinetic parameters based on the Tofts model [3] derived from DCE MRI have shown to have a good correlation with tumor angiogenesis [4, 5], and among these parameters, the volume transfer constant (Ktrans) has potential for differentiating of breast lesions. One particular issue with DCE MRI of previous studies is a lack of simultaneously high temporal and high spatial resolution DCE sequences due to technological limitations [4, 7,8,9]. High temporal resolution can be achieved while spatial resolution is preserved with controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA)-Dixon-time-resolved angiography with stochastic trajectories (TWIST)-volumetric interpolated breath-hold examination (VIBE) DCE and this sequence has demonstrated promising results [11, 12]
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