Breast DCE-MRI-derived pharmacokinetic metrics (e.g. K^trans, k_ep and v_e could quantitatively reflect the involved tissue’s microenvironment, such as tissue perfusion, vessel permeability, extracellular volume fraction and etc.¹. In routine clinical works, mean with tumor biggest diameter remains a commonly-used index to identify the malignancy, while various histogram metrics like kurtosis, skewness and percentiles were studied to characterize heterogeneity of within tumor parameter maps². Whether histogram metrics must be superior to mean in tumor detection is still unclear. Taken together, this study aims to compare the efficiency of mean and histogram metrics (i.e. skewness, kurtosis, median, variance, entropy and energy) of Ktrans and kep at transverse slice with tumor biggest diameter in discriminating benign lesion, grade II- and III-invasive ductal carcinomas (IDC) ( Figure 1). The Internal Review Board approved this study and all the written informed consents were obtained. Patients Patients 39 patients (15 benignancy, 14 grade II- and 10 grade III-IDCs) determined by needle biopsy or/and surgical pathology were performed by DCE-MRI. MR Protocols All the MRI examinations were performed on a 3.0T MRI scanner (GE, Signa HDXT) with a 16-channel breast coil. DCE-MRIs were acquired by VIBRANT sequence (TR/TE, 4.4ms/2.1ms; FA, 15o; slice thickness, 5mm; FOV, 350mm; matrix, 416×320). Data analysis K^trans and k_ep maps and quantitative metrics including mean and histogram-metrics (skewness, kurtosis, median, variance, entropy and energy) were calculated by commercially Omni-Kinetics2.0 and Matlab softwares, respectively. Statistical analysis All metrics were assessed by Wilcoxon rank-sum test. The area under the receiver operating characteristic curves (AUCs) of all metrics’ z-scores were further compared by non-parametric test.

In this study, a mean and 2 histogram metrics (median and variance) of K^trans, mean and all histogram metrics (skewness, kurtosis, median, entropy and energy) of k_ep showed significantly differences between benign and malignant masses (p_max=0.036) (Figure 2). With respect to IDC grading, significant differences were only found in histogram entropy and energy of kep between grade II- and III-IDC groups (entropy: median 4.38, range 3.82~4.66 v.s. median 4.54, range 4.33~4.69, p=0.0054; energy: median 0.015, range 0.011~0.03 v.s. median 0.012, range 0.01~0.016, p=0.011) (Figure 2).

In discrimination of benignancy and malignancy, the area under the ROC for mean of K^trans was 0.73, with a best 2D mean cutoff value of 0.192 that resulted in sensitivity of 79.17% and specificity of 66.67%. While the maximal area under the ROCs for histogram metrics of K^trans was 0.71 with a best cutoff value of 0.171 that resulted in sensitivity of 75.00% and specificity of 66.67% (Table 1). In terms of kep, the maximal areas under the ROCs for mean and histogram metrics were 0.83 and 0.91, respectively. Notably, two best cutoff values (i.e. entropy, 4.189; energy, 0.017) that yielded a higher sensitivity of 87.5% and specificity of 93.33% (Table 1). There were no significant differences between the areas under K^trans ROCs of mean and histogram metrics (p_min=0.576); or the k_ep’s mean and histogram metrics (p_min=0.157). While significant differences were observed between maximal AUCs of Ktrans and kep ( p=0.011).

In respect of IDC grading, the areas under kep ROCs of histogram entropy and energy were respectively 0.84 and 0.81 (entropy: sensitivity 70%, specificity 92.86%; energy, sensitivity 80%, specificity 78.57%) ( Table 1). No significant difference was also found between the areas under kep ROCs of such two metrics (p=0.210).

It is well-established that tumor largely depends on the angiogenesis to support its growth and progression³. In light of these, DCE-MRI derived K^trans, k_ep and v_e could track the changes in tumor microvasculature³. Coinciding with this fact and previous studies⁴, our results demonstrated the elevation of K^trans and k_ep in malignant lesions than that of benign lesions. Besides, in identifying malignancy from benignancy, mean and histogram metrics of K^trans and k_ep showed equivalent efficiency, whereas histogram metrics of k_ep showed statistically better efficiency than that of K^trans (p=0.011) (Table 1). Such finding may lie in two aspects, one is the used population-averaged AIF that eliminated individual variations and more reflected shape of k_ep-related contrast agent’s wash-out curve; another is that K^trans is more sensitive to variation in pre-contrast T1 values that may over-/under- estimate the K^trans values⁵. Moreover, superior to mean, histogram metrics of kep like entropy and energy showed good discriminability in tumor grading with specificity of 92.86% (Table 1). In breast DCE-MRI, both mean and histogram-metrics provide roughly comparable values in identifying malignancy from benignancy. However, histogram-metrics are considerably more informative and enable to discriminate pathological grade of IDCs. k_ep presented better diagnostic efficiency than K^trans.