Yiqi Hu1, Tao Ai1, and Liming Xia1
1Tongji Hospital, department of radiology, Wuhan, China, People's Republic of
Synopsis
The overlap of pharmacokinetic parameters values exists between benign and malignant lesions. Most previous studies chose mean pharmacokinetic parameters when elevating the state of breast lesions perfusion. However, tumors are heterogeneous that are marked by microenvironmental factors and thus manifests as radiologic heterogeneity. The mean pharmacokinetic parameter values may overlook the subtle but important difference between breast lesions. Thus, the aim of our study is to investigate the feasibility of histogram analysis of pharmacokinetic parameters including Ktrans, kep, ve in breast DCE-MRI imaging and determine which metric of each pharmacokinetic parameter may best help differentiate benign from malignant lesions.Purpose
To investigate the feasibility of histogram analysis
of pharmacokinetic parameters in breast T1-weighted dynamic contrast-enhanced
MR imaging (DCE-MRI) for differentiating the malignant from benign breast
lesions.
Method
92 patients with 97 breast lesions (26 benign and 71
malignant) were enrolled in this retrospective study with their informed
consent. Patients underwent dynamic breast imaging at 3T MR (Siemens,
Healthcare) with a prototype CAIPIRINHA-Dixon-Twist-Vibe (CDT-VIBE) technique
and subsequently confirmed by histopathologic results. The imaging protocol
included 1 min 05 s for T1 mapping (FA = 2 and 14 degree, respectively) and 6
min 58 s for DCE MR imaging (35 phases X 11s). The detailed imaging parameters
included TR = 5.4ms, TE = 2.46/3.69ms, FA = 9 degree, FOV = 320 mm, matrix = 320
X 320,slice
thickness = 1.5mm. In addition, a contrast medium (Omniscan, GE Healthcare) was
administrated at the beginning of the fourth phase of the DCE sequence, via a
power injector (0.1 mmol/kg body-weight). Ktrans
(volume transfer constant between plasma and EES), kep (constant flux rate between EES and plasma) and ve (EES volume per unit volume of tissue)
were then calculated using the functional tissue 4D software
(Fig.1). The cumulative histogram
parameters of pharmacokinetic parameters including mean value, 25th/50th/75th/90th
percentiles, skewness and kurtosis were extracted. Single-sample K-S test,
paired t-test with Bonferroni correction and receiver operating characteristic
curve (ROC) analysis were used for statistical analysis.
Results
and discussion
Malignant breast lesions had significantly higher Ktrans, kep and lower ve in mean value, and 25th/50th/75th/90
th percentiles with higher skewness of ve
than those of benign lesions (all
P <
0.05;
Table 1). These results
demonstrated that most histogram parameters can differentiate malignant from
benign breast lesions. For diagnostic accuracy, the results of ROC analysis were
shown in
Table 2. These results demonstrated
that the 90th percentile of Ktrans and
kep, and the 50th percentile of ve had the greatest area under receiver
operating characteristic curve (AUC) than the other histogram-derived values.
It indicates that the 90th percentile of pharmacokinetic parameters of Ktrans and kep has better diagnostic performance for the differentiation of
the breast lesions; and may be more closely related to the angiogenesis and
aggression of the breast carcinoma. In addition, the 90th percentile of kep achieved the highest AUC value
(0.927) among the all histogram-derived values. However, the results showed no
significant differences in skewness values of Ktrans and kep between
the malignant and benign breast lesions (all
P > 0.05). And there were no significant differences in kurtosis
values for all three metrics between the malignant and benign breast lesions
(all
P > 0.05).
Conclusions
The histogram analysis of pharmacokinetic parameters can
improve the diagnostic accuracy of breast DCE-MRI imaging with CDT-VIBE
technique. The 90th percentile of kep
may be the best indicator in the differentiation of malignant and benign breast
lesions.
Acknowledgements
No acknowledgement found.References
1. Michaely, et al.Invest Radiol, 2013. 48(8): p. 590-7. 2. Kim EJ, et al. J Magn Reson Imaging 2015.