Characterization of Breast Lesions Using Diffusion Kurtosis Model-Based Imaging
Journal Title: Biomedical Journal of Scientific & Technical Research (BJSTR) - Year 2019, Vol 19, Issue 3
Abstract
Objective: To investigate the characterization of breast lesions using diffusion kurtosis model-based imaging. Methods: This prospective study included 120 consecutive patients underwent preoperative DCE-MRI examinations and multi-b-value diffusion-weighted imaging (DWI). 88 maligant lesions and 44 benign lesions were found and 56 normal fibroglandular breast tissue were selected as normal control. Conventional apparent diffusion coefficient (ADC) as well as DKI-based parameters mean kurtosis (MK) and mean diffusivity (MD) were analyzed by lesions types and histological subtypes using one-way ANOVA and receiver operating characteristic (ROC) curve. Results: a) The malignant group showed significantly lower ADC and MD (1.07±0.32 ×10-3 and 1.30±0.40 ×10-3 mm2/s, respectively) and higher MK(0.87±0.18)than the benign group(1.29±0.26 ×10-3, 1.62±0.31 ×10-3 mm2/s and 0.67±0.18,respectively) and normal control(1.67±0.33 ×10-3, 2.24±0.28 ×10-3 mm2/s and 0.52±0.08) (all P<0.001). b) Area under the curve (AUC) for diagnosing malignant lesions was 0.936 for MD, 0.911 for MK and 0.897 for ADC. The AUC for MD was significantly higher than that for ADC(P=0.015).The optimal cut-off values, sensitivity, specificity, positive predictive value, negative predictive value and accuracy were as follow: ADC=1.18×103mm2/s,78.3%,93.2%,81.2%, 81.6%,81.4%;MD=1.48×103mm2/s, 82.2%, 98.3%, 84.4%, 87.8%, 86.2%; MK=0.78, 91.5%, 85.3%, 89.0%, 85.8%, 87.2%. c) Invasive ductal carcinoma (IDC), ductal carcinoma in situ (DCIS) and mucinous adenocarcinoma showed significantly different ADC, MD and MK values (all P<0.05).n Conclusions: MR-DKI parameters enable to improve breast lesion characterization and have diagnostic potential in different pathological subtypes of breast cancers.Breast cancer has become the most common form of tumors in women [1], and Dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is an rather sensitive technique method for early detection and identification of benign and malignant breast lesions. However, diagnostic difficulty may exist in identification of benign and malignant breast lesions due to the overlap of time intensity curves of benign and malignant lesions. MR diffusion-weighted imaging (DWI) is of value in diagnosing of benign and malignant breast lesions, and its apparent diffusion coefficient (ADC) can improve the specificity of dynamic contrastenhanced (DCE) MRI in the diagnosis of malignant breast lesions [2-4]. However, there is also a substantial overlap in ADC values for benign and malignant lesions. The traditional DWI is based on the assumption that the diffusion of water molecules (random Brownian motion) within tissues is in accordance with a Gaussian distribution, whereas restrictions imposed by cell membranes, organelles, shrunked intercellular spaces due to cell proliferation and complex structures in tumor tissues result in the diffusion of water molecules deviating from a Gaussian distribution. Acknowledging this problem, Jensen et al. [5,6] introduced a diffusion kurtosis imaging (DKI) model which is an extension of Difussion Tenser Imaging (DTI) to quantitatively describe the displacement of water molecular diffusion that deviated from a Gaussian distribution. Mean kurtosis and mean diffusion coeffcients are calculated from this model.
Authors and Affiliations
Shao-zhong HE, WANG Qun, Ya-Ting Mao
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