4.7 Article

Diffusion Kurtosis at 3.0T as an in vivo Imaging Marker for Breast Cancer Characterization: Correlation With Prognostic Factors

期刊

JOURNAL OF MAGNETIC RESONANCE IMAGING
卷 49, 期 3, 页码 845-856

出版社

WILEY
DOI: 10.1002/jmri.26249

关键词

MRI; breast cancer; risk stratification; diffusion kurtosis

资金

  1. National Natural Science Foundation of China [81471729, 81101102]
  2. Science and Technology Planning Project of Guangdong Province [2016A020216025]
  3. Research Award Fund for Outstanding Young Teachers in Higher Education Institutions, Guangdong Province [YQ2015245]
  4. National Natural Science Foundation of Guangdong Province [S2011010004973]
  5. Department of Education of Guangdong Province [2017KTSCX071]

向作者/读者索取更多资源

BackgroundDiffusion-kurtosis imaging (DKI) has preliminarily shown promise as a relatively new MRI technique to provide useful information regarding breast lesions, but the diagnostic performance of DKI has not been fully evaluated. PurposeTo compare the diagnostic accuracy of DKI, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI) and proton MR spectroscopy (H-1-MRS) in differentiating malignant from benign breast lesions independently or jointly, and explore the correlation between DKI-derived parameters and prognostic factors. Study TypeProspective. SubjectsSeventy-one patients with breast lesions (50 malignant, 26 benign). SequenceDKI, DWI, DCE-MRI, and H-1-MRS were performed at 3.0T. AssessmentMean kurtosis (MK), mean diffusivity (MD), apparent diffusion coefficient (ADC), BI-RADS category, and choline peaks were analyzed by two experienced radiologists. Statistical TestsStudent's t-test was used for continuous variables; receiver operating characteristic (ROC) analysis for assessing the diagnostic accuracy of imaging parameters; Spearman or Pearson correlations for assessing the associations between imaging parameters and prognostic factors. ResultsMK exhibited higher area under the curves (AUCs) for differentiating malignant from benign lesions than did MD, ADC, DCE, and tCho (0.979 vs. 0.928, 0.911, 0.777, and 0.833, respectively, P<0.05). MK showed a positive association with Ki-67 expression (r=0.508) and histologic grades (r=0.551), whereas MD and ADC were negatively correlated with Ki-67 expression (r=-0.416 and r=-0.458) and histologic grades (r=-0.411 and r=-0.319). Moreover, MK showed relatively higher AUCs compared with MD and ADC in detecting breast cancers with lymph nodal involvement, histologic grades, and Ki-67 expression. Data ConclusionMK has higher diagnostic accuracy compared with ADC, DCE, and tCho regarding detection of breast cancer. Moreover, DKI shows promise as a quantitative imaging technique for characterizing breast lesions, highlighting the potential utility of MK as a promising imaging marker for predicting tumor aggressiveness. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:845-856.

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