title: Characterization of breast tumors using diffusion kurtosis imaging (DKI).
abstract: OBJECTIVE
  The aim of this study was to investigate and evaluate the role of magnetic resonance (MR) diffusion kurtosis imaging (DKI) in characterizing breast lesions.
  
  
  METHODS
  One hundred and twenty-four lesions in 103 patients (mean age: 57 ± 14 years) were evaluated by MR DKI performed with 7 b-values of 0, 250, 500, 750, 1,000, 1,500, 2,000 s/mm2 and dynamic contrast-enhanced (DCE) MR imaging. Breast lesions were histologically characterized and DKI related parameters--mean diffusivity (MD) and mean kurtosis (MK)--were measured. The MD and MK in normal fibroglandular breast tissue, benign and malignant lesions were compared by One-way analysis of variance (ANOVA) with Tukey's multiple comparison test. Receiver operating characteristic (ROC) analysis was performed to assess the sensitivity and specificity of MD and MK in the diagnosis of breast lesions.
  
  
  RESULTS
  The benign lesions (n = 42) and malignant lesions (n = 82) had mean diameters of 11.4 ± 3.4 mm and 35.8 ± 20.1 mm, respectively. The MK for malignant lesions (0.88 ± 0.17) was significantly higher than that for benign lesions (0.47 ± 0.14) (P < 0.001), and, in contrast, MD for benign lesions (1.97 ± 0.35 (10(-3) mm2/s)) was higher than that for malignant lesions (1.20 ± 0.31 (10(-3) mm2/s)) (P < 0.001). At a cutoff MD/MK 1.58 (10(-3) mm2/s)/0.69, sensitivity and specificity of MD/MK for the diagnosis of malignant were 79.3%/84.2% and 92.9%/92.9%, respectively. The area under the curve (AUC) is 0.86/0.92 for MD/MK.
  
  
  CONCLUSIONS
  DKI could provide valuable information on the diffusion properties related to tumor microenvironment and increase diagnostic confidence of breast tumors.
authors.affiliation: Shanghai Key Laboratory of Magnetic Resonance, East China Normal University, Shanghai, China; Department of Radiology, Wayne State University, Detroit, Michigan, United States of America.
authors.forename: Dongmei
authors.initials: D
authors.lastname: Wu
authors.affiliation: Department of Radiology, Yue Yang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
authors.forename: Guanwu
authors.initials: G
authors.lastname: Li
authors.affiliation: Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui Province, China.
authors.forename: Junxiang
authors.initials: J
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Yue Yang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
authors.forename: Shixing
authors.initials: S
authors.lastname: Chang
authors.affiliation: Department of Radiology, Wayne State University, Detroit, Michigan, United States of America.
authors.forename: Jiani
authors.initials: J
authors.lastname: Hu
authors.affiliation: Philips Healthcare, Shanghai, China.
authors.forename: Yongming
authors.initials: Y
authors.lastname: Dai
mesh_terms: D000368:Aged; D000704:Analysis of Variance; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D012372:ROC Curve; D059016:Tumor Microenvironment