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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
Value of Multimodal Diffusion-weighted Imaging in Preoperative Evaluation of Ki-67 Expression in Endometrial
Huan Meng1, Si-Xuan Ding1, Yu Zhang1
1Department of Radiology, Affiliated Hospital of Hebei University, Baoding, Hebei Province, China.
Purpose:
Purpose: To investigate the value of multimodal diffusion weighted imaging (DWI) in preoperative evaluation of Ki-67 expression of endometrial carcinoma (EC).
Materials And Methods:
Patients who had undergone pelvic DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) sequence MRI scan before surgery were retrospectively enrolled. Single index model, double index model, and DKI were used for post-processing of the DWI data, and the apparent diffusion coefficient (ADC), real diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), non-Gaussian mean diffusion kurtosis (MK), mean diffusion coefficient (MD) and anisotropy fraction (FA) were calculated and compared between the Ki-67 high (≥50%) and low (<50%) expression groups.
Results:
Forty-two patients with a median age of 56 (range 37 - 75) years were enrolled, including 15 patients with a high Ki-67 (≥50%) expression and 27 with a low Ki-67 (<50%) expression. The MK (0.91 ± 0.12 vs. 0.76 ± 0.12) was significantly (P<0.05) higher while MD (0.99 ± 0.17 vs. 1.16 ± 0.22), D (0.55 ± 0.06 vs. 0.62 ± 0.08), and f (0.21 vs. 0.28) were significantly (P<0.05) lower in the high than in the low expression group. The combined model of MK, MD, D, and f-values had the largest area under the curve (AUC) value of 0.869 (95% CI: 0.764-0.974), sensitivity 0.733 and specificity 0.852, followed by the MK value with an AUC value 0.827 (95% CI: 0.700-0.954), sensitivity 0.733 and specificity 0.815.
Conclusions:
IVIM and DKI have certain diagnostic values for preoperative evaluation of the EC Ki-67 expression, and the combined model has the highest diagnostic efficiency.
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