02 March 2016 : Clinical Research
Evaluation of Hepatic Tumors Using Intravoxel Incoherent Motion Diffusion-Weighted MRI
Mingjie WangAE, Xudan LiBF, Jianxun ZouAD, Xugao ChenBF, Shuyan ChenD, Wanqing XiangBDOI: 10.12659/MSM.895909
Med Sci Monit 2016; 22:702-709
Abstract
BACKGROUND: This study aimed to evaluate the diagnostic value of the D value, D* value, and f magnitude for identifying benign and malignant hepatic tumors using intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI).
MATERIAL AND METHODS: Data of 89 cases (123 lesions) with hepatic tumor confirmed by surgical pathology and postoperative follow-up were retrospectively collected. Among these cases, 40 cases were benign hepatic tumors (57 lesions) and 49 cases were malignant hepatic tumors (66 lesions). All subjects underwent conventional MRI with T1WI, T2WI, multi-b-value DWI, and dynamic enhanced LAVA scan. Diffusion-weighted images with 11 b values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, and 1000 s/mm2) were obtained to calculate true molecular diffusion (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (f). The diagnostic performance in differentiating between malignant and benign hepatic lesions was analyzed.
RESULTS: Malignant lesions had a significantly lower D value ([1.04±0.34]×10–3 mm2/s) and D* value ([16.5±7.7]×10–3 mm2/s) compared to benign lesions (D value: [1.70±0.55]×10–3 mm2/s, P<0.01; D* value: [21.7±9.9]×10–3 mm2/s, P<0.01). There was no statistically significant difference in f values between malignant (23.3±9.5) and benign lesions (33.5±14.9, P=0.13). In addition, D exhibited a better diagnostic performance than D* in terms of the area under the curve, sensitivity, and specificity when identifying malignancies from benign lesions.
CONCLUSIONS: D and D* are significant parameters for diagnosing hepatic tumors. Moreover, the D value is a more reliable parameter in distinguishing benign and malignant hepatic tumors.
Keywords: Aged, 80 and over, Diffusion Magnetic Resonance Imaging - methods, Liver Neoplasms - diagnosis, Signal Processing, Computer-Assisted
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