Comparison Of The Diagnostic Value Of Mono-Exponential, Bi-Exponential, And Stretched Exponential Signal Models In Diffusion-Weighted Mr Imaging For Differentiating Benign And Malignant Hepatic Lesions

MAGNETIC RESONANCE IN MEDICAL SCIENCES(2021)

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摘要
Purpose: To compare the diagnostic value of mono-exponential, bi-exponential, and stretched exponential diffusion-weighted imaging (DWI) for differentiating benign and malignant hepatic lesions.Methods: This prospective study was approved by our Institutional Review Board and the patients provided written informed consent. Magnetic resonance imaging was acquired for 56 patients with suspected liver disease. This identified 90 focal liver lesions with a maximum diameter >10 mm, of which 47 were benign and 43 were malignant. Using home-built software, two radiologists measured the DWI parameters of hepatic lesions for three models: the apparent diffusion coefficient (ADC) from a mono-exponential model; the true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from a bi-exponential model; and the distributed diffusion coefficient ( DDC) and water molecular diffusion heterogeneity index (alpha) from a stretched exponential model. The parameters were compared between benign and malignant hepatic lesions.Results: ADC, D, D*, f, and DDC values were significantly lower for malignant hepatic lesions than for benign lesions (P < 0.0001-0.03). Although logistic regression analysis demonstrated that DDC was the only statistically significant parameter for differentiating benign and malignant lesions (P = 0.039), however, the areas under the receiver operating characteristic curve for differentiating benign and malignant lesions were comparable between ADC (0.98) and DDC (0.98) values.Conclusion: DDC values obtained from the stretched exponential model could be also used as a quantitative imaging biomarker for differentiating benign and malignant hepatic lesions, however, the diagnostic performance was comparable with ADC values.
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关键词
magnetic resonance imaging, liver neoplasms, abdomen
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