Multiparametric magnetic resonance imaging, diffusion-weighted magnetic resonance imaging, and magnetic resonance...

This study investigates the accuracy of multiparametric magnetic resonance imaging (mpMRI), diffusion-weighted imaging (DWI), and magnetic resonance elastography (MRE) in differentiating benign and malignant liver lesions.

This retrospective study included patients with focal liver lesions who underwent MRI and MRE between 2018 and 2022. Based on histopathologic analyses or follow-up imaging findings, 70 solid liver lesions were retrospectively evaluated as benign (n = 20) or malignant (n = 50).

There was no statistically significant difference between the benign and malignant liver lesions in pre-contrast T1 relaxation times (P > 0.05). Malignant liver lesions had a significantly lower T2 value, contrast-enhancement ratio (CER), T1 relaxation time reduction (T1D), T1D percentage [T1D (%)], and apparent diffusion coefficient (ADC), along with a significantly higher stiffness value (P < 0.05). In receiver operating characteristic analysis, the following cut-off values were determined for differentiating malignant from benign lesions: a CER of 1.99 [area under the curve (AUC): 0.828, sensitivity 78.6%, specificity 73.2%], a T1D of 749.5 ms (AUC: 0.817, sensitivity 71.4%, specificity 78%), a T1D (%) reduction of 49.71% (AUC: 0.831, sensitivity 78.6%, specificity 73.2%), a T2 relaxation time of 74 ms (AUC: 0.705, sensitivity 65%, specificity 76.6%), an ADC of 1.275 × 10^-3 mm²/s (AUC: 0.861, sensitivity 89.5%, specificity 81.2%), and a stiffness of 3.77 kPa (AUC: 0.848, sensitivity 85%, specificity 75%).

Combined mpMRI, DWI, and MRE provide high diagnostic accuracy, with ADC and MRE offering superior performance in differentiating malignant from benign liver lesions.

This article highlights the accuracy of mpMRI, MRE, and DWI in distinguishing between malignant and benign liver lesions. These findings support the integration of mpMRI, DWI, and MRE into clinical practice for non-invasive liver lesion characterization.