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Diffusion-Weighted Imaging: An Exciting and Problem-Solving Tool in Patients with Hepatic Metastases
Background The diffusion-weighted imaging (DWI) is based on the random Brownian motion of water molecules that influences image contrast depending on different pathological conditions.
Objective The purpose of this study was to evaluate the efficacy of various magnetic resonance imaging (MRI) sequences including diffusion-weighted and gadobenate-enhanced MRI in the detection and characterization of liver lesions in a patient of known primary malignancy and to compare MRI with contrast-enhanced computed tomography (CECT) and ultrasonography (USG) in the detection of liver metastases.
Methods All patients underwent a multiphase MRI. The final diagnosis was established by histopathological examination.
Results A total of 43 patients of known primary malignancy were enrolled. MRI gave a provisional diagnosis of liver metastases in 21 patients and benign disease in 22 patients with histopathological correlation revealing two false-negative and one false-positive result. In the detection of lesions, DWI outscored other sequences (92.9 vs. 83.5% in hepatobiliary phase vs. 55.0% in T2-weighted sequences) with a statistically significant difference noted only in comparison with T2-weighted sequences (p < 0.001). In 16 patients, MRI added new lesions that were not detected by CECT/USG. The sensitivity and specificity of MRI for detecting metastases were 90.9%/95.2% and 97.9%/96.8% for per-patient and per-lesion basis, respectively.
Conclusion Multiphase MRI improved both the detection and characterization of liver metastases. Adding DWI to the routine MR sequences helped in detecting small liver metastases (<10 mm) not detected by other sequences.
Keywordsdiffusion-weighted imaging - contrast-enhanced computed tomography - hepatic metastases - multiphase MRI - ultrasonography
23 May 2021 (online)
© 2021. Indian Radiological Association. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).
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