Synopsis

In summary, liver imaging has found its place in the reality of cross-sectional imaging. The use of contrast agent is still controversial. Here further developments are directed in order to improve the qualitative and quantitative information. Artificial intelligence techniques will integrate multiparametric MRI information in the concept of radionics and radiogenomics.

Magnetic resonance imaging (MRI) of the liver slowly transitions from a problem-solving imaging modality to first-line imaging modality for many diseases of the liver. Well-established advantages of MRI over other cross-sectional imaging modalities are the basis for this transition. New technological advancements in the past and present focus on high-quality images, fast imaging, increasing diagnostic accuracy and developing newer function-specific tests like MR spectroscopy, MR elastography, and the latest techniques and functional imaging. The use of gadolinium-based contrast agents is controversial due to findings with permanent deposition of gadolinium in neural structures. However, contrast-enhanced dynamic T1w imaging is crucial in the evaluation of focal liver diseases, especially in the detection, staging and therapy planning of hepatocellular carcinomas (HCC). The latest techniques include fluoro-triggered contrast-enhanced MRI, bolus timing, and artificial intelligence-based learning techniques for the interpretation of MR findings.

Acknowledgements

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References

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