Keywords: Quantitative Imaging, Liver, cT1, T2*, PDFF, volume, future liver remnantUnderstanding the interplay between quantitative MRI metrics is crucial for reliable clinical assessment of liver health. This study utilised Bayesian networks to visualise hidden relationships between cT1, T2*, proton density fat fraction (PDFF), volume and future liver remnant (FLR). Analysing the directionality between Bayesian networks on a pre-operative dataset with 130 participants and a post-operative dataset with 90 participants, clear causal relationships from PDFF to cT1 and from PDFF to volume were found, which are supported by published literature. An additional discovery is the potential for correlation between metrics to help strengthen the clinical utility of cT1 after surgery.
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