Integrating Imaging, Clinical, and Pathological Data on Post-hepatectomy Liver Failure

We present a multi-institutional dataset of preoperative Gd-EOB-DTPA-enhanced MRI scans, comprising 14,895 images across three academic medical centers. This comprehensive dataset includes more than 20,000 expert annotations of key anatomical structures - such as the liver, Couinaud liver segments, liver tumors, spleen, and psoas muscles - enabling automated quantification of future liver remnant (FLR) volume and functional assessment. Additionally, it incorporates detailed clinicopathological variables, with all annotations subjected to a two-tier radiological review process to ensure labeling accuracy and reliability. By integrating FLR volume, Gd-EOB-DTPA-enhanced MRI-derived functional parameters, and clinical risk factors, this dataset serves as a foundational resource for developing interpretable and generalizable AI models.