Artificial intelligence in colorectal liver metastases: From detection and resectability to treatment response and recurrence prediction

Figure 1 Conceptual framework for artificial intelligence across the colorectal liver metastasis care pathway. The pathway is shown as five sequential domains: A: Detection and characterization; B: Resectability assessment and surgical planning; C: Intraoperative guidance; D: Treatment-response prediction; E: Recurrence and survival prediction. Input data types (computed tomography, magnetic resonance imaging, whole-slide histopathology, molecular and clinical variables) feed the corresponding artificial intelligence methods (radiomics, machine learning, deep learning), and each domain is annotated with its current stage of clinical maturity. 3D: Three-dimensional; CRLM: Colorectal liver metastases; CT: Computed tomography; FLR: Future liver remnant; ICG: Indocyanine green; MRI: Magnetic resonance imaging; RFS: Recurrence-free survival.