Conceptual shift from static and reactive to spatiotemporal and adaptive precision management of GI cancers (IMAGE)
Caption
The traditional paradigm is characterized by single-time-point biopsy, limited biomarker assessment, and a largely linear treatment pathway, with treatment modification often triggered by overt disease progression. The proposed paradigm integrates spatial profiling, longitudinal temporal monitoring, and AI-enabled decision support to enable dynamic clinical management. Three decision turning points are defined: T1 (predict, baseline) for estimating treatment benefit and informing initial treatment selection; T2 (adapt, on-treatment) for reassessing treatment response and emerging resistance and supporting treatment adaptation; and T3 (intercept, surveillance) for estimating recurrence or MRD risk and enabling earlier intervention. Together, these decision functions establish a closed-loop framework aimed at achieving the right treatment for the right patient at the right time. AI: artificial intelligence; ctDNA: circulating tumor DNA; GI: gastrointestinal; MRD: minimal residual disease
Credit
Pan Gao, Jun Zhang.
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License
CC BY