A Quantitative Framework for Longitudinal Multimodal Integration in Oncology Imaging

This work introduces a Dynamic Relativistic Imaging framework applied to magnetic resonance imaging, designed to make implicit tumor dynamics visually and clinically explicit. By integrating longitudinal MRI data (T0–T1), relativistic differentials, biological time estimation (τᵦ), and a structured color-coding system, the approach reveals patterns of instability, inertia, and transition that are not detectable through conventional structural assessment alone. The method shifts image interpretation from static morphology to dynamic behavior, enabling the identification of localized therapeutic vulnerability before overt volumetric progression occurs. The incorporation of the U-Index provides a global metric of tumor reorganization and regime change, independent of size-based criteria. This framework allows the estimation of biologically meaningful therapeutic windows, expressed in days to weeks rather than imaging intervals. Color-linked dynamic states are further connected to dominant biological vulnerabilities, supporting integrative clinical reasoning without being prescriptive. Overall, the work reframes MRI as a temporally informed, predictive tool that supports earlier, more precise oncologic decision-making.