FLIP-HEDOS: a patient-specific blood dose quantification model during radiotherapy treatments

Objective.To introduce FLIP-HEDOS, a blood dose modeling framework that combines patient-specific and generic circulatory data to enable individualized blood dose estimation during radiotherapy (RT) treatments and to overcome limitations of non-personalized approaches.Approach.Patient-specific images of vasculature were obtained from patients with thorax-abdomen or head-neck tumors treated with proton or photon RT. Large vessels from the tumor location were segmented, and their blood flow velocities were extracted from phase-contrast MRI. Movement of blood particles (BPs) was simulated using a Lagrangian approach along patient-specific flowlines in these vessels, forming the FLIP method. This circulation was incorporated into a standardized model (HEDOS) to form a closed-loop whole-body model that computes the spatiotemporal BP distribution and associated blood dose accumulation, accounting for dose delivery dynamics, dose rate and beam-on/beam-off times. Cardiac output (CO) was individualized to match each patient blood flow characteristics. FLIP-HEDOS retains the modular HEDOS architecture, extending its large vessel compartments with the FLIP approach patient-specific vessels represented as new compartments. Remaining compartments were adapted to preserve the standardized connectivity of the circulatory network.Main Results.The study quantified mean blood dose values and tracked the number of times BPs entered patient-specific compartments during dose delivery. Simulations were performed across a range of inter-beam intervals, and the three models FLIP (patient-specific vessels), HEDOS (generic whole-body), and FLIP-HEDOS (integrated model) were compared with respect to their resulting blood dose values. The comparison shows that when patient-specific information is incorporated in blood dose assessment, BPs experience higher radiation doses.Significance.FLIP-HEDOS proves that standardized vascular data can be effectively combined with patient-specific parameters to achieve physiologically realistic modeling of circulating blood. By enabling individualized CO and blood flow dynamics, the framework adapts to the anatomical and hemodynamic characteristics of each patient.