Background/Objectives: This study aims to present a structured clinical workflow for offline adaptive Biology-guided Radiotherapy (BgRT) using the RefleXion X1 PET-linac system, addressing challenges introduced by inter-treatment anatomical and biological changes. Methods: We propose a decision tree offline adaptation framework based on real-time assessments of Activity Concentration (AC), Normalized Target Signal (NTS), and bounded dose-volume histogram (bDVH%) metrics. Three offline strategies were developed: (1) preemptive adaptation for minor changes, (2) partial re-simulation for moderate changes, and (3) full re-simulation for major anatomical or metabolic alterations. Two clinical cases demonstrating strategies 1 and 2 are presented. Results: The preemptive adaptation strategy was applied in a case with early tumor shrinkage, maintaining delivery parameters within acceptable limits while updating contours and dose distribution. In the partial re-Simulation case, significant changes in PET signal necessitated a same-day PET functional modeling session and plan re-optimization, effectively restoring safe deliverability. Both cases showed reduced target volumes and improved OAR sparing without additional patient visits or tracer injections. Conclusions: Offline adaptive workflows for BgRT provide practical solutions to address inter-fractional changes in tumor structure and function. These strategies can help maintain the safety and accuracy of BgRT delivery and support clinical adoption of PET-guided radiotherapy, paving the way for future online adaptive capabilities.

Background/Objectives: The aim of this study was to establish the relationship between target size and the required diagnostic PET maximum standard uptake value (SUVmax) thresholds needed for successful Biology-guided Radiotherapy (BgRT) delivery on RefleXion X1 PET-linac. The current clinical eligibility recommendation is an SUVmax ≥ 6 at simulation, but the RefleXion system subsequently evaluates Activity Concentration (AC), which must exceed 5 kBq/mL for successful BgRT planning. Methods: A custom 3D-printed phantom containing six spherical targets (8 to 20 mm diameter) was used with varying target-to-background ratios (5:1 to 20:1) of 18F-FDG to systematically achieve a range of SUVmax values for each target size. Images were acquired on Siemens Biograph mCT for SUVmax quantification and RefleXion X1 for AC measurements. Twenty-four BgRT plans were evaluated, and delivery accuracy was validated using ArcCHECK. Additionally, retrospective data from 18 patients across four institutions were analyzed to validate the phantom-derived findings. Results: The PET-linac successfully planned treatments for 13/24 experiments, all achieving an AC > 5 kBq/mL. SUVmax requirements varied by target size: 16–20 mm targets required an SUVmax > 6, consistent with current recommendations, while smaller targets required higher thresholds (e.g., 13 mm: SUVmax > 10, and 11 mm: SUVmax > 15). 8 and 9 mm targets failed to meet AC requirements even at SUVmax 14. Successful deliveries maintained acceptable accuracy, with gamma passing rates of 92.4% ± 5.0% (3%/2 mm) and 97.6% ± 1.9% (3%/3 mm). Analysis revealed that Volume (cc) × SUVmax > 11 consistently predicted successful BgRT planning across all target sizes. This threshold was validated using multi-institutional PET-CT patient data (mean: 11.36, 95% CI: 9.1–12.9), correctly predicting treatment eligibility in 15 of 18 cases. Conclusions: Target size significantly influences BgRT eligibility. We derived a new criterion, Volume(cc) × SUVmax > 11 (95% CI: 9.1–12).