Simulating the Potential of Model-Based Individualized Prescriptions for Ultracentral Lung Tumors

Purpose/ObjectivesThe use of SBRT for ultracentral lung tumors is limited by increased toxicity. We hypothesized that using published normal tissue complication probability (NTCP) and tumor control (TCP) models, could improve the therapeutic ratio between A proposed model-based approach was applied to virtually replan early stage non-small cell cancer (NSCLC) tumors.Materials/MethodsThe analysis included 63 patients with NSCLC treated at our center 2008 2017. Along current clinical constraints, additional NTCP criteria including grade 3+ radiation pneumonitis (RP3+) 2+ esophagitis (E2+) were implemented, four different fractionation schemes. Scaled dose distributions resulting in highest TCP without violating constraints selected (Planopt). Planopt predictions compared observed local (LC) toxicities.ResultsThe 2-year LC rate 72% (95%CI 57-88%) 87% (range 6-93%) TCP. 39 had > 80%, while 14 < 50%. The NTCPs RP3+ reduced nearly half patients’ RP3+. most frequent reason 80% (14/24 patients), followed E2+ (5/24 patients) due larger (>40 cc vs <=40cc; p=0.002) or a shorter esophagus distance (>=5cm <5cm; p<0.001).ConclusionsWe demonstrated potential prescriptions yield higher respecting patient NSCLC. Individualizing treatments based on TCP-driven simulations halved predicted relative rates Our also identified whose not be improved near proximity.