Introduction: Stereotactic ablative radiotherapy (SABR) is a guideline-recommended treatment for inoperable stage I non-small cell lung cancer (NSCLC), but imaging assessment of response after SABR is difficult. The goal of this study was to evaluate imaging-based biomarkers of tumour response using dynamic 18 F-FDG-PET and CT perfusion (CTP). Methods: Thirty-one patients with early-stage NSCLC participated in this prospective correlative study. Each underwent dynamic 18 F-FDG-PET/CTP studies on a PET/CT scanner pre-and 8 weeks post-SABR. The dynamic 18 F-FDG-PET measured the tumour SUV max , SUV mean and the following parameters: K 1 , k 2 , k 3 , k 4 and K i , all using the Johnson-Wilson-Lee kinetic model. CTP quantitatively mapped BF, BV, MTT and PS in tumours and measured largest tumour diameter. Since free-breathing was allowed during CTP scanning, non-rigid image registration of CT images was applied to minimize misregistration before generating the CTP functional maps. Differences between pre-and post-SABR imaging-based parameters were compared. Results: Tumour size changed only slightly after SABR (median 26 mm pre-SABR vs. 23 mm post-SABR; P = 0.01). However, dynamic 18 F-FDG-PET and CTP study showed substantial and significant changes in SUV max , SUV mean , k 3 , k 4 and K i . Significant decreases were evident in SUV max (median 6.1 vs. 2.6; P < 0.001), SUV mean (median 2.5 vs. 1.5; P < 0.001), k 3 (relative decrease of 52%; P = 0.002), K i (relative decrease of 27%; P = 0.03), whereas there was an increase in k 4 (+367%; P < 0.001). Conclusions: Hybrid 18 F-FDG-PET/CTP allowed the response of NSCLC to SABR to be assessed regarding metabolic and functional parameters. Future studies are needed, with correlation with long-term outcomes, to evaluate these findings as potential imaging biomarkers of response.

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Background Stereotactic ablative radiation therapy (SABR) is effective in treating inoperable stage I non-small cell lung cancer (NSCLC), but imaging assessment of response after SABR is difficult. This prospective study aimed to develop a predictive model for true pathologic complete response (pCR) to SABR using imaging-based biomarkers from dynamic [18F]FDG-PET and CT Perfusion (CTP). Methods Twenty-six patients with early-stage NSCLC treated with SABR followed by surgical resection were included, as a pre-specified secondary analysis of a larger study. Dynamic [18F]FDG-PET and CTP were performed pre-SABR and 8-week post. Dynamic [18F]FDG-PET provided maximum and mean standardized uptake value (SUV) and kinetic parameters estimated using a previously developed flow-modified two-tissue compartment model while CTP measured blood flow, blood volume and vessel permeability surface product. Recursive partitioning analysis (RPA) was used to establish a predictive model with the measured PET and CTP imaging biomarkers for predicting pCR. The model was compared to current RECIST (Response Evaluation Criteria in Solid Tumours version 1.1) and PERCIST (PET Response Criteria in Solid Tumours version 1.0) criteria. Results RPA identified three response groups based on tumour blood volume before SABR (BVpre-SABR) and change in SUVmax (ΔSUVmax), the thresholds being BVpre-SABR = 9.3 mL/100 g and ΔSUVmax = − 48.9%. The highest true pCR rate of 92% was observed in the group with BVpre-SABR < 9.3 mL/100 g and ΔSUVmax < − 48.9% after SABR while the worst was observed in the group with BVpre-SABR ≥ 9.3 mL/100 g (0%). RPA model achieved excellent pCR prediction (Concordance: 0.92; P = 0.03). RECIST and PERCIST showed poor pCR prediction (Concordance: 0.54 and 0.58, respectively). Conclusions In this study, we developed a predictive model based on dynamic [18F]FDG-PET and CT Perfusion imaging that was significantly better than RECIST and PERCIST criteria to predict pCR of NSCLC to SABR. The model used BVpre-SABR and ΔSUVmax which correlates to tumour microvessel density and cell proliferation, respectively and warrants validation with larger sample size studies. Trial registration MISSILE-NSCLC, NCT02136355 (ClinicalTrials.gov). Registered May 8, 2014, https://clinicaltrials.gov/ct2/show/NCT02136355