Dae-Myoung Yang1,2,3, David A Palma4,5, Keith Kwan6, Alexander V Louie7, Richard Malthaner8, Dalilah Fortin8, George B Rodrigues4,5, Brian P Yaremko4,5, Joanna Laba4,5, Stewart Gaede1,4,5, Andrew Warner5, Richard Inculet8, Ting-Yim Lee9,10,11,12. 1. Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, 1151 Richmond St N, London, ON, N6A 5C1, Canada. 2. Robarts Research Institute, University of Western Ontario, 1151 Richmond St N, London, ON, N6A 3K7, Canada. 3. Lawson Imaging Research Program, Lawson Health Research Institute, 268 Grosvenor St, London, ON, N6A 4V2, Canada. 4. Department of Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, 800 Commissioners Rd E, London, ON, N6A 5W9, Canada. 5. Department of Radiation Oncology, London Regional Cancer Program, 800 Commissioners Rd E, London, ON, N6A 5W9, Canada. 6. Pathology and Laboratory Medicine, London Health Sciences Centre, 800 Commissioners Rd E, London, ON, N6A 5W9, Canada. 7. Department of Radiation Oncology, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, ON, M4N 3M5, Canada. 8. Department of Surgery, Division of Thoracic Surgery, London Health Sciences Centre, 800 Commissioners Rd E, London, ON, N6A 5W9, Canada. 9. Department of Medical Biophysics, Schulich School of Medicine and Dentistry, University of Western Ontario, 1151 Richmond St N, London, ON, N6A 5C1, Canada. tlee@imaging.robarts.ca. 10. Robarts Research Institute, University of Western Ontario, 1151 Richmond St N, London, ON, N6A 3K7, Canada. tlee@imaging.robarts.ca. 11. Lawson Imaging Research Program, Lawson Health Research Institute, 268 Grosvenor St, London, ON, N6A 4V2, Canada. tlee@imaging.robarts.ca. 12. Department of Oncology, Schulich School of Medicine and Dentistry, University of Western Ontario, 800 Commissioners Rd E, London, ON, N6A 5W9, Canada. tlee@imaging.robarts.ca.
Abstract
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.
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.
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