Predicting Pathological Complete Response (Pcr) After Stereotactic Ablative Radiation Therapy (Sabr) of Lung Cancer Using Quantitative Dynamic [18f]fdg Pet and Ct Perfusion: A Prospective Exploratory Clinical Study [post]

Dae-Myoung Yang, David A. Palma, Keith Kwan, Alexander V. Louie, Richard Malthaner, Dalilah Fortin, George B. Rodrigues, Brian P. Yaremko, Joanna Laba, Stewart Gaede, Andrew Warner, Richard Inculet (+1 others)
2020 unpublished
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 fortrue 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
more » ... d, as a pre-specified secondary analysis of a larger study. 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. Using recursive partitioning analysis (RPA), the imaging-based biomarkers for predicting pCRwere assessedand 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 threepatient groups based on tumour blood volume before SABR (BVpre-SABR) and change in SUV­max (ΔSUVmax).The highest true pCR rate of 92%was observed in the group withBVpre-SABR< 9.3 mL/100g and ΔSUVmax< -48.9% after SABR while the worst was observed in the group with BVpre-SABR ≥ 9.3 (0%). A logistic regression model based on RPA risk groupsshowedexcellentpCRprediction(Concordance: 0.92; P=0.03). RECIST and PERCIST showed poor pCRprediction (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. This model warrants validation with larger sample size studies.Trial registration:MISSILE-NSCLC, NCT02136355 ( Registered May 8, 2014,
doi:10.21203/ fatcat:bfiizz4y4jf2tfaep3dqqbpegy