Quantitative kinetic modelling of FDG in lung imaging of COPD

Objectives Thoracic FDG PET/CT may be a promising imaging biomarker to assess novel therapies in inflammatory lung conditions, including Chronic Obstructive Pulmonary Disease (COPD). We analyzed baseline data in an ongoing multi-centre clinical trial (NCT01541852), which recruited high fibrinogen COPD patients, to investigate static and dynamic analysis methods to quantify parameters of lung tissue uptake in COPD and evaluate their correlation to clinical measures of airflow limitation Methods 62 COPD subjects were dynamically scanned following FDG bolus injection. Upper subdivision of the lung (UL) was delineated using the CT and was applied to the dynamic FBP reconstructed PET data to derive regional time activity curves. Mean SUV and SUVr (30-60min) were calculated. Kinetic model (KM) estimates of the metabolic rate (Ki) were calculated using an irreversible 2-tissue compartmental model (2TC-3k) with an image-derived input function (IDIF) from the pulmonary artery. Tissue density correction (TDC) was applied using either the CT or the PET-KM. The 2TC-3k model was applied both with and without a blood volume component to investigate the impact of blood volume correction (BVC). Subjects also underwent spirometry measures (FEV1%predicted) to assess severity of airflow limitation Results A significant negative correlation between PET outcome parameters and FEV1% was measured only with the quantitative KM parameter Ki. Stronger correlation was obtained following correction for both TD and BV (Table 1) and this yielded a higher range of Ki values (CoV=49%) as compared to TDC alone (CoV=32%) Conclusions Quantitative kinetic model estimation of 18F-FDG metabolic rate in lung tissue correlates strongly with measures of lung function and could be further considered for longitudinal assessment of changes in lung inflammation (Table Presented).