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EJNMMI Res. 2017 Dec;7(1):47. doi: 10.1186/s13550-017-0291-2. Epub 2017 May 25.

Quantitative analysis of dynamic 18F-FDG PET/CT for measurement of lung inflammation.

Author information

1
Imanova Ltd., Centre for Imaging Sciences, Hammersmith Hospital, London, UK. christopher.coello@gmail.com.
2
Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK. christopher.coello@gmail.com.
3
Experimental Medicine and Immunotherapeutics (EMIT) Division, Department of Medicine, University of Cambridge, Cambridge, UK.
4
NIHR Respiratory Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College, London, UK.
5
GSK R&D, King of Prussia, PA, USA.
6
GSK R&D, Stevenage, UK.
7
Imanova Ltd., Centre for Imaging Sciences, Hammersmith Hospital, London, UK.
8
Cambridge Clinical Trials Unit, Addenbrooke's Hospital, Cambridge, UK.
9
GSK R&D, Cambridge, UK.
10
Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK.
11
Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK.
12
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.

Abstract

BACKGROUND:

An inflammatory reaction in the airways and lung parenchyma, comprised mainly of neutrophils and alveolar macrophages, is present in some patients with chronic obstructive pulmonary disease (COPD). Thoracic fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) has been proposed as a promising imaging biomarker to assess this inflammation. We sought to introduce a fully quantitative analysis method and compare this with previously published studies based on the Patlak approach using a dataset comprising 18F-FDG PET scans from COPD subjects with elevated circulating inflammatory markers (fibrinogen) and matched healthy volunteers (HV). Dynamic 18F-FDG PET scans were obtained for high-fibrinogen (>2.8 g/l) COPD subjects (N = 10) and never smoking HV (N = 10). Lungs were segmented using co-registered computed tomography images and subregions (upper, middle and lower) were semi-automatically defined. A quantitative analysis approach was developed, which corrects for the presence of air and blood in the lung (qABL method), enabling direct estimation of the metabolic rate of FDG in lung tissue. A normalised Patlak analysis approach was also performed to enable comparison with previously published results. Effect sizes (Hedge's g) were used to compare HV and COPD groups.

RESULTS:

The qABL method detected no difference (Hedge's g = 0.15 [-0.76 1.04]) in the tissue metabolic rate of FDG in the whole lung between HV (μ = 6.0 ± 1.9 × 10-3 ml cm-3 min-1) and COPD (μ = 5.7 ± 1.7 × 10-3 ml cm-3 min-1). However, analysis with the normalised Patlak approach detected a significant difference (Hedge's g = -1.59 [-2.57 -0.48]) in whole lung between HV (μ = 2.9 ± 0.5 × 10-3 ml cm-3 min-1) and COPD (μ = 3.9 ± 0.7 × 10-3 ml cm-3 min-1). The normalised Patlak endpoint was shown to be a composite measure influenced by air volume, blood volume and actual uptake of 18F-FDG in lung tissue.

CONCLUSIONS:

We have introduced a quantitative analysis method that provides a direct estimate of the metabolic rate of FDG in lung tissue. This work provides further understanding of the underlying origin of the 18F-FDG signal in the lung in disease groups and helps interpreting changes following standard or novel therapies.

KEYWORDS:

18F-FDG; COPD; Lung inflammation; Modelling; PET

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