Learning Objectives: On successful completion of this activity, participants should be able to (1) describe the methods that have been used to quantify 18 F-FDG uptake in the lungs using dynamic PET; (2) discuss the interpretation of the outcomes from these methods; and (3) provide suggested considerations on quantification of 18 F-FDG uptake in the lungs for future studies.

Background: Respiratory diseases are one of the leading causes of death worldwide, yet effective treatment options remain limited. Although inflammation is thought to be a key driver in the pathogenesis and progression of several lung diseases, the underlying molecular mechanisms of lung dysfunction remain poorly understood. Imaging techniques may help to further our understanding of the pathophysiology and facilitate the translation of novel therapies. Positron Emission Tomography (PET) is a functional imaging technique which has the potential to interrogate the underlying inflammatory response. We present a systematic review of the literature summarising the emerging PET radiotracers developed to quantify pulmonary inflammation. Method: We performed a systematic review using the following databases: Medline, Embase, Scopus, PubMed, Web of Science and Cochrane. We included articles between 1995 and 2019 for all studies using PET radiotracers to evaluate inflammatory response in the lung. From a total of 911 articles covering both animal and human studies, two reviewers selected papers based on the inclusion/exclusion criteria and extracted data from 68 articles selected. Results: 53 out of 68 papers, including both human and animal studies, were eligible for synthesis. Heterogenous study populations and differences in study design, image acquisition and analysis made data pooling unfeasible; instead, we provide a narrative synthesis. Conclusions: Currently, very few novel radiotracers targeting lung inflammation have crossed the translational gap from animal models to human studies. Nevertheless, our results highlight a handful of promising tracers which warrant further evaluation in humans. 18 F-FDG has been investigated most extensively; although 18 F-FDG is not a specific inflammatory tracer, human studies of several pulmonary diseases support its use as a biomarker for inflammation. Despite ongoing debate about the optimal analysis methodology for 18 F-FDG lung images, standardisation of image acquisition and analysis should help to improve confidence in research outcomes. PET radiotracers can provide quantitative, targeted biomarkers which relate to the activity of molecular pathways and may expedite development of specific anti-inflammatory drugs.

Positron emission tomography (PET) with 18 F-fluorodeoxyglucose (18 F-FDG) has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and monitor disease progression and treatment outcomes in lung diseases, disorders that interfere with gas exchange through alterations of the pulmonary parenchyma, airways and/or vasculature. To date, however, there are no widely accepted standard acquisition protocols and imaging data analysis methods for pulmonary 18 F-FDG PET/CT in these diseases, resulting in disparate approaches. Hence, comparison of data across the literature is challenging. To help harmonize the acquisition and analysis and promote reproducibility, acquisition protocol and analysis method details were collated from seven PET centers. Based on this information and discussions among the authors, the consensus recommendations reported here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting were reached.

YNS is a lymphatic phenotype because lymphatic insufficiency was found to exist in all patients and the insufficiency was widespread (upper and lower limbs), with a common mechanistic fault of poor transport. The origin of the lymphatic fault is unclear. In healthy individuals, lymphatic abnormalities may be relatively common in the fifth decade of life onward.

IntroductionCompartmental modelling is an established method of quantifying 18F-FDG uptake; however, only recently has it been applied to evaluate pulmonary inflammation. Implementation of compartmental models remains challenging in the lung, partly due to the low signal-to-noise ratio compared to other organs and the lack of standardisation. Good reproducibility is a key requirement of an imaging biomarker which has yet to be demonstrated in pulmonary compartmental models of 18F-FDG; in this paper, we address this unmet need.MethodsRetrospective subject data were obtained from the EVOLVE observational study: Ten COPD patients (age =66±9; 8M/2F), 10 α1ATD patients (age =63±8; 7M/3F) and 10 healthy volunteers (age =68±8; 9M/1F) never smokers. PET and CT images were co-registered, and whole lung regions were extracted from CT using an automated algorithm; the descending aorta was defined using a manually drawn region. Subsequent stages of the compartmental analysis were performed by two independent operators using (i) a MIAKATTM based pipeline and (ii) an in-house developed pipeline. We evaluated the metabolic rate constant of 18F-FDG (Kim) and the fractional blood volume (Vb); Bland-Altman plots were used to compare the results. Further, we adjusted the in-house pipeline to identify the salient features in the analysis which may help improve the standardisation of this technique in the lung.ResultsThe initial agreement on a subject level was poor: Bland-Altman coefficients of reproducibility for Kim and Vb were 0.0031 and 0.047 respectively. However, the effect size between the groups (i.e. COPD, α1ATD and healthy subjects) was similar using either pipeline. We identified the key drivers of this difference using an incremental approach: ROI methodology, modelling of the IDIF and time delay estimation. Adjustment of these factors led to improved Bland-Altman coefficients of reproducibility of 0.0015 and 0.027 for Kim and Vb respectively.ConclusionsDespite similar methodology, differences in implementation can lead to disparate results in the outcome parameters. When reporting the outcomes of lung compartmental modelling, we recommend the inclusion of the details of ROI methodology, input function fitting and time delay estimation to improve reproducibility.