In Vivo Visualization and Quantification of Neutrophil Elastase in Lungs of COVID-19 Patients: A First-in-Humans PET Study with 11C-NES.

Coronavirus disease 2019 (COVID-19) can cause life-threatening lung inflammation that is thought to be mediated by neutrophils. The aim of the present work was to evaluate a novel PET tracer for neutrophil elastase (NE). Methods: In this first-in-humans study, 4 patients with hypoxia due to COVID-19 and 2 healthy controls were investigated with PET using 11C-NES and 15O-water for visualization and quantification of NE and perfusion in the lungs, respectively. Results: 11C-NES accumulated selectively in lung areas with COVID-19 opacities on CT scans, suggesting high levels of NE there. In the same areas, perfusion was severely reduced in comparison to healthy lung tissue as measured with 15O-water. Conclusion: The data suggest that NE is associated with severe lung inflammation in COVID-19 patients and that inhibition of NE could potentially reduce the acute inflammatory process and improve the condition.

PET Imaging of Neutrophil Elastase with 11C-GW457427 in Acute Respiratory Distress Syndrome in Pigs.

Today, there is a lack of clinically available imaging techniques to detect and quantify specific immune cell populations. Neutrophils are one of the first immune cells at the site of inflammation, and they secrete the serine protease neutrophil elastase (NE), which is crucial in the fight against pathogens. However, the prolonged lifespan of neutrophils increases the risk that patients will develop severe complications, such as acute respiratory distress syndrome (ARDS). Here, we evaluated the novel radiolabeled NE inhibitor 11C-GW457427 in a pig model of ARDS, for detection and quantification of neutrophil activity in the lungs. Methods: ARDS was induced by intravenous administration of oleic acid to 5 farm pigs, and 4 were considered healthy controls. The severity of ARDS was monitored by clinical parameters of lung function and plasma biomarkers. Each pig was studied with 11C-GW457427 and PET/CT, before and after pretreatment with the NE inhibitor GW311616 to determine in vivo binding specificity. PET image data were analyzed as SUVs and correlated with immunohistochemical staining for NE in biopsies. Results: The binding of 11C-GW457427 was increased in pig lungs with induced ARDS (median SUVmean, 1.91; interquartile range [IQR], 1.67-2.55) compared with healthy control pigs (P < 0.05 and P = 0.03, respectively; median SUVmean, 1.04; IQR, 0.66-1.47). The binding was especially strong in lung regions with high levels of NE and ongoing inflammation, as verified by immunohistochemistry. The binding was successfully blocked by pretreatment of an NE inhibitor drug, which demonstrated the in vivo specificity of 11C-GW457427 (P < 0.05 and P = 0.04, respectively; median SUVmean, 0.60; IQR, 0.58-0.77). The binding in neutrophil-rich tissues such as bone marrow (P < 0.05 and P = 0.04, respectively; baseline median SUVmean, 5.01; IQR, 4.48-5.49; block median SUVmean, 1.57; IQR, 0.95-1.85) and spleen (median SUVmean, 2.14; IQR, 1.19-2.36) was also high in all pigs. Conclusion: 11C-GW457427 binds to NE in a porcine model of oleic acid-induced lung inflammation in vivo, with a specific increase in regional lung, bone marrow, and spleen SUV. 11C-GW457427 is a promising tool for localizing, tracking, and quantifying neutrophil-facilitated inflammation in clinical diagnostics and drug development.

PET-CT imaging of pulmonary inflammation using [68Ga]Ga-DOTA-TATE.

PURPOSE: In the characterization of severe lung diseases, early detection of specific inflammatory cells could help to monitor patients' response to therapy and increase chances of survival. Macrophages contribute to regulating the resolution and termination of inflammation and have increasingly been of interest for targeted therapies. [68Ga]Ga-DOTA-TATE is an established clinical radiopharmaceutical targeting somatostatin receptor subtype 2 (SSTR 2). Since activated macrophages (M1) overexpress SSTR 2, the aim of this study was to investigate the applicability of [68Ga]Ga-DOTA-TATE for positron emission tomography (PET) imaging of M1 macrophages in pulmonary inflammation. METHODS: Inflammation in the pig lungs was induced by warm saline lavage followed by injurious ventilation in farm pigs (n = 7). Healthy pigs (n = 3) were used as control. A 60-min dynamic PET scan over the lungs was performed after [68Ga]Ga-DOTA-TATE injection and [18F]FDG scan was executed afterward for comparison. The uptake of both tracers was assessed as mean standardized uptake values (SUVmean) 30-60-min post-injection. The PET scans were followed by computed tomography (CT) scans, and the Hounsfield units (HU) were quantified of the coronal segments. Basal and apical segments of the lungs were harvested for histology staining. A rat lung inflammation model was also studied for tracer specificity using lipopolysaccharides (LPS) by oropharyngeal aspiration. Organ biodistribution, ex vivo autoradiography (ARG) and histology samples were conducted on LPS treated, octreotide induced blocking and control healthy rats. RESULTS: The accumulation of [68Ga]Ga-DOTA-TATE on pig lavage model was prominent in the more severely injured dorsal segments of the lungs (SUVmean = 0.91 ± 0.56), compared with control animals (SUVmean = 0.27 ± 0.16, p < 0.05). The tracer uptake corresponded to the damaged areas assessed by CT and histology and were in line with HU quantification. The [68Ga]Ga-DOTA-TATE uptake in LPS treated rat lungs could be blocked and was significantly higher compared with control group. CONCLUSION: The feasibility of the noninvasive assessment of tissue macrophages using [68Ga]Ga-DOTA-TATE/PET was demonstrated in both porcine and rat lung inflammation models. [68Ga]Ga-DOTA-TATE has a great potential to be used to study the role and presence of macrophages in humans in fight against severe lung diseases.

Quantitative comparison of data-driven gating and external hardware gating for 18F-FDG PET-MRI in patients with esophageal tumors.

BACKGROUND: Respiratory motion during PET imaging reduces image quality. Data-driven gating (DDG) based on principal component analysis (PCA) can be used to identify respiratory signals. The use of DDG, without need for external devices, would greatly increase the feasibility of using respiratory gating in a routine clinical setting. The objective of this study was to evaluate data-driven gating in relation to external hardware gating and regular static image acquisition on PET-MRI data with respect to SUVmax and lesion volumes. METHODS: Sixteen patients with esophageal or gastroesophageal cancer (Siewert I and II) underwent a 6-min PET scan on a Signa PET-MRI system (GE Healthcare) 1.5-2 h after injection of 4 MBq/kg 18F-FDG. External hardware gating was done using a respiratory bellow device, and DDG was performed using MotionFree (GE Healthcare). The DDG raw data files and the external hardware-gating raw files were created on a Matlab-based toolbox from the whole 6-min scan LIST-file. For comparison, two 3-min static raw files were created for each patient. Images were reconstructed using TF-OSEM with resolution recovery with 2 iterations, 28 subsets, and 3-mm post filter. SUVmax and lesion volume were measured in all visible lesions, and noise level was measured in the liver. Paired t-test, linear regression, Pearson correlation, and Bland-Altman analysis were used to investigate difference, correlation, and agreement between the methods. RESULTS: A total number of 30 lesions were included in the study. No significant differences between DDG and external hardware-gating SUVmax or lesion volumes were found, but the noise level was significantly reduced in the DDG images. Both DDG and external hardware gating demonstrated significantly higher SUVmax (9.4% for DDG, 10.3% for external hardware gating) and smaller lesion volume (- 5.4% for DDG, - 6.6% for external gating) in comparison with non-gated static images. CONCLUSIONS: Data-driven gating with MotionFree for PET-MRI performed similar to external device gating for esophageal lesions with respect to SUVmax and lesion volume. Both gating methods significantly increased the SUVmax and reduced the lesion volume in comparison with non-gated static acquisition. DDG resulted in reduced image noise compared to external device gating and static images.

Prospective data-driven respiratory gating of [68Ga]Ga-DOTATOC PET/CT.

AIM: The aim of this prospective study was to evaluate a data-driven gating software's performance, in terms of identifying the respiratory signal, comparing [68Ga]Ga-DOTATOC and [18F]FDG examinations. In addition, for the [68Ga]Ga-DOTATOC examinations, tracer uptake quantitation and liver lesion detectability were assessed. METHODS: Twenty-four patients with confirmed or suspected neuroendocrine tumours underwent whole-body [68Ga]Ga-DOTATOC PET/CT examinations. Prospective DDG was applied on all bed positions and respiratory motion correction was triggered automatically when the detected respiratory signal exceeded a certain threshold (R value ≥ 15), at which point the scan time for that bed position was doubled. These bed positions were reconstructed with quiescent period gating (QPG), retaining 50% of the total coincidences. A respiratory signal evaluation regarding the software's efficacy in detecting respiratory motion for [68Ga]Ga-DOTATOC was conducted and compared to [18F]FDG data. Measurements of SUVmax, SUVmean, and tumour volume were performed on [68Ga]Ga-DOTATOC PET and compared between gated and non-gated images. RESULTS: The threshold of R ≥ 15 was exceeded and gating triggered on mean 2.1 bed positions per examination for [68Ga]Ga-DOTATOC as compared to 1.4 for [18F]FDG. In total, 34 tumours were evaluated in a quantitative analysis. An increase of 25.3% and 28.1%, respectively, for SUVmax (P < 0.0001) and SUVmean (P < 0.0001), and decrease of 21.1% in tumour volume (P < 0.0001) was found when DDG was applied. CONCLUSIONS: High respiratory signal was exclusively detected in bed positions where respiratory motion was expected, indicating reliable performance of the DDG software on [68Ga]Ga-DOTATOC PET/CT. DDG yielded significantly higher SUVmax and SUVmean values and smaller tumour volumes, as compared to non-gated images.