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Leek F, Anderson C, Robinson AP, Moss RM, Porter JC, Garthwaite HS, Groves AM, Hutton BF, Thielemans K. Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch. EJNMMI Phys 2023; 10:77. [PMID: 38049611 PMCID: PMC10695904 DOI: 10.1186/s40658-023-00595-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/20/2023] [Indexed: 12/06/2023] Open
Abstract
BACKGROUND Increased pulmonary [Formula: see text]F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image. METHODS Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, [Formula: see text]; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), [Formula: see text]; iii) smoothing the GT image to match the reconstruction within the VOI, [Formula: see text]. The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, [Formula: see text] was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols. RESULTS The simulations demonstrated that at [Formula: see text] iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The [Formula: see text] method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at [Formula: see text]200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10% at [Formula: see text]200i, while larger lung RMSEs were observed for the VOI-specific kernels. The global kernel approach was then employed with the [Formula: see text] method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated. CONCLUSIONS Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The [Formula: see text] method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners.
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Affiliation(s)
- Francesca Leek
- Institute of Nuclear Medicine, University College London Hospitals NHS Trust, London, UK.
- Nuclear Medicine Metrology, National Physical Laboratory, Teddington, UK.
| | - Cameron Anderson
- Institute of Nuclear Medicine, University College London Hospitals NHS Trust, London, UK
| | - Andrew P Robinson
- Nuclear Medicine Metrology, National Physical Laboratory, Teddington, UK
- Christie Medical Physics and Engineering, The Christie NHS Foundation Trust, Manchester, UK
- Schuster Laboratory, School of Physics and Astronomy, University of Manchester, Manchester, UK
| | - Robert M Moss
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Joanna C Porter
- UCL Respiratory, University College London and Interstitial Lung Disease Service, University College London Hospitals NHS Trust, London, UK
| | - Helen S Garthwaite
- UCL Respiratory, University College London and Interstitial Lung Disease Service, University College London Hospitals NHS Trust, London, UK
| | - Ashley M Groves
- Institute of Nuclear Medicine, University College London Hospitals NHS Trust, London, UK
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London Hospitals NHS Trust, London, UK
| | - Kris Thielemans
- Institute of Nuclear Medicine, University College London Hospitals NHS Trust, London, UK
- Centre for Medical Image Computing, University College London, London, UK
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2
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Gulhane AV, Chen DL. Overview of positron emission tomography in functional imaging of the lungs for diffuse lung diseases. Br J Radiol 2022; 95:20210824. [PMID: 34752146 PMCID: PMC9153708 DOI: 10.1259/bjr.20210824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Positron emission tomography (PET) is a quantitative molecular imaging modality increasingly used to study pulmonary disease processes and drug effects on those processes. The wide range of drugs and other entities that can be radiolabeled to study molecularly targeted processes is a major strength of PET, thus providing a noninvasive approach for obtaining molecular phenotyping information. The use of PET to monitor disease progression and treatment outcomes in DLD has been limited in clinical practice, with most of such applications occurring in the context of research investigations under clinical trials. Given the high costs and failure rates for lung drug development efforts, molecular imaging lung biomarkers are needed not only to aid these efforts but also to improve clinical characterization of these diseases beyond canonical anatomic classifications based on computed tomography. The purpose of this review article is to provide an overview of PET applications in characterizing lung disease, focusing on novel tracers that are in clinical development for DLD molecular phenotyping, and briefly address considerations for accurately quantifying lung PET signals.
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Affiliation(s)
- Avanti V Gulhane
- Department of Radiology, University of Washington School of Medicine, Seattle, United States
| | - Delphine L Chen
- Department of Radiology, University of Washington School of Medicine, Seattle, United States
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3
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Brusaferri L, Emond EC, Bousse A, Twyman R, Whitehead AC, Atkinson D, Ourselin S, Hutton BF, Arridge S, Thielemans K. Detection Efficiency Modeling and Joint Activity and Attenuation Reconstruction in Non-TOF 3-D PET From Multiple-Energy Window Data. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2022. [DOI: 10.1109/trpms.2021.3064239] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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4
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Chen DL, Ballout S, Chen L, Cheriyan J, Choudhury G, Denis-Bacelar AM, Emond E, Erlandsson K, Fisk M, Fraioli F, Groves AM, Gunn RN, Hatazawa J, Holman BF, Hutton BF, Iida H, Lee S, MacNee W, Matsunaga K, Mohan D, Parr D, Rashidnasab A, Rizzo G, Subramanian D, Tal-Singer R, Thielemans K, Tregay N, van Beek EJR, Vass L, Vidal Melo MF, Wellen JW, Wilkinson I, Wilson FJ, Winkler T. Consensus Recommendations on the Use of 18F-FDG PET/CT in Lung Disease. J Nucl Med 2020; 61:1701-1707. [PMID: 32948678 PMCID: PMC9364897 DOI: 10.2967/jnumed.120.244780] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 09/09/2020] [Indexed: 01/04/2023] Open
Abstract
PET with 18F-FDG has been increasingly applied, predominantly in the research setting, to study drug effects and pulmonary biology and to monitor disease progression and treatment outcomes in lung diseases that interfere with gas exchange through alterations of the pulmonary parenchyma, airways, or vasculature. To date, however, there are no widely accepted standard acquisition protocols or imaging data analysis methods for pulmonary 18F-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, we collated details of acquisition protocols and analysis methods from 7 PET centers. From this information and our discussions, we reached the consensus recommendations given here on patient preparation, choice of dynamic versus static imaging, image reconstruction, and image analysis reporting.
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Affiliation(s)
- Delphine L Chen
- Department of Radiology, University of Washington, Seattle Cancer Care Alliance, Seattle, Washington
| | - Safia Ballout
- School of Physics and Astronomy, University of Leeds, Leeds, United Kingdom
| | - Laigao Chen
- Worldwide Research, Development, and Medical, Pfizer Inc., Cambridge, Massachusetts
| | - Joseph Cheriyan
- Cambridge University Hospitals, NHS Foundation Trust, Cambridge, United Kingdom
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Gourab Choudhury
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Elise Emond
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Kjell Erlandsson
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Marie Fisk
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Ashley M Groves
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Roger N Gunn
- inviCRO, London, United Kingdom
- Department of Medicine, Imperial College London, London, United Kingdom
| | - Jun Hatazawa
- Department of Nuclear Medicine and Tracer Kinetics, Osaka University, Osaka, Japan
| | - Beverley F Holman
- Nuclear Medicine Department, Royal Free Hospital, London, United Kingdom
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Hidehiro Iida
- Faculty of Biomedicine and Turku PET Center, University of Turku, Turku, Finland
| | - Sarah Lee
- Amallis Consulting Ltd., London, United Kingdom
| | - William MacNee
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Keiko Matsunaga
- Department of Nuclear Medicine and Tracer Kinetics, Osaka University, Osaka, Japan
| | - Divya Mohan
- Medical Innovation, Value Evidence, and Outcomes, GlaxoSmithKline R&D, Collegeville, Pennsylvania
| | - David Parr
- University Hospitals Coventry and Warwickshire, Coventry, United Kingdom
| | - Alaleh Rashidnasab
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Gaia Rizzo
- inviCRO, London, United Kingdom
- Department of Medicine, Imperial College London, London, United Kingdom
| | | | - Ruth Tal-Singer
- Medical Innovation, Value Evidence, and Outcomes, GlaxoSmithKline R&D, Collegeville, Pennsylvania
| | - Kris Thielemans
- Institute of Nuclear Medicine, University College London, London, United Kingdom
| | - Nicola Tregay
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Edwin J R van Beek
- Edinburgh Imaging, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Laurence Vass
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Marcos F Vidal Melo
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Jeremy W Wellen
- Research and Early Development, Celgene, Cambridge, Massachusetts; and
| | - Ian Wilkinson
- Cambridge University Hospitals, NHS Foundation Trust, Cambridge, United Kingdom
- Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Frederick J Wilson
- Clinical Imaging, Clinical Pharmacology, and Experimental Medicine, GlaxoSmithKline, Stevenage, United Kingdom
| | - Tilo Winkler
- Department of Anesthesia, Critical Care, and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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5
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Emond EC, Bousse A, Brusaferri L, Hutton BF, Thielemans K. Improved PET/CT Respiratory Motion Compensation by Incorporating Changes in Lung Density. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2020. [DOI: 10.1109/trpms.2020.3001094] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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6
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Emond EC, Bousse A, Machado M, Porter J, Groves AM, Hutton BF, Thielemans K. Effect of attenuation mismatches in time of flight PET reconstruction. Phys Med Biol 2020; 65:085009. [PMID: 32101801 DOI: 10.1088/1361-6560/ab7a6f] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
While the pursuit of better time resolution in positron emission tomography (PET) is rapidly evolving, little work has been performed on time of flight (TOF) image quality at high time resolution in the presence of modelling inconsistencies. This works focuses on the effect of using the wrong attenuation map in the system model, causing perturbations in the reconstructed radioactivity image. Previous work has usually considered the effects to be local to the area where there is attenuation mismatch, and has shown that the quantification errors in this area tend to reduce with improved time resolution. This publication shows however that errors in the PET image at a distance from the mismatch increase with time resolution. The errors depend on the reconstruction algorithm used. We quantify the errors in the hypothetical case of perfect time resolution for maximum likelihood reconstructions. In addition, we perform reconstructions on simulated and patient data. In particular, for respiratory-gated reconstructions from a wrong attenuation map, increased errors are observed with improved time resolutions in areas close to the lungs (e.g. from 13.3% in non-TOF to up to 20.9% at 200 ps in the left ventricle).
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Affiliation(s)
- Elise C Emond
- Institute of Nuclear Medicine, University College London, London NW1 2BU, United Kingdom
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7
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Mokri S, Saripan M, Nordin A, Marhaban M, Abd Rahni A. Thoracic hybrid PET/CT registration using improved hybrid feature intensity multimodal demon. Radiat Phys Chem Oxf Engl 1993 2020. [DOI: 10.1016/j.radphyschem.2019.04.030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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8
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Holman BF, Cuplov V, Millner L, Endozo R, Maher TM, Groves AM, Hutton BF, Thielemans K. Improved quantitation and reproducibility in multi-PET/CT lung studies by combining CT information. EJNMMI Phys 2018; 5:14. [PMID: 29869186 PMCID: PMC5986691 DOI: 10.1186/s40658-018-0212-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 04/09/2018] [Indexed: 02/06/2023] Open
Abstract
Background Matched attenuation maps are vital for obtaining accurate and reproducible kinetic and static parameter estimates from PET data. With increased interest in PET/CT imaging of diffuse lung diseases for assessing disease progression and treatment effectiveness, understanding the extent of the effect of respiratory motion and establishing methods for correction are becoming more important. In a previous study, we have shown that using the wrong attenuation map leads to large errors due to density mismatches in the lung, especially in dynamic PET scans. Here, we extend this work to the case where the study is sub-divided into several scans, e.g. for patient comfort, each with its own CT (cine-CT and ‘snap shot’ CT). A method to combine multi-CT information into a combined-CT has then been developed, which averages the CT information from each study section to produce composite CT images with the lung density more representative of that in the PET data. This combined-CT was applied to nine patients with idiopathic pulmonary fibrosis, imaged with dynamic 18F-FDG PET/CT to determine the improvement in the precision of the parameter estimates. Results Using XCAT simulations, errors in the influx rate constant were found to be as high as 60% in multi-PET/CT studies. Analysis of patient data identified displacements between study sections in the time activity curves, which led to an average standard error in the estimates of the influx rate constant of 53% with conventional methods. This reduced to within 5% after use of combined-CTs for attenuation correction of the study sections. Conclusions Use of combined-CTs to reconstruct the sections of a multi-PET/CT study, as opposed to using the individually acquired CTs at each study stage, produces more precise parameter estimates and may improve discrimination between diseased and normal lung.
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Affiliation(s)
- Beverley F Holman
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK.
| | - Vesna Cuplov
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK
| | - Lynn Millner
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK
| | - Raymond Endozo
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK
| | - Toby M Maher
- National Institute for Health Research Respiratory Biomedical Research Unit, Royal Brompton Hospital, Sydney St, London, SW3 6NP, UK.,Fibrosis Research Group, Inflammation, Repair and Development Section, NHLI, Sir Alexander Flemming Building, Imperial College London, London, SW7 2AZ, UK
| | - Ashley M Groves
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK.,Centre for Medical Radiation Physics, University of Wollongong, Wollongong, Australia
| | - Kris Thielemans
- Institute of Nuclear Medicine, University College London, UCLH (T-5), Euston Road, London, NW1 2BU, UK
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9
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Volpi S, Ali JM, Tasker A, Peryt A, Aresu G, Coonar AS. The role of positron emission tomography in the diagnosis, staging and response assessment of non-small cell lung cancer. ANNALS OF TRANSLATIONAL MEDICINE 2018; 6:95. [PMID: 29666818 DOI: 10.21037/atm.2018.01.25] [Citation(s) in RCA: 50] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Lung cancer is a common disease and the leading cause of cancer-related mortality, with non-small cell lung cancer (NSCLC) accounting for the majority of cases. Following diagnosis of lung cancer, accurate staging is essential to guide clinical management and inform prognosis. Positron emission tomography (PET) in conjunction with computed tomography (CT)-as PET-CT has developed as an important tool in the multi-disciplinary management of lung cancer. This article will review the current evidence for the role of 18F-fluorodeoxyglucose (FDG) PET-CT in NSCLC diagnosis, staging, response assessment and follow up.
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Affiliation(s)
- Sara Volpi
- Department of Thoracic Surgery, Papworth Hospital, Cambridge, UK
| | - Jason M Ali
- Department of Thoracic Surgery, Papworth Hospital, Cambridge, UK
| | - Angela Tasker
- Department of Radiology, Papworth Hospital, Cambridge, UK
| | - Adam Peryt
- Department of Thoracic Surgery, Papworth Hospital, Cambridge, UK
| | - Giuseppe Aresu
- Department of Thoracic Surgery, Papworth Hospital, Cambridge, UK
| | - Aman S Coonar
- Department of Thoracic Surgery, Papworth Hospital, Cambridge, UK
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10
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Frood R, McDermott G, Scarsbrook A. Respiratory-gated PET/CT for pulmonary lesion characterisation-promises and problems. Br J Radiol 2018; 91:20170640. [PMID: 29338327 DOI: 10.1259/bjr.20170640] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
2-deoxy-2-(18Fluorine)-fluoro-D-glucose (FDG) PET/CT is an integral part of lung carcinoma staging and frequently used in the assessment of solitary pulmonary nodules. However, a limitation of conventional three-dimensional PET/CT when imaging the thorax is its susceptibility to motion artefact, which blurs the signal from the lesion resulting in inaccurate representation of size and metabolic activity. Respiratory gated (four-dimensional) PET/CT aims to negate the effects of motion artefact and provide a more accurate interpretation of pulmonary nodules and lymphadenopathy. There have been recent advances in technology and a shift from traditional hardware to more streamlined software methods for respiratory gating which should allow more widespread use of respiratory-gating in the future. The purpose of this article is to review the evidence surrounding four-dimensional PET/CT in pulmonary lesion characterisation.
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Affiliation(s)
- Russell Frood
- 1 Department of Nuclear Medicine, Leeds Teaching Hospitals NHS Trust , Leeds , United Kingdom
| | - Garry McDermott
- 2 Department of Medical Physics & Engineering, Leeds Teaching Hospitals NHS Trust , Leeds , United Kingdom
| | - Andrew Scarsbrook
- 1 Department of Nuclear Medicine, Leeds Teaching Hospitals NHS Trust , Leeds , United Kingdom.,3 Leeds Institute of Cancer and Pathology, University of Leeds , Leeds , United Kingdom
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11
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Coello C, Fisk M, Mohan D, Wilson FJ, Brown AP, Polkey MI, Wilkinson I, Tal-Singer R, Murphy PS, Cheriyan J, Gunn RN. Quantitative analysis of dynamic 18F-FDG PET/CT for measurement of lung inflammation. EJNMMI Res 2017; 7:47. [PMID: 28547129 PMCID: PMC5445063 DOI: 10.1186/s13550-017-0291-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2017] [Accepted: 05/09/2017] [Indexed: 11/23/2022] Open
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. Electronic supplementary material The online version of this article (doi:10.1186/s13550-017-0291-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Christopher Coello
- Imanova Ltd., Centre for Imaging Sciences, Hammersmith Hospital, London, UK. .,Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK.
| | - Marie Fisk
- Experimental Medicine and Immunotherapeutics (EMIT) Division, Department of Medicine, University of Cambridge, Cambridge, UK
| | - Divya Mohan
- NIHR Respiratory Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College, London, UK.,GSK R&D, King of Prussia, PA, USA
| | | | - Andrew P Brown
- Imanova Ltd., Centre for Imaging Sciences, Hammersmith Hospital, London, UK
| | - Michael I Polkey
- NIHR Respiratory Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College, London, UK
| | - Ian Wilkinson
- Experimental Medicine and Immunotherapeutics (EMIT) Division, Department of Medicine, University of Cambridge, Cambridge, UK.,Cambridge Clinical Trials Unit, Addenbrooke's Hospital, Cambridge, UK
| | | | | | - Joseph Cheriyan
- Experimental Medicine and Immunotherapeutics (EMIT) Division, Department of Medicine, University of Cambridge, Cambridge, UK.,GSK R&D, Cambridge, UK.,Cambridge Clinical Trials Unit, Addenbrooke's Hospital, Cambridge, UK.,Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
| | - Roger N Gunn
- Imanova Ltd., Centre for Imaging Sciences, Hammersmith Hospital, London, UK.,Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK.,Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
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