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Published in: European Journal of Nuclear Medicine and Molecular Imaging 10/2019

Open Access 01-09-2019 | Idiopathic Pulmonary Fibrosis | Original Article

Synergistic application of pulmonary 18F-FDG PET/HRCT and computer-based CT analysis with conventional severity measures to refine current risk stratification in idiopathic pulmonary fibrosis (IPF)

Authors: Francesco Fraioli, Maria Lyasheva, Joanna C. Porter, Jamshed Bomanji, Robert I. Shortman, Raymond Endozo, Simon Wan, Linda Bertoletti, Maria Machado, Balaji Ganeshan, Thida Win, Ashley M. Groves

Published in: European Journal of Nuclear Medicine and Molecular Imaging | Issue 10/2019

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Abstract

Introduction

To investigate the combined performance of quantitative CT (qCT) following a computer algorithm analysis (IMBIO) and 18F-FDG PET/CT to assess survival in patients with idiopathic pulmonary fibrosis (IPF).

Methods

A total of 113 IPF patients (age 70 ± 9 years) prospectively and consecutively underwent 18F-FDG PET/CT and high-resolution CT (HRCT) at our institution. During a mean follow-up of 29.6 ± 26 months, 44 (48%) patients died. As part of the qCT analysis, pattern evaluation of HRCT (using IMBIO software) included the total extent (percentage) of the following features: normal-appearing lung, hyperlucent lung, parenchymal damage (comprising ground-glass opacification, reticular pattern and honeycombing), and the pulmonary vessels. The maximum (SUVmax) and minimum (SUVmin) standardized uptake value (SUV) for 18F-FDG uptake in the lungs, and the target-to-background (SUVmax/SUVmin) ratio (TBR) were quantified using routine region-of-interest (ROI) analysis. Pulmonary functional tests (PFTs) were acquired within 14 days of the PET/CT/HRCT scan. Kaplan–Meier (KM) survival analysis was used to identify associations with mortality.

Results

Data from 91 patients were available for comparative analysis. The average ± SD GAP [gender, age, physiology] score was 4.2 ± 1.7 (range 0–8). The average ± SD SUVmax, SUVmin, and TBR were 3.4 ± 1.4, 0.7 ± 0.2, and 5.6 ± 2.8, respectively. In all patients, qCT analysis demonstrated a predominantly reticular lung pattern (14.9 ± 12.4%). KM analysis showed that TBR (p = 0.018) and parenchymal damage assessed by qCT (p = 0.0002) were the best predictors of survival. Adding TBR and qCT to the GAP score significantly increased the ability to differentiate between high and low risk (p < 0.0001).

Conclusion

18F-FDG PET and qCT are independent and synergistic in predicting mortality in patients with IPF.
Literature
1.
go back to reference Lynch DA, David GJ, Safrin S, et al. High-resolution computed tomography in idiopathic pulmonary fibrosis: diagnosis and prognosis. Am J Respir Crit Care Med. 2005;172:488–93.CrossRef Lynch DA, David GJ, Safrin S, et al. High-resolution computed tomography in idiopathic pulmonary fibrosis: diagnosis and prognosis. Am J Respir Crit Care Med. 2005;172:488–93.CrossRef
2.
go back to reference Watadani T, Sakai F, Johkoh T, et al. Interobserver variability in the CT assessment of honeycombing in the lungs. Radiology. 2013;266:936–44.CrossRefPubMed Watadani T, Sakai F, Johkoh T, et al. Interobserver variability in the CT assessment of honeycombing in the lungs. Radiology. 2013;266:936–44.CrossRefPubMed
3.
go back to reference Wu X, Kim GH, Salisbury ML, Barber D, et al. Computed tomographic biomarkers in idiopathic pulmonary fibrosis. The future of quantitative analysis. Am J Respir Crit Care Med. 2019;199:12–21.CrossRef Wu X, Kim GH, Salisbury ML, Barber D, et al. Computed tomographic biomarkers in idiopathic pulmonary fibrosis. The future of quantitative analysis. Am J Respir Crit Care Med. 2019;199:12–21.CrossRef
4.
go back to reference Spagnolo P, Maher TM. Clinical trial research in focus: why do so many clinical trials fail in IPF? Lancet Respir Med. 2017;5:372–4.CrossRefPubMed Spagnolo P, Maher TM. Clinical trial research in focus: why do so many clinical trials fail in IPF? Lancet Respir Med. 2017;5:372–4.CrossRefPubMed
5.
go back to reference Jones HA, Cadwallader KA, White JF, Uddin M, Peters AM, Chilvers ER. Dissociation between respiratory burst activity and deoxyglucose uptake in human neutrophil granulocytes: implications for interpretation of 18F-FDG PET images. J Nucl Med. 2002;43:652–7.PubMed Jones HA, Cadwallader KA, White JF, Uddin M, Peters AM, Chilvers ER. Dissociation between respiratory burst activity and deoxyglucose uptake in human neutrophil granulocytes: implications for interpretation of 18F-FDG PET images. J Nucl Med. 2002;43:652–7.PubMed
6.
go back to reference Wallace WE, Gupta NC, Hubbs AF, Mazza SM, Bishop HA, Keane MJ, et al. Cis-4-[18F]fluoro-L-proline PET imaging of pulmonary fibrosis in a rabbit model. J Nucl Med. 2002;43:413–20.PubMed Wallace WE, Gupta NC, Hubbs AF, Mazza SM, Bishop HA, Keane MJ, et al. Cis-4-[18F]fluoro-L-proline PET imaging of pulmonary fibrosis in a rabbit model. J Nucl Med. 2002;43:413–20.PubMed
7.
go back to reference Groves AM, Win T, Screaton NJ, Berovic M, Endozo R, Booth H, et al. Idiopathic pulmonary fibrosis and diffuse parenchymal lung disease: implications from initial experience with 18F-FDG PET/CT. J Nucl Med. 2009;50:538–45.CrossRefPubMed Groves AM, Win T, Screaton NJ, Berovic M, Endozo R, Booth H, et al. Idiopathic pulmonary fibrosis and diffuse parenchymal lung disease: implications from initial experience with 18F-FDG PET/CT. J Nucl Med. 2009;50:538–45.CrossRefPubMed
8.
go back to reference Win T, Screaton NJ, Porter JC, Ganeshan B, et al. Pulmonary (18)F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF). Eur J Nucl Med Mol Imaging. 2018;45(5):806–15.CrossRefPubMedPubMedCentral Win T, Screaton NJ, Porter JC, Ganeshan B, et al. Pulmonary (18)F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF). Eur J Nucl Med Mol Imaging. 2018;45(5):806–15.CrossRefPubMedPubMedCentral
9.
go back to reference Ley B, Collard HR, King TE Jr. Clinical course and prediction of survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2011;183(4):431–40.CrossRef Ley B, Collard HR, King TE Jr. Clinical course and prediction of survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med. 2011;183(4):431–40.CrossRef
10.
go back to reference Ley B, Ryerson CJ, Vittinghoff E, Ryu JH, Tomassetti S, Lee JS, et al. A multidimensional index and staging system for idiopathic pulmonary fibrosis. Ann Intern Med. 2012;15:684–91.CrossRef Ley B, Ryerson CJ, Vittinghoff E, Ryu JH, Tomassetti S, Lee JS, et al. A multidimensional index and staging system for idiopathic pulmonary fibrosis. Ann Intern Med. 2012;15:684–91.CrossRef
11.
go back to reference Chen DL, Schuster DP. Imaging pulmonary inflammation with positron emission tomography: a biomarker for drug development. Mol Pharm. 2006;3:488–95.CrossRefPubMed Chen DL, Schuster DP. Imaging pulmonary inflammation with positron emission tomography: a biomarker for drug development. Mol Pharm. 2006;3:488–95.CrossRefPubMed
12.
go back to reference Jacob J, Hirani N, van Moorsel CHM, Rajagopalan S, Murchison JT, et al. Predicting outcomes in rheumatoid arthritis related interstitial lung disease. Eur Respir J. 2019;53. Jacob J, Hirani N, van Moorsel CHM, Rajagopalan S, Murchison JT, et al. Predicting outcomes in rheumatoid arthritis related interstitial lung disease. Eur Respir J. 2019;53.
13.
go back to reference Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, Nair A, Karwoski R, Walsh SL, Wells AU, Hansell DM. Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures. Eur Respir J. 2017;49. Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, Nair A, Karwoski R, Walsh SL, Wells AU, Hansell DM. Mortality prediction in idiopathic pulmonary fibrosis: evaluation of computer-based CT analysis with conventional severity measures. Eur Respir J. 2017;49.
14.
go back to reference Jacob J, Nicholson AG, Wells AU, Hansell DM. Impact of pulmonary vascular volume on mortality in IPF: is it time to reconsider the role of vasculature in disease pathogenesis and progression? Eur Respir J. 2017;49(2). Jacob J, Nicholson AG, Wells AU, Hansell DM. Impact of pulmonary vascular volume on mortality in IPF: is it time to reconsider the role of vasculature in disease pathogenesis and progression? Eur Respir J. 2017;49(2).
15.
go back to reference Puxeddu E, Cavalli F, Pezzuto G, et al. Impact of pulmonary vascular volume on mortality in IPF: is it time to reconsider the role of vasculature in disease pathogenesis and progression? Eur Respir J. 2017;49:1602345.CrossRefPubMed Puxeddu E, Cavalli F, Pezzuto G, et al. Impact of pulmonary vascular volume on mortality in IPF: is it time to reconsider the role of vasculature in disease pathogenesis and progression? Eur Respir J. 2017;49:1602345.CrossRefPubMed
16.
go back to reference Win T, Thomas BA, Lambrou T, et al. Areas of normal pulmonary parenchyma on HRCT exhibit increased FDG PET signal in IPF patients. Eur J Nucl Med Mol Imaging. 2014;41:337–42.CrossRefPubMed Win T, Thomas BA, Lambrou T, et al. Areas of normal pulmonary parenchyma on HRCT exhibit increased FDG PET signal in IPF patients. Eur J Nucl Med Mol Imaging. 2014;41:337–42.CrossRefPubMed
17.
go back to reference McLoud TC. Role of high-resolution computed tomography in idiopathic pulmonary fibrosis: the final word? Am J Respir Crit Care Med. 2005;172:408–9.CrossRefPubMed McLoud TC. Role of high-resolution computed tomography in idiopathic pulmonary fibrosis: the final word? Am J Respir Crit Care Med. 2005;172:408–9.CrossRefPubMed
18.
go back to reference Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, et al. Automated quantitative computed tomography versus visual computed tomography scoring in idiopathic pulmonary fibrosis: validation against pulmonary function. J Thorac Imaging. 2016;31:304–11.CrossRefPubMed Jacob J, Bartholmai BJ, Rajagopalan S, Kokosi M, et al. Automated quantitative computed tomography versus visual computed tomography scoring in idiopathic pulmonary fibrosis: validation against pulmonary function. J Thorac Imaging. 2016;31:304–11.CrossRefPubMed
19.
20.
go back to reference Holman BF, Cuplov V, Millner L, Hutton BF, et al. Improved correction for the tissue fraction effect in lung PET/CT imaging. Phys Med Biol. 2015;60:7387–402.CrossRefPubMed Holman BF, Cuplov V, Millner L, Hutton BF, et al. Improved correction for the tissue fraction effect in lung PET/CT imaging. Phys Med Biol. 2015;60:7387–402.CrossRefPubMed
21.
go back to reference Ganeshan B, Miles KA, Young RC, Chatwin CR. Three-dimensional selective-scale texture analysis of computed tomography pulmonary angiograms. Investig Radiol. 2008;43:382–94.CrossRef Ganeshan B, Miles KA, Young RC, Chatwin CR. Three-dimensional selective-scale texture analysis of computed tomography pulmonary angiograms. Investig Radiol. 2008;43:382–94.CrossRef
Metadata
Title
Synergistic application of pulmonary 18F-FDG PET/HRCT and computer-based CT analysis with conventional severity measures to refine current risk stratification in idiopathic pulmonary fibrosis (IPF)
Authors
Francesco Fraioli
Maria Lyasheva
Joanna C. Porter
Jamshed Bomanji
Robert I. Shortman
Raymond Endozo
Simon Wan
Linda Bertoletti
Maria Machado
Balaji Ganeshan
Thida Win
Ashley M. Groves
Publication date
01-09-2019
Publisher
Springer Berlin Heidelberg
Published in
European Journal of Nuclear Medicine and Molecular Imaging / Issue 10/2019
Print ISSN: 1619-7070
Electronic ISSN: 1619-7089
DOI
https://doi.org/10.1007/s00259-019-04386-5

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