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Review
. 2019 Sep 4:14:2065-2079.
doi: 10.2147/COPD.S207363. eCollection 2019.

Assessing pulmonary hypertension in COPD. Is there a role for computed tomography?

Florence Coste #  1   2 , Ilyes Benlala #  1   2   3 , Gaël Dournes  1   2   3 , Pierre-Olivier Girodet  1   2   3 , François Laurent #  1   2   3 , Patrick Berger #  1   2   3
Affiliations
Review

Assessing pulmonary hypertension in COPD. Is there a role for computed tomography?

Florence Coste et al. Int J Chron Obstruct Pulmon Dis. .

Abstract

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity and mortality. Reference standard method to diagnose PH is right heart catheterization. Several non-invasive imaging techniques have been employed in the detection of PH. Among them, computed tomography (CT) is the most commonly used for phenotyping and detecting complications of COPD. Several CT findings have also been described in patients with severe PH. Nevertheless, CT analysis is currently based on visual findings which can lead to reproducibility failure. Therefore, there is a need for quantification in order to assess objective criteria. In this review, progresses in automated analyses of CT parameters and their values in predicting PH and COPD outcomes are presented.

Keywords: COPD; computed tomography; prediction; pulmonary hypertension.

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Conflict of interest statement

Professor Laurent reports personal fees from Boehringer-Ingelheim, Roche, and Chiesi, outside the submitted work. Professor Pierre-Olivier Girodet reports personal fees, non-financial support from Novartis, personal fees, non-financial support from Chiesi, personal fees, non-financial support from Boehringer-Ingelheim, personal fees, non-financial support from AstraZeneca, personal fees, non-financial support from ALK, outside the submitted work. Professor Patrick Berger reports grants from Novartis, personal fees, non-financial support from AstraZeneca, personal fees, non-financial support from Menarini, personal fees, non-financial support from Circassia, personal fees, non-financial support from Sanofi, personal fees from Teva, outside the submitted work; in addition, Prof Berger has a patent Geometric characterization of airways using MRI. 22605-FR pending. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Reconstructed chest CT scan in COPD patient. This image was acquired with high-spatial-frequency algorithm reconstruction using fully automated Pulmo3D software (Siemens, Munich, Germany). Low attenuation area (LAA%) was derived from the voxel frequency distribution histogram and represented the percentage of lung voxels less than −950 HU. In this COPD patient, LAA value was 23%. Abbreviations: COPD, chronic obstructive pulmonary disease; CT, computed tomography.
Figure 2
Figure 2
Bronchi segmentation. (A) Frontal view of a propagation algorithm to obtain a skeleton binary volume based on bi-thresholding. Arrow shows bronchi in which measurements were assessed. (B) Peripheral bronchus is designated (arrow) on a native transverse thin-section CT. (C) Thin-section CT scan used to obtain measurements. (D) A Laplacian of Gaussian algorithm was assessed to segment the designed airway and measure bronchial thickness. Abbreviation: CT, computed tomography.
Figure 3
Figure 3
Pulmonary artery and aorta measurements. Ratio measurement obtained in a COPD patient in a transverse CT section. Abbreviations: COPD, chronic obstructive pulmonary disease; CT, computed tomography.
Figure 4
Figure 4
Measurement of cross-sectional areas (CSA) of small pulmonary vessels using Image J free-software. (A) CT image segmented within the threshold values from −500 to −1024 HU of lung field. (B) Segmented image segmented into binary images. (C) Mask image for the particle analysis after setting circularity within [0.9–1.0] and vessel size within [0–5] mm2. Abbreviation: CT, computed tomography.
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References

    1. From the Global Strategy for the Diagnosis, Management and Prevention of COPD, Global Initiative for Chronic Obstructive Lung Disease (GOLD); 2018. Available from: http://www.goldcopd.org/. Accessed July31, 2009.
    1. From the Global Strategy for the Diagnosis, Management and Prevention of COPD, Global Initiative for Chronic Obstructive Lung Disease (GOLD); 2017. Available from: https://goldcopd.org. Accessed July31, 2009.
    1. Galie N, Humbert M, Vachiery JL, et al. 2015 ESC/ERS guidelines for the diagnosis and treatment of pulmonary hypertension. Rev Esp Cardiol. 2016;69(2):177. doi:10.1016/j.recesp.2016.01.002 - DOI - PubMed
    1. Galie N, Humbert M, Vachiery JL, et al. 2015 ESC/ERS guidelines for the diagnosis and treatment of pulmonary hypertension: the joint task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): endorsed by: association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J. 2016;37(1):67–119. doi:10.1093/eurheartj/ehv317 - DOI - PubMed
    1. Seeger W, Adir Y, Barbera JA, et al. Pulmonary hypertension in chronic lung diseases. J Am Coll Cardiol. 2013;62(25 Suppl):D109–D116. doi:10.1016/j.jacc.2013.10.036 - DOI - PubMed

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