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An automated computed tomography score for the cystic fibrosis lung

  • Chest
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Abstract

Objectives

To develop an automated density-based computed tomography (CT) score evaluating high-attenuating lung structural abnormalities in patients with cystic fibrosis (CF).

Methods

Seventy adult CF patients were evaluated. The development cohort comprised 17 patients treated with ivacaftor, with 45 pre-therapeutic and follow-up chest CT scans. Another cohort of 53 patients not treated with ivacaftor was used for validation. CT-density scores were calculated using fixed and adapted thresholds based on histogram characteristics, such as the mode and standard deviation. Visual CF-CT score was also calculated. Correlations between the CT scores and forced expiratory volume in 1 s (FEV1% pred), and between their changes over time were assessed.

Results

On cross-sectional evaluation, the correlation coefficients between FEV1%pred and the automated scores were slightly lower to that of the visual score in the development and validation cohorts (R = up to -0.68 and -0.61, versus R = -0.72 and R = -0.64, respectively). Conversely, the correlation to FEV1%pred tended to be higher for automated scores (R = up to -0.61) than for visual score (R = -0.49) on longitudinal follow-up. Automated scores based on Mode + 3 SD and Mode +300 HU showed the highest cross-sectional (R = -0.59 to -0.68) and longitudinal (R = -0.51 to -0.61) correlation coefficients to FEV1%pred.

Conclusions

The developed CT-density score reliably quantifies high-attenuating lung structural abnormalities in CF.

Key Points

• Automated CT score shows moderate to good cross-sectional correlations with FEV 1 %pred .

• CT score has potential to be integrated into the standard reporting workflow

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Abbreviations

CF:

Cystic fibrosis

FEV1 :

Forced expiratory volume in 1 s

MLD:

Mean lung density

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Funding

This study has received funding by the patient association “Vaincre la Mucoviscidose”.

Author information

Authors and Affiliations

  1. Radiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France

    Guillaume Chassagnon, Paul Legmann & Marie-Pierre Revel

  2. Centre for Visual Computing, Ecole Centrale Paris, Grande Voie des Vignes, 92290, Chatenay Malabry, France

    Guillaume Chassagnon, Nikos Paragios & Evangelia I. Zacharaki

  3. Pulmonary Department and Adult CF Centre, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France

    Clémence Martin, Pierre-Régis Burgel & Dominique Hubert

  4. Physiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France

    Isabelle Fajac

  5. Biostatistics and Epidemiology Department, Groupe Hospitalier Cochin-Hotel Dieu, Université Paris Descartes, 27 Rue du Faubourg Saint-Jacques, 75014, Paris, France

    Joel Coste

Authors
  1. Guillaume Chassagnon
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  2. Clémence Martin
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  3. Pierre-Régis Burgel
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  4. Dominique Hubert
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  5. Isabelle Fajac
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  6. Nikos Paragios
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  7. Evangelia I. Zacharaki
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  8. Paul Legmann
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  9. Joel Coste
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  10. Marie-Pierre Revel
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Corresponding author

Correspondence to Guillaume Chassagnon.

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Guarantor

The scientific guarantor of this publication is Marie-Pierre Revel

Conflict of interest

The authors of this manuscript declare relationships with the following companies:

• Pierre-Régis Burgel, Dominique Hubert and Isabelle Fajac have received personal fees from Vertex Pharmaceuticals, outside the submitted work.

• Guillaume Chassagnon and Marie-Pierre Revel have made a patent application for the image analysis method presented in this article.

The other authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

Joel Coste has significant statistical expertise.

Informed consent

The need for informed consent was waived, in accordance with French rules for retrospective studies

Ethical approval

The study was approved by the Paris Ile de France I ethics committee (ref 13.652).

Study subjects or cohorts overlap

The 17 study subjects of the development cohort have been previously reported in Chassagnon et al. [15].

Methodology

• retrospective

• observational

• multicentre study

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Chassagnon, G., Martin, C., Burgel, PR. et al. An automated computed tomography score for the cystic fibrosis lung. Eur Radiol 28, 5111–5120 (2018). https://doi.org/10.1007/s00330-018-5516-x

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  • DOI: https://doi.org/10.1007/s00330-018-5516-x

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