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Volumetric quantification of lung MR signal intensities using ultrashort TE as an automated score in cystic fibrosis

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Abstract

Objectives

The study aimed to validate automated quantification of high and low signal intensity volumes using ultrashort echo-time MRI, with CT and pulmonary function test (PFT) as references, to assess the severity of structural alterations in cystic fibrosis (CF).

Methods

This prospective study was performed in a single center between May 2015 and September 2017. Participants with CF completed clinical examination, CT, MRI, and PFT the same day during routine clinical follow-up (M0), and then 1 year after (M12) except for CT. Using MRI, percentage high (%MR-HSV), low (%MR-LSV), and total abnormal (%MR-TSV) signal intensity volumes were recorded, as well as their corresponding attenuation values using CT (%CT-HAV, %CT-LAV, %CT-TAV, respectively). Automated quantifications and visual Bhalla score were evaluated independently by two observers. Correlations were assessed using the Spearman test, comparisons using the Mann-Whitney test, and reproducibility using the intraclass correlation coefficient (ICC).

Results

A total of 30 participants were enrolled (median age 27 years, 18 men). At M0, there was a good correlation between %MR-HSV and %CT-HAV (ρ = 0.70; p < 0.001) and %MR-LSV and %CT-LAV (ρ = 0.60; p < 0.001). Automated MR metrics correlated to PFTs and Bhalla score (p < 0.05) while %MR-TSV was significantly different between CF with and without respiratory exacerbation (p = 0.01) at both M0 and M12. The variation of %MR-HSV correlated to the variation of FEV1% at PFT (ρ = − 0.49; p = 0.008). Reproducibility was almost perfect (ICCs > 0.95).

Conclusions

Automated quantification of abnormal signal intensity volumes relates to CF severity and allows reproducible cross-sectional and longitudinal assessment.

Trial registration

Clinical trial identifier: NCT02449785

Key Points

• Cross-sectionally, the automated quantifications of high and low signal intensity volumes at UTE correlated to the quantification of high and low attenuation using CT as reference.

• Longitudinally, the variation of high signal intensity volume at UTE correlated to the variation of pulmonary function test and was significantly reduced in CF with an improvement in exacerbation status.

• Automated quantification of abnormal signal intensity volumes are objective and reproducible tools to assess structural alterations in CF and follow-up longitudinally, for both research and clinical purposes.

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Abbreviations

%CT-HAV:

Percentage high attenuation volume

%CT-LAV:

Percentage low attenuation volume

%CT-TAV:

Percentage total abnormal attenuation volume

%MR-HSV:

Percentage high signal intensity volume

%MR-LSV:

Percentage low signal intensity volume

%MR-TSV:

Percentage total abnormal signal intensity volume

3D-UTE:

Three-dimensional high-resolution morphology using ultrashort echo-times

CF:

Cystic fibrosis

PFT:

Pulmonary function test

SD:

Standard deviation

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Acknowledgments

The study was achieved within the context of Laboratory of Excellence TRAIL ANR-10-LABX-57, and the authors would like to thank Dr. Wadie Benhassen, PhD, for technical support.

Funding

Gael Dournes received academic funding from the French Society of Radiology (Grant Alain Rahmouni SFR-CERF 2019) and IdeX Bordeaux (ANR-10-IDEX-03-02). Ilyes Benlala received academic funding from the Foundation Le Nouveau Souffle (AAP2018). Julie Macey received academic funding from the University Hospital of Bordeaux.

Author information

Author notes

  1. Julie Macey and Gaël Dournes contributed equally to this work.

Authors and Affiliations

  1. Univ. Bordeaux, F-33000, Bordeaux, France

    Ilyes Benlala, Patrick Berger, François Laurent & Gaël Dournes

  2. Inserm, Centre de Recherche Cardio-Thoracique de Bordeaux, U1045, CIC 1401, F-33000, Bordeaux, France

    Ilyes Benlala, Patrick Berger, François Laurent & Gaël Dournes

  3. Service d’Imagerie Thoracique et Cardiovasculaire, Service des Maladies Respiratoires, Service d’Exploration Fonctionnelle Respiratoire, University Hospital of Bordeaux, CIC 1401, F-33600, Pessac, France

    Ilyes Benlala, Sophie Point, Cédric Leung, Patrick Berger, Chantal Raherison, François Laurent, Julie Macey & Gaël Dournes

  4. Center for Pulmonary Imaging Research, Cincinnati Children Hospital Medical Center, Cincinnati, Ohio, USA

    Jason C. Woods

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  1. Ilyes Benlala
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Corresponding author

Correspondence to Gaël Dournes.

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Guarantor

The scientific guarantor of the study is Dr. Gael Dournes.

Conflict of interest

The 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

Pr Patrick Berger has significant statistical expertise.

Informed consent

Written consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Prospective

• Cross sectional study

• Performed at one institution

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Benlala, I., Point, S., Leung, C. et al. Volumetric quantification of lung MR signal intensities using ultrashort TE as an automated score in cystic fibrosis. Eur Radiol 30, 5479–5488 (2020). https://doi.org/10.1007/s00330-020-06910-w

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