• Ilyes Benlala, Sophie Point, Cédric Leung, Patrick Berger, Jason C Woods, Chantal Raherison, François Laurent, Julie Macey, and Gaël Dournes.
• Univ. Bordeaux, F-33000, Bordeaux, France.
• Eur Radiol. 2020 Oct 1; 30 (10): 5479-5488.

ObjectivesThe 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).MethodsThis 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).ResultsA 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).ConclusionsAutomated quantification of abnormal signal intensity volumes relates to CF severity and allows reproducible cross-sectional and longitudinal assessment.Trial RegistrationClinical 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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