An automated computed tomography score for the cystic fibrosis lung.

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.