EPS4.3 Differential sensitivity of outcome measures that assess progression of mild CF lung disease in school age children

Robinson, Tamira; Goris, Marina; Moss, Richard B.; Tian, Liming; Kan, PG; Yilma, Mignote; McCoy, Karen; Jong, P.A. de; Long, Frederick R.; Brody, A.; Behrje, Rhett; Yates, Denise; Cornfield, D.N.

doi:10.1016/s1569-1993(17)30304-1

Cited by 3 publications

(1 citation statement)

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“…The prospective multi-center study was carried out in 36 subjects enrolled in the Novartis CF Natural History Study [ 28 ] from 2007–2011 and was approved by the Institutional Review Boards of Stanford University Medical Center and Ohio State University School of Medicine. Informed written consent for examination and further data processing was obtained from all patients or legal guardians prior to inclusion.…”

Section: Methodsmentioning

confidence: 99%

Validation of automated lobe segmentation on paired inspiratory-expiratory chest CT in 8-14 year-old children with cystic fibrosis

et al. 2018

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ObjectivesDensitometry on paired inspiratory and expiratory multidetector computed tomography (MDCT) for the quantification of air trapping is an important approach to assess functional changes in airways diseases such as cystic fibrosis (CF). For a regional analysis of functional deficits, an accurate lobe segmentation algorithm applicable to inspiratory and expiratory scans is beneficial.Materials and methodsWe developed a fully automated lobe segmentation algorithm, and subsequently validated automatically generated lobe masks (ALM) against manually corrected lobe masks (MLM). Paired inspiratory and expiratory CTs from 16 children with CF (mean age 11.1±2.4) acquired at 4 time-points (baseline, 3mon, 12mon, 24mon) with 2 kernels (B30f, B60f) were segmented, resulting in 256 ALM. After manual correction spatial overlap (Dice index) and mean differences in lung volume and air trapping were calculated for ALM vs. MLM.ResultsThe mean overlap calculated with Dice index between ALM and MLM was 0.98±0.02 on inspiratory, and 0.86±0.07 on expiratory CT. If 6 lobes were segmented (lingula treated as separate lobe), the mean overlap was 0.97±0.02 on inspiratory, and 0.83±0.08 on expiratory CT. The mean differences in lobar volumes calculated in accordance with the approach of Bland and Altman were generally low, ranging on inspiratory CT from 5.7±52.23cm3 for the right upper lobe to 17.41±14.92cm3 for the right lower lobe. Higher differences were noted on expiratory CT. The mean differences for air trapping were even lower, ranging from 0±0.01 for the right upper lobe to 0.03±0.03 for the left lower lobe.ConclusionsAutomatic lobe segmentation delivers excellent results for inspiratory and good results for expiratory CT. It may become an important component for lobe-based quantification of functional deficits in cystic fibrosis lung disease, reducing necessity for user-interaction in CT post-processing.

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Section: Methodsmentioning

confidence: 99%