ArticlePloS one2020
Optimizing airway wall segmentation and quantification by reducing the influence of adjacent vessels and intravascular contrast material with a modified integral-based algorithm in quantitative computed tomography.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Airway segmentation on CT - A systematic review of machine learning tools.European journal of radiology open · 2026Article
- Quantitative spectral computed tomography detects different patterns of airway wall thickening and contrast enhancement in infective lung disease: a feasibility study.European radiology · 2025Article
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Authors and funding
9 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
introductionQuantitative analysis of multi-detector computed tomography (MDCT) plays an increasingly important role in assessing airway disease. Depending on the algorithms used, airway dimensions may be over- or underestimated, primarily if contrast material was used. Therefore, we tested a modified integral-based method (IBM) to address this problem.
methodsTemporally resolved cine-MDCT was performed in seven ventilated pigs in breath-hold during iodinated contrast material (CM) infusion over 60s. Identical slices in non-enhanced (NE), pulmonary-arterial (PA), systemic-arterial (SA), and venous phase (VE) were subjected to an in-house software using a standard and a modified IBM. Total diameter (TD), lumen area (LA), wall area (WA), and wall thickness (WT) were measured for ten extra- and six intrapulmonary airways.
resultsThe modified IBM significantly reduced TD by 7.6%, LA by 12.7%, WA by 9.7%, and WT by 3.9% compared to standard IBM on non-enhanced CT (p<0.05). Using standard IBM, CM led to a decrease of all airway parameters compared to NE. For example, LA decreased from 80.85±49.26mm2 at NE, to 75.14±47.96mm2 (-7.1%) at PA (p<0.001), 74.96±48.55mm2 (-7.3%) at SA (p<0.001), and to 78.95±48.94mm2 (-2.4%) at VE (p = 0.200). Using modified IBM, the differences were reduced to -3.1% at PA, -2.9% at SA and -0.7% at VE (p<0.001; p<0.001; p = 1.000).
conclusionsThe modified IBM can optimize airway wall segmentation and reduce the influence of CM on quantitative CT. This allows a more precise measurement as well as potentially the comparison of enhanced with non-enhanced scans in inflammatory airway disease.
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