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 - Konietzke, Philip; Weinheimer, Oliver; Wagner, Willi Linus; Wünnemann, Felix; Hintze, Christian; Biederer, Jürgen; Heußel, Claus Peter; Kauczor, Hans-Ulrich; Wielpütz, Mark Oliver (PLOS ONE, 2020)
Introduction Quantitative 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. Methods Temporally 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. Results The 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). Conclusions The 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.