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Locally Adaptive Half-Max Methods for Airway Lumen-Area and Wall-Thickness and Their Repeat CT Scan Reproducibility
Conference proceeding

Locally Adaptive Half-Max Methods for Airway Lumen-Area and Wall-Thickness and Their Repeat CT Scan Reproducibility

Syed Ahmed Nadeem, Eric A Hoffman, Alejandro P Comellas and Punam K Saha
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Vol.2020-, pp.1883-1886
04/2020
DOI: 10.1109/ISBI45749.2020.9098558
PMCID: PMC8375398
PMID: 34422222
url
https://www.ncbi.nlm.nih.gov/pmc/articles/8375398View
Open Access

Abstract

Quantitative computed tomography (CT)-based characterization of bronchial metrics is increasingly being used to investigate chronic obstructive pulmonary disease (COPD)-related phenotypes. Automated methods for airway measurements benefit large multi-site studies by reducing cost and subjectivity errors. Critical challenges for CT-based analysis of airway morphology are related to location of lumen and wall transitions in the presence of varying scales and intensity-contrasts from proximal to distal sites. This paper introduces locally adaptive half-max methods to locate airway lumen and wall transitions and compute cross-sectional lumen area and wall-thickness. Also, the method uses a consistency analysis of wall-thickness to avoid adjoining-structure-artifacts. Experimental results show that computed bronchial measures at individual anatomic airway tree locations are repeat CT scan reproducible with intra-class correlation coefficient (ICC) values exceeding 0.9 and 0.8 for lumen-area and wall-thickness, respectively. Observed ICC values for derived morphologic measures, e.g., lumen-area compactness ( \text{ICC} > 0.67 ) and tapering ( \text{ICC} > 0.47 ) are relatively lower.
airway measurements airway tree Computed tomography COPD wall thickness

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