TL;DR
This study introduces a reproducible method for measuring airway tapering in CT scans, demonstrating its ability to distinguish healthy airways from bronchiectasis-affected ones and assessing measurement robustness across different scan parameters.
Contribution
The paper presents a novel pipeline for quantifying airway tapering from CT scans and evaluates its reproducibility under various imaging conditions, advancing quantitative airway analysis.
Findings
Significant difference in tapering between healthy and bronchiectasis airways
Measurement remains reliable across different radiation doses and voxel sizes
Code for the method is publicly available
Abstract
Purpose: This paper proposes a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on CT. We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure. Methods: We generate a spline from the centreline of an airway to measure the area and arclength at contiguous intervals. The tapering measurement is the gradient of the linear regression between area in log space and arclength. The reproducibility of the measure was assessed by analysing different radiation doses, voxel sizes and reconstruction kernel on single timepoint and longitudinal CT scans and by evaluating the effct of airway bifurcations. Results: Using 74 airways from 10 CT scans, we show a statistical difference, p = 3.4 10 in tapering between healthy airways…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsLinear Regression
