Quantifying the Accuracy of Airquant Airway Measurements of to-Scale 3D Airway Models
Abstract
Purpose
To quantify the accuracy of airway measurement using AirQuant on to-scale airway models.
Methods
Six lobar airway models based on airway measurements of three patients using AirQuant were 3D-printed. The modeling pipeline generates a signed distance field of blended hollow tapered capsules based on patient anatomy with known luminal radii, luminal area, and wall thickness. In total, 123 distinct airways were printed. CT scans were collected of the models submerged in rice, mimicking lung parenchyma. AirQuant was then used to measure airway metrics from these scans. CT-derived metrics were then compared to the known model dimensions. For each metric, average error and standard deviation were calculated. Bland Altman analyses were run to determine mean bias.
Results
The models had a mean luminal radius of 1.87mm (range: 0.69mm-5.92mm), the AirQuant-measured CT scans of the model ("CT") had a mean of 1.98mm (range: 0.76mm-7.16mm). The average absolute error between the CT luminal radius and the model dimensions was 0.19mm (p = 5E-6). The model had a mean wall thickness of 1.15mm (range: 0.80-2.05mm); the CT had a mean thickness of 1.62mm (range: 1.33-2.39mm). The wall thickness average absolute error was 0.532mm (p = 2E-24). The model luminal area had a mean of 13.63 mm2 (range: 1.71-113.07mm2); the mean CT luminal area was 15.00mm2 (range: 2.26-165.74mm2). The luminal area average absolute error was 3.28mm2 (p < 0.001).
Conclusion
While paired t-tests indicate that AirQuant measurements are significantly different from the model dimensions, the mean error for luminal radius is smaller than a high-resolution CT slice of 0.5mm, meaning AirQuant is accurately measuring dimensions to within one voxel. The mean error for wall thickness was similarly close to 0.5mm. The error magnitude suggests that AirQuant can reliably quantify differences in luminal and outer radii in patient CT scans.