Abstract
Optical coherence tomography (OCT) has been increasingly used for imaging pulmonary alveoli. Only a few studies, however, have quantified individual alveolar areas, and the validity of alveolar volumes represented within OCT images has not been shown. To validate quantitative measurements of alveoli from OCT images, we compared the cross-sectional area, perimeter, volume, and surface area of matched subpleural alveoli from micro-computed tomography (micro-CT) and OCT images of fixed air-filled swine samples. The relative change in size between different alveoli was extremely well correlated (r > 0.9, P < 0.0001), but OCT images underestimated absolute sizes compared to micro-CT by 27% (area), 7% (perimeter), 46% (volume), and 25% (surface area) on average. We hypothesized that the differences resulted from refraction at the tissue-air interfaces and developed a ray-tracing model that approximates the reconstructed alveolar size within OCT images. Using this model and OCT measurements of the refractive index for lung tissue (1.41 for fresh, 1.53 for fixed), we derived equations to obtain absolute size measurements of superellipse and circular alveoli with the use of predictive correction factors. These methods and results should enable the quantification of alveolar sizes from OCT images in vivo.
| Original language | English |
|---|---|
| Article number | 126015 |
| Journal | Journal of Biomedical Optics |
| Volume | 17 |
| Issue number | 12 |
| ISSN | 1083-3668 |
| DOIs | |
| Publication status | Published - 01.01.2012 |
| Externally published | Yes |
Funding
The authors thank Elkan Halpern from the MGH Institute for Technology Assessment and Benoit Piednoir from Air Liquide for expert statistical advice, as well as Hao Wang and Veronica Delaney for help with the tissue paste preparation and with the index measurement. This work has been supported by Air Liquide R&D, Medical Gases, Les-Loges-en-Josas, France. Additional funds were provided by the Center for Biomedical OCT Research and Translation through grant number P41EB015903, awarded by the National Center for Research Resources and the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health.