@inproceedings{5565f466461e4d0a9bf2657c44271b22,
title = "Complementary use of x-ray dark-field and attenuation computed tomography in quantifying pulmonary fibrosis in a mouse model",
abstract = "X-ray dark-field measured on laboratory sources with large focal spots and detector apertures is sensitive to intra-pixel phase gradients abundant in the lungs due to its hierarchical structure of subdividing airways terminating in thin-walled alveoli. This work leverages this sensitivity to exploit complementary information from x-ray dark-field and attenuation computed tomography (CT) images to improve quantification of morphology in pulmonary fibrosis. Specifically, a dark-field enhanced attenuation technique is developed to restore edges and small features in the attenuation image lost to blurring by appropriately scaling and subtracting the dark-field image. An intratracheally treated bleomycin mouse model of pulmonary fibrosis was used to evaluate the impact of the proposed dark-field enhanced attenuation technique on quantifying fibrosis extent. The mouse model was fixated ex vivo to be imaged with a Talbot-Lau grating interferometer micro-CT to generate x-ray dark field and attenuation volumes of 60 µm voxels. Then the specimen was imaged with a reference micro-CT scanner at 5 µm voxel resolution to get a ground truth approximation of local structure. The volumes were co-registered for visual and pixelwise comparisons. Qualitative image comparisons were used to assess visual sharpness while Bland-Altman plots were used to assess agreement with the reference scan at quantifying fibrosis in terms of tissue area fraction measured in 80 randomly sampled nonoverlapping 2 mm square patches. Visual comparisons demonstrated enhanced sharpness and retention of small lung structures while Bland-Altman analysis revealed an improved agreement ratio of 0.544 compared to 0.374 in the original attenuation image with a reduction in variance. These results demonstrate that dark-field and attenuation images can be used together to improve resolution of small structures and aid in quantification of pulmonary fibrosis in a mouse model.",
keywords = "bleomycin, computed tomography, dark field, pulmonary fibrosis",
author = "Nelson, {Brandon J.} and Shuai Leng and Thomas Koenig and McCollough, {Cynthia H.}",
note = "Publisher Copyright: {\textcopyright} 2022 SPIE; Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and Functional Imaging ; Conference date: 21-03-2022 Through 27-03-2022",
year = "2022",
doi = "10.1117/12.2612877",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Gimi, {Barjor S.} and Andrzej Krol",
booktitle = "Medical Imaging 2022",
}