In vivo 4D x-ray dark-field lung imaging in mice
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910708489256960 |
|---|---|
| author | How, Ying Ying Reyne, Nicole Croughan, Michelle K. Cmielewski, Patricia Batey, Daniel Costello, Lucy F. Smith, Ronan Ahlers, Jannis N. Cholewa, Marian Kolodziej, Magdalena Duerr, Julia Mall, Marcus A. Kitchen, Marcus J. Asselin-Labat, Marie-Liesse Paganin, David M. Donnelley, Martin Morgan, Kaye S. |
| author_facet | How, Ying Ying Reyne, Nicole Croughan, Michelle K. Cmielewski, Patricia Batey, Daniel Costello, Lucy F. Smith, Ronan Ahlers, Jannis N. Cholewa, Marian Kolodziej, Magdalena Duerr, Julia Mall, Marcus A. Kitchen, Marcus J. Asselin-Labat, Marie-Liesse Paganin, David M. Donnelley, Martin Morgan, Kaye S. |
| contents | X-ray dark-field imaging is well-suited to visualizing the health of the lungs because the alveoli create a strong dark-field signal. However, time-resolved and tomographic (i.e., 4D) dark-field imaging is challenging, since most x-ray dark-field techniques require multiple sample exposures, captured while scanning the position of crystals or gratings. Here, we present the first in vivo 4D x-ray dark-field lung imaging in mice. This was achieved by synchronizing the data acquisition process of a single-exposure grid-based imaging approach with the breath cycle. The short data acquisition time per dark-field projection made this approach feasible for 4D x-ray dark-field imaging by minimizing the motion-blurring effect, the total time required and the radiation dose imposed on the sample. Images were captured from a control mouse and from mouse models of muco-obstructive disease and lung cancer, where a change in the size of the alveoli was expected. This work demonstrates that the 4D dark-field signal provides complementary information that is inaccessible from conventional attenuation-based CT images, in particular, how the size of the alveoli from different parts of the lungs changes throughout a breath cycle, with examples shown across the different models. By quantifying the dark-field signal and relating it to other physical properties of the alveoli, this technique could be used to perform functional lung imaging that allows the assessment of both global and regional lung conditions where the size or expansion of the alveoli is affected. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_14669 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | In vivo 4D x-ray dark-field lung imaging in mice How, Ying Ying Reyne, Nicole Croughan, Michelle K. Cmielewski, Patricia Batey, Daniel Costello, Lucy F. Smith, Ronan Ahlers, Jannis N. Cholewa, Marian Kolodziej, Magdalena Duerr, Julia Mall, Marcus A. Kitchen, Marcus J. Asselin-Labat, Marie-Liesse Paganin, David M. Donnelley, Martin Morgan, Kaye S. Medical Physics X-ray dark-field imaging is well-suited to visualizing the health of the lungs because the alveoli create a strong dark-field signal. However, time-resolved and tomographic (i.e., 4D) dark-field imaging is challenging, since most x-ray dark-field techniques require multiple sample exposures, captured while scanning the position of crystals or gratings. Here, we present the first in vivo 4D x-ray dark-field lung imaging in mice. This was achieved by synchronizing the data acquisition process of a single-exposure grid-based imaging approach with the breath cycle. The short data acquisition time per dark-field projection made this approach feasible for 4D x-ray dark-field imaging by minimizing the motion-blurring effect, the total time required and the radiation dose imposed on the sample. Images were captured from a control mouse and from mouse models of muco-obstructive disease and lung cancer, where a change in the size of the alveoli was expected. This work demonstrates that the 4D dark-field signal provides complementary information that is inaccessible from conventional attenuation-based CT images, in particular, how the size of the alveoli from different parts of the lungs changes throughout a breath cycle, with examples shown across the different models. By quantifying the dark-field signal and relating it to other physical properties of the alveoli, this technique could be used to perform functional lung imaging that allows the assessment of both global and regional lung conditions where the size or expansion of the alveoli is affected. |
| title | In vivo 4D x-ray dark-field lung imaging in mice |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2411.14669 |