1
|
Lin Q, Wu Z, Huang M, Dang Z, Tian L, Guan Y, Liu G, Lu Y, Tian Y. Detection of early pulmonary emphysema by multi-contrast x-ray Talbot-Lau interferometer. Med Phys 2024; 51:4133-4142. [PMID: 38578373 DOI: 10.1002/mp.17053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 03/14/2024] [Accepted: 03/24/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Pulmonary emphysema is a part of chronic obstructive pulmonary disease, which is an irreversible chronic respiratory disease. In order to avoid further damage to lung tissue, early diagnosis and treatment of pulmonary emphysema is essential. PURPOSE Early pulmonary emphysema diagnosis is difficult with conventional radiographic imaging. Recently, x-ray phase contrast imaging has proved to be an effective and promising imaging strategy for soft tissue, due to its high sensitivity and multi-contrast. The aim of this study is to diagnose pulmonary emphysema early utilizing an x-ray Talbot-Lau interferometer (TLI). METHODS We successfully established the mouse model of emphysema by porcine pancreatic elastase treatment, and then used the established x-ray TLI to perform imaging experiments on the mice with different treatment time. The traditional absorption CT and phase contrast CT were obtained simultaneously through TLI. The CT results and histopathology of mice lung in different treatment time were quantitatively analyzed. RESULTS By imaging mice lungs, it can be found that phase contrast has higher sensitivity than absorption contrast in early pulmonary emphysema. The results show that the phase contrast signal could distinguish the pulmonary emphysema earlier than the conventional attenuation signal, which can be consistent with histological images. Through the quantitative analysis of pathological section and phase contrast CT, it can be found that there is a strong linear correlation. CONCLUSIONS In this study, we quantitatively analyze mean linear intercept of histological sections and CT values of mice. The results show that the phase contrast signal has higher imaging sensitivity than the attenuation signal. X-ray TLI multi-contrast imaging is proved as a potential diagnostic method for early pulmonary emphysema in mice.
Collapse
Affiliation(s)
- Qisi Lin
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Zhao Wu
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Meng Huang
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
- Ultrasonic Department, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zheng Dang
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Lijiao Tian
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Yong Guan
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Gang Liu
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| | - Yalin Lu
- Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei, China
| | - Yangchao Tian
- National Synchrotron Radiation Laboratory, University of Science and Technology of China, Hefei, China
| |
Collapse
|
2
|
Rubin DA. Dark Matter: Information from Scattered X-ray Photons May Contribute to Fracture Detection. Radiology 2024; 311:e240794. [PMID: 38805730 DOI: 10.1148/radiol.240794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/30/2024]
Affiliation(s)
- David A Rubin
- From the Department of Radiology, NYU Grossman School of Medicine, 160 E 34th St, New York, NY 10016; All Pro Orthopedic Imaging Consultants, St Louis, Mo; and Radsource, Brentwood, Tenn
| |
Collapse
|
3
|
Guo P, Zhang L, Lu J, Zhang H, Zhu X, Wu C, Zhan X, Yin H, Wang Z, Xu Y, Wang Z. Grating-based x-ray dark-field CT for lung cancer diagnosis in mice. Eur Radiol Exp 2024; 8:12. [PMID: 38270720 PMCID: PMC10810771 DOI: 10.1186/s41747-023-00399-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 10/20/2023] [Indexed: 01/26/2024] Open
Abstract
BACKGROUND The low absorption of x-rays in lung tissue and the poor resolution of conventional computed tomography (CT) limits its use to detect lung disease. However, x-ray dark-field imaging can sense the scattered x-rays deflected by the structures being imaged. This technique can facilitate the detection of small alveolar lesions that would be difficult to detect with conventional CT. Therefore, it may provide an alternative imaging modality to diagnose lung disease at an early stage. METHODS Eight mice were inoculated with lung cancers simultaneously. Each time two mice were scanned using a grating-based dark-field CT on days 4, 8, 12, and 16 after the introduction of the cancer cells. The detectability index was calculated between nodules and healthy parenchyma for both attenuation and dark-field modalities. High-resolution micro-CT and pathological examinations were used to crosscheck and validate our results. Paired t-test was used for comparing the ability of dark-field and attenuation modalities in pulmonary nodule detection. RESULTS The nodules were shown as a signal decrease in the dark-field modality and a signal increase in the attenuation modality. The number of nodules increased from day 8 to day 16, indicating disease progression. The detectability indices of dark-field modality were higher than those of attenuation modality (p = 0.025). CONCLUSIONS Compared with the standard attenuation CT, the dark-field CT improved the detection of lung nodules. RELEVANCE STATEMENT Dark-field CT has a higher detectability index than conventional attenuation CT in lung nodule detection. This technique could improve the early diagnosis of lung cancer. KEY POINTS • Lung cancer progression was observed using x-ray dark-field CT. • Dark-field modality complements with attenuation modality in lung nodule detection. • Dark-field modality showed a detectability index higher than that attenuation in nodule detection.
Collapse
Affiliation(s)
- Peiyuan Guo
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China
- Institute for Precision Medicine, Tsinghua University, Beijing, China
| | - Li Zhang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China
- Institute for Precision Medicine, Tsinghua University, Beijing, China
| | - Jincheng Lu
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China
- Institute for Precision Medicine, Tsinghua University, Beijing, China
| | - Huitao Zhang
- School of Mathematical Sciences, Capital Normal University, Beijing, China
| | - Xiaohua Zhu
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China
| | - Chengpeng Wu
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China
| | - Xiangwen Zhan
- NHC Key Laboratory of Human Disease Comparative Medicine, Beijing Engineering Research Center for Experimental Animal Models of Human Critical Diseases, Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences (CAMS) and Comparative Medicine Center, Peking Union Medical College (PUMC), Beijing, China
| | - Hongxia Yin
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yan Xu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| | - Zhentian Wang
- Department of Engineering Physics, Tsinghua University, Beijing, China.
- Key Laboratory of Particle & Radiation Imaging (Tsinghua University) of Ministry of Education, Beijing, China.
- Institute for Precision Medicine, Tsinghua University, Beijing, China.
| |
Collapse
|