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3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing
by
Schmale, Sebastian
, Salditt, Tim
, Blaurock, Claudia
, Reichmann, Jakob
, Balkema-Buschmann, Anne
, Sarrazin, Clement
, Schmitzer, Bernhard
in
631/1647/245/1847
/ 631/1647/245/2221
/ 639/766/747
/ 692/308/153
/ 692/700/139/422
/ Alveoli
/ Animal models
/ Animals
/ Classification
/ COVID-19
/ COVID-19 - diagnostic imaging
/ COVID-19 - pathology
/ COVID-19 - virology
/ COVID-19 Drug Treatment
/ Cricetinae
/ Data acquisition
/ Disease Models, Animal
/ Drug development
/ Drug Evaluation, Preclinical - methods
/ Drug testing
/ Histology
/ Humanities and Social Sciences
/ Imaging, Three-Dimensional - methods
/ Lung - diagnostic imaging
/ Lung - pathology
/ Lung - virology
/ Medical research
/ multidisciplinary
/ Physiology
/ Radiation
/ SARS-CoV-2 - isolation & purification
/ Science
/ Science (multidisciplinary)
/ Severe acute respiratory syndrome coronavirus 2
/ Soft tissues
/ Tomography
/ Tomography, X-Ray Computed - methods
/ Visual discrimination
2024
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3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing
by
Schmale, Sebastian
, Salditt, Tim
, Blaurock, Claudia
, Reichmann, Jakob
, Balkema-Buschmann, Anne
, Sarrazin, Clement
, Schmitzer, Bernhard
in
631/1647/245/1847
/ 631/1647/245/2221
/ 639/766/747
/ 692/308/153
/ 692/700/139/422
/ Alveoli
/ Animal models
/ Animals
/ Classification
/ COVID-19
/ COVID-19 - diagnostic imaging
/ COVID-19 - pathology
/ COVID-19 - virology
/ COVID-19 Drug Treatment
/ Cricetinae
/ Data acquisition
/ Disease Models, Animal
/ Drug development
/ Drug Evaluation, Preclinical - methods
/ Drug testing
/ Histology
/ Humanities and Social Sciences
/ Imaging, Three-Dimensional - methods
/ Lung - diagnostic imaging
/ Lung - pathology
/ Lung - virology
/ Medical research
/ multidisciplinary
/ Physiology
/ Radiation
/ SARS-CoV-2 - isolation & purification
/ Science
/ Science (multidisciplinary)
/ Severe acute respiratory syndrome coronavirus 2
/ Soft tissues
/ Tomography
/ Tomography, X-Ray Computed - methods
/ Visual discrimination
2024
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3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing
by
Schmale, Sebastian
, Salditt, Tim
, Blaurock, Claudia
, Reichmann, Jakob
, Balkema-Buschmann, Anne
, Sarrazin, Clement
, Schmitzer, Bernhard
in
631/1647/245/1847
/ 631/1647/245/2221
/ 639/766/747
/ 692/308/153
/ 692/700/139/422
/ Alveoli
/ Animal models
/ Animals
/ Classification
/ COVID-19
/ COVID-19 - diagnostic imaging
/ COVID-19 - pathology
/ COVID-19 - virology
/ COVID-19 Drug Treatment
/ Cricetinae
/ Data acquisition
/ Disease Models, Animal
/ Drug development
/ Drug Evaluation, Preclinical - methods
/ Drug testing
/ Histology
/ Humanities and Social Sciences
/ Imaging, Three-Dimensional - methods
/ Lung - diagnostic imaging
/ Lung - pathology
/ Lung - virology
/ Medical research
/ multidisciplinary
/ Physiology
/ Radiation
/ SARS-CoV-2 - isolation & purification
/ Science
/ Science (multidisciplinary)
/ Severe acute respiratory syndrome coronavirus 2
/ Soft tissues
/ Tomography
/ Tomography, X-Ray Computed - methods
/ Visual discrimination
2024
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3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing
Journal Article
3D imaging of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography enables drug testing
2024
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Overview
X-ray Phase Contrast Tomography (XPCT) based on wavefield propagation has been established as a high resolution three-dimensional (3D) imaging modality, suitable to reconstruct the intricate structure of soft tissues, and the corresponding pathological alterations. However, for biomedical research, more is needed than 3D visualisation and rendering of the cytoarchitecture in a few selected cases. First, the throughput needs to be increased to cover a statistically relevant number of samples. Second, the cytoarchitecture has to be quantified in terms of morphometric parameters, independent of visual impression. Third, dimensionality reduction and classification are required for identification of effects and interpretation of results. To address these challenges, we here design and implement a novel integrated and high throughput XPCT imaging and analysis workflow for 3D histology, pathohistology and drug testing. Our approach uses semi-automated data acquisition, reconstruction and statistical quantification. We demonstrate its capability for the example of lung pathohistology in Covid-19. Using a small animal model, different Covid-19 drug candidates are administered after infection and tested in view of restoration of the physiological cytoarchitecture, specifically the alveolar morphology. To this end, we then use morphometric parameter determination followed by a dimensionality reduction and classification based on optimal transport. This approach allows efficient discrimination between physiological and pathological lung structure, thereby providing quantitative insights into the pathological progression and partial recovery due to drug treatment. Finally, we stress that the XPCT image chain implemented here only used synchrotron radiation for validation, while the data used for analysis was recorded with laboratory
μ
CT radiation, more easily accessible for pre-clinical research.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
/ Alveoli
/ Animals
/ COVID-19
/ COVID-19 - diagnostic imaging
/ Drug Evaluation, Preclinical - methods
/ Humanities and Social Sciences
/ Imaging, Three-Dimensional - methods
/ SARS-CoV-2 - isolation & purification
/ Science
/ Severe acute respiratory syndrome coronavirus 2
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