1
|
Smith R, Morgan K, McCarron A, Cmielewski P, Reyne N, Parsons D, Donnelley M. Ultra-fast in vivodirectional dark-field x-ray imaging for visualising magnetic control of particles for airway gene delivery. Phys Med Biol 2024; 69:105025. [PMID: 38640914 DOI: 10.1088/1361-6560/ad40f5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Accepted: 04/19/2024] [Indexed: 04/21/2024]
Abstract
Objective.Magnetic nanoparticles can be used as a targeted delivery vehicle for genetic therapies. Understanding how they can be manipulated within the complex environment of live airways is key to their application to cystic fibrosis and other respiratory diseases.Approach.Dark-field x-ray imaging provides sensitivity to scattering information, and allows the presence of structures smaller than the detector pixel size to be detected. In this study, ultra-fast directional dark-field synchrotron x-ray imaging was utlilised to understand how magnetic nanoparticles move within a live, anaesthetised, rat airway under the influence of static and moving magnetic fields.Main results.Magnetic nanoparticles emerging from an indwelling tracheal cannula were detectable during delivery, with dark-field imaging increasing the signal-to-noise ratio of this event by 3.5 times compared to the x-ray transmission signal. Particle movement as well as particle retention was evident. Dynamic magnetic fields could manipulate the magnetic particlesin situ. Significance.This is the first evidence of the effectiveness ofin vivodark-field imaging operating at these spatial and temporal resolutions, used to detect magnetic nanoparticles. These findings provide the basis for further development toward the effective use of magnetic nanoparticles, and advance their potential as an effective delivery vehicle for genetic agents in the airways of live organisms.
Collapse
Affiliation(s)
- Ronan Smith
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| | - Kaye Morgan
- Department of Physics, Monash University, Wellington Road, Melbourne, Australia
| | - Alexandra McCarron
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| | - Patricia Cmielewski
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| | - Nicole Reyne
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| | - David Parsons
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| | - Martin Donnelley
- Adelaide Medical School, University of Adelaide, North Terrace, Adelaide, Australia
- Women's and Children's Hospital, King William Road, Adelaide, Australia
- Robinson Research Institute, University of Adelaide, King William Road, Adelaide, Australia
| |
Collapse
|
2
|
Busse M, Ferstl S, Kimm MA, Hehn L, Steiger K, Allner S, Muller M, Drecoll E, Burkner T, Dierolf M, Gleich B, Weichert W, Pfeiffer F. Multi-Scale Investigation of Human Renal Tissue in Three Dimensions. IEEE TRANSACTIONS ON MEDICAL IMAGING 2022; 41:3489-3497. [PMID: 36251918 DOI: 10.1109/tmi.2022.3214344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Histopathology as a diagnostic mainstay for tissue evaluation is strictly a 2D technology. Combining and supplementing this technology with 3D imaging has been proposed as one future avenue towards refining comprehensive tissue analysis. To this end, we have developed a laboratory-based X-ray method allowing for the investigation of tissue samples in three dimensions with isotropic volume information. To assess the potential of our method for micro-morphology evaluation, we selected several kidney regions from three patients with cystic kidney disease, obstructive nephropathy and diabetic glomerulopathy. Tissue specimens were processed using our in-house-developed X-ray eosin stain and investigated with a commercial microCT and our in-house-built NanoCT. The microCT system provided overview scans with voxel sizes of [Formula: see text] and the NanoCT was employed for higher resolutions including voxel sizes from [Formula: see text] to 210 nm. We present a methodology allowing for a precise micro-morphologic investigation in three dimensions which is compatible with conventional histology. Advantages of our methodology are its versatility with respect to multi-scale investigations, being laboratory-based, allowing for non-destructive imaging and providing isotropic volume information. We believe, that after future developmental work this method might contribute to advanced multi-modal tissue diagnostics.
Collapse
|
3
|
Meyer S, Shi SZ, Shapira N, Maidment ADA, Noël PB. Quantitative analysis of speckle-based X-ray dark-field imaging using numerical wave-optics simulations. Sci Rep 2021; 11:16113. [PMID: 34373478 PMCID: PMC8352882 DOI: 10.1038/s41598-021-95227-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/12/2021] [Indexed: 11/24/2022] Open
Abstract
The dark-field signal measures the small-angle scattering strength and provides complementary diagnostic information. This is of particular interest for lung imaging due to the pronounced small-angle scatter from the alveolar microstructure. However, most dark-field imaging techniques are relatively complex, dose-inefficient, and require sophisticated optics and highly coherent X-ray sources. Speckle-based imaging promises to overcome these limitations due to its simple and versatile setup, only requiring the addition of a random phase modulator to conventional X-ray equipment. We investigated quantitatively the influence of sample structure, setup geometry, and source energy on the dark-field signal in speckle-based X-ray imaging with wave-optics simulations for ensembles of micro-spheres. We show that the dark-field signal is accurately predicted via a model originally derived for grating interferometry when using the mean frequency of the speckle pattern power spectral density as the characteristic speckle size. The size directly reflects the correlation length of the diffuser surface and did not change with energy or propagation distance within the near-field. The dark-field signal had a distinct dependence on sample structure and setup geometry but was also affected by beam hardening-induced modifications of the visibility spectrum. This study quantitatively demonstrates the behavior of the dark-field signal in speckle-based X-ray imaging.
Collapse
Affiliation(s)
- Sebastian Meyer
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19103, USA.
| | - Serena Z Shi
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19103, USA
| | - Nadav Shapira
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19103, USA
| | - Andrew D A Maidment
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19103, USA
| | - Peter B Noël
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19103, USA.
- Department of Diagnostic and Interventional Radiology, School of Medicine and Klinikum rechts der Isar, Technical University of Munich, 81675, Munich, Germany.
| |
Collapse
|
4
|
Birnbacher L, Braig EM, Pfeiffer D, Pfeiffer F, Herzen J. Quantitative X-ray phase contrast computed tomography with grating interferometry : Biomedical applications of quantitative X-ray grating-based phase contrast computed tomography. Eur J Nucl Med Mol Imaging 2021; 48:4171-4188. [PMID: 33846846 PMCID: PMC8566444 DOI: 10.1007/s00259-021-05259-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 02/11/2021] [Indexed: 11/25/2022]
Abstract
The ability of biomedical imaging data to be of quantitative nature is getting increasingly important with the ongoing developments in data science. In contrast to conventional attenuation-based X-ray imaging, grating-based phase contrast computed tomography (GBPC-CT) is a phase contrast micro-CT imaging technique that can provide high soft tissue contrast at high spatial resolution. While there is a variety of different phase contrast imaging techniques, GBPC-CT can be applied with laboratory X-ray sources and enables quantitative determination of electron density and effective atomic number. In this review article, we present quantitative GBPC-CT with the focus on biomedical applications.
Collapse
Affiliation(s)
- Lorenz Birnbacher
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Eva-Maria Braig
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
| | - Daniela Pfeiffer
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Franz Pfeiffer
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany
- Department of Diagnostic and Interventional Radiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
| | - Julia Herzen
- Physics Department, Munich School of Bioengineering, Technical University of Munich, Munich, Germany.
| |
Collapse
|