Skip to main navigationSkip to main content
The University of Southampton
µ-VIS: Multidisciplinary, Multiscale, Microtomographic Volume Imaging

3D X-ray Histology (XRH)

Publications

This section lists the research outputs like peer-reviewed publications in scientific journals and conference proceedings related to 3D X-ray Histology generated by our group.

Peer-reviewed publications in scientific journals

JabRef references
Matching entries: 0
settings...
Katsamenis OL, Olding M, Warner JA, Chatelet DS, Jones MG, Sgalla G, Smit B, Larkin OJ, Haig I, Richeldi L and others (2019), "X-ray micro-computed tomography for non-destructive 3D X-ray histology", The American journal of pathology., May, 2019. Elsevier.
Abstract: Historically, micro-computed tomography has been considered unsuitable for histological analysis of unstained formalin-fixed and paraffin-embedded (FFPE) soft tissue biopsies due to a lack of image contrast between the tissue and the paraffin. However, we recently demonstrated that μCT can successfully resolve microstructural detail in routinely prepared tissue specimens. Here, we illustrate how μCT imaging of standard FFPE biopsies can be seamlessly integrated into conventional histology workflows, enabling non-destructive three-dimensional (3D) X-ray histology, the use and benefits of which we showcase for the exemplar of human lung biopsy specimens. This technology advancement was achieved through manufacturing a first-of-kind μCT scanner for X-ray histology and developing optimised imaging protocols, which do not require any additional sample preparation. 3D X-ray histology allows for non-destructive 3D imaging of tissue microstructure, resolving structural connectivity and heterogeneity of complex tissue networks, such as the vascular or the respiratory tract. We also demonstrate that 3D X-ray histology can yield consistent and reproducible image quality, enabling quantitative assessment of tissue’s 3D microstructures, which is inaccessible to conventional two-dimensional histology. Being non-destructive the technique does not interfere with histology workflows, permitting subsequent tissue characterisation by means of conventional light microscopy-based histology, immunohistochemistry, and immunofluorescence. 3D X-ray histology can be readily applied to a plethora of archival materials, yielding unprecedented opportunities in diagnosis and research of disease.
BibTeX:
@article{Katsamenis2019,
  author = {Katsamenis, Orestis L and Olding, Michael and Warner, Jane A and Chatelet, David S and Jones, Mark G and Sgalla, Giacomo and Smit, Bennie and Larkin, Oliver J and Haig, Ian and Richeldi, Luca and others},
  title = {X-ray micro-computed tomography for non-destructive 3D X-ray histology},
  journal = {The American journal of pathology},
  publisher = {Elsevier},
  year = {2019},
  note = {In Press, Accepted Manuscript},
  url = {https://www.sciencedirect.com/science/article/pii/S0002944019302068},
  doi = {10.1016/j.ajpath.2019.05.004}
}
Koo H-K, Vasilescu DM, Booth S, Hsieh A, Katsamenis OL, Fishbane N, Elliott WM, Kirby M, Lackie P, Sinclair I, Warner JA, Cooper JD, Coxson HO, Paré PD, Hogg JC and Hackett T-L (2018), "Small airways disease in mild and moderate chronic obstructive pulmonary disease: a cross-sectional study.", The Lancet. Respiratory medicine., August, 2018. Vol. 6, pp. 591-602.
Abstract: The concept that small conducting airways less than 2 mm in diameter become the major site of airflow obstruction in chronic obstructive pulmonary disease (COPD) is well established in the scientific literature, and the last generation of small conducting airways, terminal bronchioles, are known to be destroyed in patients with very severe COPD. We aimed to determine whether destruction of the terminal and transitional bronchioles (the first generation of respiratory airways) occurs before, or in parallel with, emphysematous tissue destruction. In this cross-sectional analysis, we applied a novel multiresolution CT imaging protocol to tissue samples obtained using a systematic uniform sampling method to obtain representative unbiased samples of the whole lung or lobe of smokers with normal lung function (controls) and patients with mild COPD (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 1), moderate COPD (GOLD 2), or very severe COPD (GOLD 4). Patients with GOLD 1 or GOLD 2 COPD and smokers with normal lung function had undergone lobectomy and pneumonectomy, and patients with GOLD 4 COPD had undergone lung transplantation. Lung tissue samples were used for stereological assessment of the number and morphology of terminal and transitional bronchioles, airspace size (mean linear intercept), and alveolar surface area. Of the 34 patients included in this study, ten were controls (smokers with normal lung function), ten patients had GOLD 1 COPD, eight had GOLD 2 COPD, and six had GOLD 4 COPD with centrilobular emphysema. The 34 lung specimens provided 262 lung samples. Compared with control smokers, the number of terminal bronchioles decreased by 40% in patients with GOLD 1 COPD (p=0·014) and 43% in patients with GOLD 2 COPD (p=0·036), the number of transitional bronchioles decreased by 56% in patients with GOLD 1 COPD (p=0·0001) and 59% in patients with GOLD 2 COPD (p=0·0001), and alveolar surface area decreased by 33% in patients with GOLD 1 COPD (p=0·019) and 45% in patients with GOLD 2 COPD (p=0·0021). These pathological changes were found to correlate with lung function decline. We also showed significant loss of terminal and transitional bronchioles in lung samples from patients with GOLD 1 or GOLD 2 COPD that had a normal alveolar surface area. Remaining small airways were found to have thickened walls and narrowed lumens, which become more obstructed with increasing COPD GOLD stage. These data show that small airways disease is a pathological feature in mild and moderate COPD. Importantly, this study emphasises that early intervention for disease modification might be required by patients with mild or moderate COPD. Canadian Institutes of Health Research.
BibTeX:
@article{Koo2018,
  author = {Koo, Hyun-Kyoung and Vasilescu, Dragoş M and Booth, Steven and Hsieh, Aileen and Katsamenis, Orestis L and Fishbane, Nick and Elliott, W Mark and Kirby, Miranda and Lackie, Peter and Sinclair, Ian and Warner, Jane A and Cooper, Joel D and Coxson, Harvey O and Paré, Peter D and Hogg, James C and Hackett, Tillie-Louise},
  title = {Small airways disease in mild and moderate chronic obstructive pulmonary disease: a cross-sectional study.},
  journal = {The Lancet. Respiratory medicine},
  year = {2018},
  volume = {6},
  pages = {591--602},
  doi = {10.1016/S2213-2600(18)30196-6}
}
Karavasili C, Andreadis DA, Katsamenis OL, Panteris E, Anastasiadou P, Kakazanis Z, Zoumpourlis V, Markopoulou CK, Koutsopoulos S, Vizirianakis IS and others (2019), "Synergistic anti-tumour potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer", Molecular pharmaceutics. ACS Publications.
Abstract: Combination therapy has been conferred with manifold assets leveraging the synergy of different agents to achieve a sufficient therapeutic outcome with lower administered drug doses and reduced side effects. The therapeutic potency of a self-assembling peptide hydrogel for the co-delivery of doxorubicin and curcumin was assessed against head and neck cancer cells. The dual loaded peptide hydrogel enabled control over the rate of drug release based on drug’s aqueous solubility. A significantly enhanced cell growth inhibitory effect was observed after treatment with the combination drug-loaded hydrogel formulations compared to the respective combination drug solution. The synergistic pharmacological effect of selected hydrogel formulations was further confirmed with enhanced apoptotic cell response, interference in cell cycle progression, and significantly altered apoptotic/anti-apoptotic gene expression profiles obtained in dose levels well below the half-maximal inhibitory concentrations of both drugs. The in vivo antitumor efficacy of the drug-loaded peptide hydrogel formulation was confirmed in HSC-3 cell-xenografted severe combined immunodeficient mice and visualized with μCT imaging. Histological and terminal deoxynucleotidyl transferase dUTP nick end labeling assay analyses of major organs were implemented to assess the safety of the topically administered hydrogel formulation. Overall, results demonstrated the therapeutic utility of the dual drug-loaded peptide hydrogel as a pertinent approach for the local treatment of head and neck cancer.
BibTeX:
@article{karavasili2019synergistic,
  author = {Karavasili, Christina and Andreadis, Dimitrios A and Katsamenis, Orestis L and Panteris, Emmanuel and Anastasiadou, Pinelopi and Kakazanis, Zacharias and Zoumpourlis, Vasilis and Markopoulou, Catherine K and Koutsopoulos, Sotirios and Vizirianakis, Ioannis S and others},
  title = {Synergistic anti-tumour potency of a self-assembling peptide hydrogel for the local co-delivery of doxorubicin and curcumin in the treatment of head and neck cancer},
  journal = {Molecular pharmaceutics},
  publisher = {ACS Publications},
  year = {2019},
  url = {https://pubs.acs.org/doi/abs/10.1021/acs.molpharmaceut.8b01221},
  doi = {10.1021/acs.molpharmaceut.8b01221}
}
Robinson SK, Ramsden JJ, Warner J, Lackie PM and Roose T (2019), "Correlative 3D Imaging and Microfluidic Modelling of Human Pulmonary Lymphatics using Immunohistochemistry and High-resolution μCT", Scientific reports. Vol. 9(1), pp. 6415. Nature Publishing Group.
Abstract: Lung lymphatics maintain fluid homoeostasis by providing a drainage system that returns fluid, cells and metabolites to the circulatory system. The 3D structure of the human pulmonary lymphatic network is essential to lung function, but it is poorly characterised. Image-based 3D mathematical modelling of pulmonary lymphatic microfluidics has been limited by the lack of accurate and representative image geometries. This is due to the microstructural similarity of the lymphatics to the blood vessel network, the lack of lymphatic-specific biomarkers, the technical limitations associated with image resolution in 3D, and sectioning artefacts present in 2D techniques. We present a method that combines lymphatic specific (D240 antibody) immunohistochemistry (IHC), optimised high-resolution X-ray microfocus computed tomography (μCT) and finite-element mathematical modelling to assess the function of human peripheral lung tissue. The initial results identify lymphatic heterogeneity within and between lung tissue. Lymphatic vessel volume fraction and fractal dimension significantly decreases away from the lung pleural surface (p < 0.001, n = 25 and p < 0.01, n = 20, respectively). Microfluidic modelling successfully shows that in lung tissue the fluid derived from the blood vessels drains through the interstitium into the lymphatic vessel network and this drainage is different in the subpleural space compared to the intralobular space. When comparing lung tissue from health and disease, human pulmonary lymphatics were significantly different across five morphometric measures used in this study (p ≤ 0.0001). This proof of principle study establishes a new engineering technology and workflow for further studies of pulmonary lymphatics and demonstrates for the first time the combination of correlative μCT and IHC to enable 3D mathematical modelling of human lung microfluidics at micrometre resolution.
BibTeX:
@article{Robinson2019,
  author = {Robinson, Stephanie K and Ramsden, Jonathan J and Warner, Jane and Lackie, Peter M and Roose, Tiina},
  title = {Correlative 3D Imaging and Microfluidic Modelling of Human Pulmonary Lymphatics using Immunohistochemistry and High-resolution μCT},
  journal = {Scientific reports},
  publisher = {Nature Publishing Group},
  year = {2019},
  volume = {9},
  number = {1},
  pages = {6415},
  url = {https://www.nature.com/articles/s41598-019-42794-7#Ack1},
  doi = {10.1038/s41598-019-42794-7}
}
Scott A, Vasilescu D, Seal K, Keyes S, Mavrogordato M, Hogg J, Sinclair I, Warner J, Hackett T and Lackie P (2015), "Three dimensional imaging of paraffin embedded human lung tissue samples by micro-computed tomography", PLoS ONE., June, 2015. , pp. 1-10.
Abstract: Background: understanding the three-dimensional (3-D) micro-architecture of lung tissue can provide insights into the pathology of lung disease. Micro computed tomography (mu CT) has previously been used to elucidate lung 3D histology and morphometry in fixed samples that have been stained with contrast agents or air inflated and dried. However, non-destructive microstructural 3D imaging of formalin-fixed paraffin embedded (FFPE) tissues would facilitate retrospective analysis of extensive tissue archives of lung FFPE lung samples with linked clinical data.

Methods: FFPE human lung tissue samples (n = 4) were scanned using a Nikon metrology mu CT scanner. Semi-automatic techniques were used to segment the 3D structure of airways and blood vessels. Airspace size (mean linear intercept, Lm) was measured on mu CT images and on matched histological sections from the same FFPE samples imaged by light microscopy to validate mu CT imaging.

Results: the mu CT imaging protocol provided contrast between tissue and paraffin in FFPE samples (15mm x 7mm). Resolution (voxel size 6.7 mu m) in the reconstructed images was sufficient for semi-automatic image segmentation of airways and blood vessels as well as quantitative airspace analysis. The scans were also used to scout for regions of interest, enabling time-efficient preparation of conventional histological sections. The Lm measurements from mu CT images were not significantly different to those from matched histological sections.

Conclusion: we demonstrated how non-destructive imaging of routinely prepared FFPE samples by laboratory mu CT can be used to visualize and assess the 3D morphology of the lung including by morphometric analysis.
BibTeX:
@article{ScottVasilescuSealEtAl2015,
  author = {A.E. Scott and D.M. Vasilescu and K.A.D. Seal and S.D. Keyes and M.N. Mavrogordato and J.C. Hogg and I. Sinclair and J.A. Warner and T.L. Hackett and P.M. Lackie},
  title = {Three dimensional imaging of paraffin embedded human lung tissue samples by micro-computed tomography},
  journal = {PLoS ONE},
  year = {2015},
  pages = {1--10},
  url = {http://eprints.soton.ac.uk/381745/}
}
Jones MG, Fabre A, Schneider P, Cinetto F, Sgalla G, Mavrogordato M, Jogai S, Alzetani A, Marshall BG, O’Reilly KM and others (2016), "Three-dimensional characterization of fibroblast foci in idiopathic pulmonary fibrosis", JCI insight. Vol. 1(5) NIH Public Access.
Abstract: In idiopathic pulmonary fibrosis (IPF), the fibroblast focus is a key histological feature representing active fibroproliferation. On standard 2D pathologic examination, fibroblast foci are considered small, distinct lesions, although they have been proposed to form a highly interconnected reticulum as the leading edge of a “wave” of fibrosis. Here, we characterized fibroblast focus morphology and interrelationships in 3D using an integrated micro-CT and histological methodology. In 3D, fibroblast foci were morphologically complex structures, with large variations in shape and volume (range, 1.3 × 104 to 9.9 × 107 μm3). Within each tissue sample numerous multiform foci were present, ranging from a minimum of 0.9 per mm3 of lung tissue to a maximum of 11.1 per mm3 of lung tissue. Each focus was an independent structure, and no interconnections were observed. Together, our data indicate that in 3D fibroblast foci form a constellation of heterogeneous structures with large variations in shape and volume, suggesting previously unrecognized plasticity. No evidence of interconnectivity was identified, consistent with the concept that foci represent discrete sites of lung injury and repair.
BibTeX:
@article{Jones2016,
  author = {Jones, Mark G and Fabre, Aurélie and Schneider, Philipp and Cinetto, Francesco and Sgalla, Giacomo and Mavrogordato, Mark and Jogai, Sanjay and Alzetani, Aiman and Marshall, Ben G and O’Reilly, Katherine MA and others},
  title = {Three-dimensional characterization of fibroblast foci in idiopathic pulmonary fibrosis},
  journal = {JCI insight},
  publisher = {NIH Public Access},
  year = {2016},
  volume = {1},
  number = {5},
  url = {https://insight.jci.org/articles/view/86375},
  doi = {10.1172/jci.insight.86375}
}
Wollatz L, Johnston SJ, Lackie PM and Cox SJ (2017), "3D Histopathology—a Lung Tissue Segmentation Workflow for Microfocus X-ray-Computed Tomography Scans", Journal of Digital Imaging. , pp. 1-10. Springer.
Abstract: Lung histopathology is currently based on the analysis of 2D sections of tissue samples. The use of microfocus X-ray-computed tomography imaging of unstained soft tissue can provide high-resolution 3D image datasets in the range of 2–10 μm without affecting the current diagnostic workflow. Important details of structural features such as the tubular networks of airways and blood vessels are contained in these datasets but are difficult and time-consuming to identify by manual image segmentation. Providing 3D structures permits a better understanding of tissue functions and structural interrelationships. It also provides a more complete picture of heterogeneous samples. In addition, 3D analysis of tissue structure provides the potential for an entirely new level of quantitative measurements of this structure that have previously been based only on extrapolation from 2D sections. In this paper, a workflow for segmenting such 3D images semi-automatically has been created using and extending the ImageJ open-source software and key steps of the workflow have been integrated into a new ImageJ plug-in called LungJ. Results indicate an improved workflow with a modular organization of steps facilitating the optimization for different sample and scan properties with expert input as required. This allows for incremental and independent optimization of algorithms leading to faster segmentation. Representation of the tubular networks in samples of human lung, building on those segmentations, has been demonstrated using this approach.
BibTeX:
@article{Wollatz2017,
  author = {Wollatz, Lasse and Johnston, Steven J and Lackie, Peter M and Cox, Simon J},
  title = {3D Histopathology—a Lung Tissue Segmentation Workflow for Microfocus X-ray-Computed Tomography Scans},
  journal = {Journal of Digital Imaging},
  publisher = {Springer},
  year = {2017},
  pages = {1--10},
  url = {https://link.springer.com/article/10.1007/s10278-017-9966-5},
  doi = {10.1007/s10278-017-9966-5}
}
Created by JabRef on 03/06/2019.

Conference proceedings

JabRef references
Matching entries: 0
settings...
Katsamenis OL, Lawson MJ, Olding M, Warner JA, Chatelet DS, Jones MG, Sgalla G, Smit B, Larkin OJ, Haig I, Richeldi L, Lackie PM, Schneider P and Sinclair I (2018), "3D X-ray histology by means of micro- Computed Tomography", In 5thDigital Pathology Congress: Europe. London, UK, December, 2018.
BibTeX:
@conference{Katsamenis2018,
  author = {Katsamenis, O. L. and Lawson, M. J. and Olding, M. and Warner, J. A. and Chatelet, D. S. and Jones, M. G. and Sgalla, G. and Smit, B. and Larkin, O. J. and Haig, I. and Richeldi, L. and Lackie, P. M. and Schneider, P. and Sinclair, I.},
  title = {3D X-ray histology by means of micro- Computed Tomography},
  booktitle = {5thDigital Pathology Congress: Europe},
  year = {2018},
  url = {http://www.giiconference.com/gel560116/}
}
Lawson MJ, Katsamenis OL, Olding M, Larkin OJ, Smit B, Haig IG, Schneider P, Lackie PM and Warner JA (2018), "Mapping 3D networks in human lung tissue using micro-computed tomography and immunofluorescence", In 6th annual Tomography for Scientific Advancement (ToScA) symposium. Warwick, UK, September, 2018.
BibTeX:
@conference{Lawson2018,
  author = {Lawson, M. J. and Katsamenis, O. L. and Olding, M. and Larkin, O. J. and Smit, B. and Haig, I. G. and Schneider, P. and Lackie, P. M. and Warner, J. A.},
  title = {Mapping 3D networks in human lung tissue using micro-computed tomography and immunofluorescence},
  booktitle = {6th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2018},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2018.html}
}
Katsamenis OL, Olding M, Warner JA, Chatelet D, Jones MG, Sgalla G, Smit B, Larkin O, Haig I, Richeldi L, Lackie PM, Schneider P and Sinclair I (2018), "3D X-ray histology by means of micro-computed tomography: A streamline workflow for high-resolution 3D imaging of biopsy specimens", In 6th annual Tomography for Scientific Advancement (ToScA) symposium. Warwick, UK, September, 2018.
BibTeX:
@conference{Katsamenis2018a,
  author = {Katsamenis, O. L. and Olding, M. and Warner, J. A. and Chatelet, D. and Jones, M. G. and Sgalla, G. and Smit, B. and Larkin, O. and Haig, I. and Richeldi, L. and Lackie, P. M. and Schneider, P. and Sinclair, I.},
  title = {3D X-ray histology by means of micro-computed tomography: A streamline workflow for high-resolution 3D imaging of biopsy specimens},
  booktitle = {6th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2018},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2018.html}
}
Lawson MJ, Katsamenis OL, Olding M, Larkin OJ, Smit B, G.Haig I, Schneider P, Lackie PM and Warner JA (2017), "Correlative microfocus computed tomography and fluorescence microscopy of fixed human lung tissue", In 5th annual Tomography for Scientific Advancement (ToScA) symposium. Portsmouth, UK, September, 2017.
BibTeX:
@conference{Lawson2017,
  author = {Lawson, M. J. and Katsamenis, O. L. and Olding, M. and Larkin, O. J. and Smit, B. and G.Haig, I. and Schneider, P. and Lackie, P. M. and Warner, J. A.},
  title = {Correlative microfocus computed tomography and fluorescence microscopy of fixed human lung tissue},
  booktitle = {5th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2017},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2017.html}
}
Rossides. C, Katsamenis OL and Larkin O. J. Smit B. Haig I. G. Sinclair I. Pender S. L. F. Schneider P (2017), "Micro-computed tomography optimised for soft tissues: first steps towards early diagnosis of colorectal cancer", In 5th annual Tomography for Scientific Advancement (ToScA) symposium. Portsmouth, UK, September, 2017.
BibTeX:
@conference{Rossides.2017,
  author = {Rossides., C. and Katsamenis, O. L. and Larkin O. J. Smit B. Haig I. G. Sinclair I. Pender S. L. F. Schneider, P.},
  title = {Micro-computed tomography optimised for soft tissues: first steps towards early diagnosis of colorectal cancer},
  booktitle = {5th annual Tomography for Scientific Advancement (ToScA) symposium},
  year = {2017},
  url = {https://www.rms.org.uk/discover-engage/event-calendar/tosca-2017.html}
}
Schneider P (2019), "3D X-ray histology: micro-CT goes medical", In Annual Congress of the European Society of Biomechanics (ESB). Vienna, Austria, July, 2019.
Abstract: Background
Living structures are an intricate three-dimensional (3D) arrangement of cells and tissue matrix across many length scales. Contemporary capabilities to quantify tissue architecture, connectivity and cell relationships are however fundamentally constrained by a lack of 3D analytical platforms with appropriate resolution, penetration, structural differentiation, consistency, volumetric analysis capability and sample throughput. Structural analysis of tissues, whether for research or diagnostic purposes, remains overwhelmingly bounded and constrained by microscopic examination of relatively sparse 2D tissue sections, providing only a snapshot from which 3D spatial relationships can only be inferred. Therefore, whilst 3D medical imaging is commonplace, microscopic tissue structure analysis (i.e., histology) remains overwhelmingly wedded to  200-year-old practices of microscopic 2D examination of tissue sections.
Recent advances
We have demonstrated previously that X-ray imaging by micro-computed tomography (μCT) allows non-invasive 3D imaging of the microstructure of standard tissue biopsies [1]. This yields details comparable to two-dimensional (2D) optical microscope sections but for the whole tissue volume, which can for example overturn misconceptions of disease development based on 2D assessment. One exemplar is the pathogenesis of idiopathic pulmonary fibrosis [2], where 3D structural insight into co-localisation of tissue features and dysmorphia within substantive tissue volumes suggested previously unrecognised fibroblast foci plasticity. Based on this encouraging μCT results for soft tissues, in collaboration with an industrial partner, we developed a custom-design and soft-tissue optimised μCT scanner [3]. Currently, we are establishing the foundations for routine 3D X-ray histology [4], including new X-ray equipment and standardised & automated workflows, where sample throughput will be increased and scan times reduced, providing the foundations for day-to-day 3D X-ray histology.
Future directions
Applicable to vast existing sample archives and a wide range of soft tissue types including musculoskeletal tissues, the technology will open new research areas, such as large-scale 3D histological phenotyping (i.e., histomics). Furthermore, 3D X-ray histology can translate directly into next-generation clinical image-based diagnostics and patient stratification using artificial intelligence and deep learning, and time-critical intraoperative 3D examination of tissue biopsies will become a realistic future target in this research programme. Here, we will present first results of our 3D X-ray histology approach and portray a vision, how high-throughput and non-destructive 3D histological assessment can offer new opportunities in basic biomedical and translational research, following our ambition to provide a day-to-day imaging tool that complements and augments standard 2D histology.
BibTeX:
@conference{Schneider2019,
  author = {Schneider, P.},
  title = {3D X-ray histology: micro-CT goes medical},
  booktitle = {Annual Congress of the European Society of Biomechanics (ESB)},
  year = {2019},
  url = {https://www.conftool.org/esb2019/index.php?page=browseSessions&form_session=112}
}
Schneider P, Katsamenis O, Thomas G, Page A, Cox S, Sinclair I and Lackie P (2019), "Why Every Hospital Should Have a Micro-CT: 3D X-Ray Histology, Let’s Go Beyond Standard 2D Histology", In 22nd International Workshop on Quantitative Musculoskeletal Imaging (QMSKI). Lake Louise, Alberta, Canada, February, 2019.
Abstract: Living structures are an intricate threedimensional (3D) arrangement of cells and tissue matrix across many length scales. Contemporary capabilities to quantify tissue architecture, connectivity and cell relationships are however fundamentally constrained by a lack of 3D analytical platforms with appropriate resolution, penetration, structural differentiation, consistency, volumetric analysis capability and sample throughput. Structural analysis of tissues, whether for research or diagnostic purposes, remains overwhelmingly bounded and constrained by microscopic examination of relatively sparse 2D tissue sections, providing only a snapshot from which 3D spatial relationships can only be inferred. Therefore, whilst 3D medical imaging is commonplace, microscopic tissue structure analysis (i.e., histology) remains overwhelmingly wedded to 200-year-old practices of microscopic 2D examination of tissue sections. We have demonstrated previously that Xray imaging by micro-computed tomography (μCT) allows non-invasive 3D imaging of
the microstructure of standard tissue biopsies 1. This yields details comparable to twodimensional (2D) optical microscope sections but for the whole tissue volume, which can for example overturn misconceptions of disease development based on 2D assessment. One exemplar is the pathogenesis of idiopathic pulmonary fibrosis 2, where 3D structural insight into co-localisation of tissue features and dysmorphia within substantive tissue volumes suggested previously unrecognised fibroblast foci plasticity.
Based on this encouraging μCT results for soft tissues, in collaboration with an industrial partner, we developed a customdesign and soft-tissue optimised μCT scanner (Wellcome Trust Pathfinder Award, 2016- 17). Currently, we are establishing the foundations for routine 3D X-ray histology (Wellcome Trust Biomedical Resource and Technology Development, 2019-2022), including new X-ray equipment and standardised & automated workflows, where sample throughput will be increased and scan times reduced, providing the foundations for day-to-day 3D X-ray histology. Applicable to vast existing sample archives and a wide range of soft tissue types including musculoskeletal tissues, the technology will open new research areas, such as largescale 3D histological phenotyping (i.e., histomics). Furthermore, 3D X-ray histology can translate directly into next-generation clinical image-based diagnostics and patient stratification using artificial intelligence and deep learning, and time-critical intraoperative 3D examination of tissue biopsies will become a realistic future target in this research programme. Here, we will present first results of our 3D Xray histology approach and portray a vision, how high-throughput and non-destructive 3D histological assessment can offer new opportunities in basic biomedical and translational research, following our ambition to provide a day-to-day imaging tool that complements and augments standard 2D histology
BibTeX:
@conference{Schneider2019a,
  author = {Schneider, Philipp and Katsamenis, Orestis and Thomas, Gareth and Page, Anton and Cox, Simon and Sinclair, Ian and Lackie, Peter},
  title = {Why Every Hospital Should Have a Micro-CT: 3D X-Ray Histology, Let’s Go Beyond Standard 2D Histology},
  booktitle = {22nd International Workshop on Quantitative Musculoskeletal Imaging (QMSKI)},
  year = {2019},
  url = {https://www.conftool.org/esb2019/index.php?page=browseSessions&form_session=112}
}
Schneider P (2019), "Engineering, Medicine and Industry team up for technology development in biomedical imaging", In FortisNet 4th Annual Meeting. Southampton, UK, January, 2019.
BibTeX:
@conference{Schneider2019b,
  author = {Schneider, P.},
  title = {Engineering, Medicine and Industry team up for technology development in biomedical imaging},
  booktitle = {FortisNet 4th Annual Meeting},
  year = {2019},
  url = {https://cdn.southampton.ac.uk/assets/imported/transforms/content-block/UsefulDownloads_Download/503413EFFA6A49A49B1C84142EF10EA8/FortisNet%20IV%20branded%20summary%20slides%20for%20web.pdf#_ga=2.241580866.115032613.1559509370-1151691026.1549917520}
}
Created by JabRef on 03/06/2019.
Back to the main XRH page
Privacy Settings