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Potential assessment of lung samples by X-ray histology (XRH) during surgery

Potential assessment of lung samples by X-ray histology (XRH) during surgery
Potential assessment of lung samples by X-ray histology (XRH) during surgery
More than 25,000 operations to remove all or part of a patient’s lung take place in Europe each year. The full extent and type of changes in lung structure due to disease may not be evident until surgery is underway. Immediate microanatomical assessment of removed tissue can guide and inform the surgical team.
We explored the feasibility of using micro-computed tomography (µCT) based X-ray histology (XRH) for timely 3D histological imaging during surgery. Key criteria include (1) visualisation of relevant microanatomical structures (2) results in less than 20 minutes during the operation (3) rapid and effective presentation of the data-rich 3D images and (4) compatibility with current intra-operative and post-operative pathology protocols.
For protocol development, pig lung was used as it is similar in size and structure to human lung. Using optimised µCT scan conditions at our XRH facility in Southampton, consistent 3D imaging of fresh, unfixed peripheral lung samples was demonstrated (n=6), providing relevant microanatomical information in less than 10 minutes (Fig 1). Snap freezing and/or air-inflation of lung samples were also feasible within the time required. Both required additional preparation steps and could lead to over-inflation or affect preparation for routine wax histology, respectively. Short scan times minimised the impact of sample movement on image quality. A system for rapid, automated generation of user-friendly reports was developed. This brings together images and sample details for assessment, patient records and clinical team discussions. To streamline the integration of XRH with existing protocols, we scanned samples in standard containers used to transfer surgical samples to the pathology lab. This allows fast, non-invasive, non-contact scanning in a sealed container, reducing sample handling and avoiding contamination.
The rapid XRH data were judged to be of potential diagnostic quality by pathologists. This approach provides opportunities for future research and diagnostic use.
intra-operative, Lung histology, Lung microanatomy, Pathology, Sample handling, Reporting, micro-Computed Tomography
Konstantinopoulou, Elena
Katsamenis, Orestis L.
8553e7c3-d860-4b7a-a883-abf6c0c4b438
Broadbent, Bethany
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Chatelet, David
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Basford, Philip J
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Haig, Ian
8c3dc208-c92b-4229-ab67-08dda8b45d64
Roche, William
a5135b2d-cab5-481b-887a-78611fa00bff
Alzetani, Aiman
04d65796-5c8e-4c5b-aeeb-ea093c118f03
Schneider, Philipp
ca82320e-1f19-4c91-ada2-1c5a3cb2bd47
Lackie, Peter
4afbbe1a-22a6-4ceb-8cad-f3696dc43a7a
Konstantinopoulou, Elena
Katsamenis, Orestis L.
8553e7c3-d860-4b7a-a883-abf6c0c4b438
Broadbent, Bethany
0a3d8c25-ddd0-44da-98f7-7d86a85a6dad
Chatelet, David
6371fd7a-e274-4738-9ccb-3dd4dab32928
Basford, Philip J
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Haig, Ian
8c3dc208-c92b-4229-ab67-08dda8b45d64
Roche, William
a5135b2d-cab5-481b-887a-78611fa00bff
Alzetani, Aiman
04d65796-5c8e-4c5b-aeeb-ea093c118f03
Schneider, Philipp
ca82320e-1f19-4c91-ada2-1c5a3cb2bd47
Lackie, Peter
4afbbe1a-22a6-4ceb-8cad-f3696dc43a7a

Konstantinopoulou, Elena, Katsamenis, Orestis L., Broadbent, Bethany, Chatelet, David, Basford, Philip J, Haig, Ian, Roche, William, Alzetani, Aiman, Schneider, Philipp and Lackie, Peter (2020) Potential assessment of lung samples by X-ray histology (XRH) during surgery. 10th Annual Tomography for Scientific Advancement (ToScA) symposium, Online, Virtual. 2 pp .

Record type: Conference or Workshop Item (Poster)

Abstract

More than 25,000 operations to remove all or part of a patient’s lung take place in Europe each year. The full extent and type of changes in lung structure due to disease may not be evident until surgery is underway. Immediate microanatomical assessment of removed tissue can guide and inform the surgical team.
We explored the feasibility of using micro-computed tomography (µCT) based X-ray histology (XRH) for timely 3D histological imaging during surgery. Key criteria include (1) visualisation of relevant microanatomical structures (2) results in less than 20 minutes during the operation (3) rapid and effective presentation of the data-rich 3D images and (4) compatibility with current intra-operative and post-operative pathology protocols.
For protocol development, pig lung was used as it is similar in size and structure to human lung. Using optimised µCT scan conditions at our XRH facility in Southampton, consistent 3D imaging of fresh, unfixed peripheral lung samples was demonstrated (n=6), providing relevant microanatomical information in less than 10 minutes (Fig 1). Snap freezing and/or air-inflation of lung samples were also feasible within the time required. Both required additional preparation steps and could lead to over-inflation or affect preparation for routine wax histology, respectively. Short scan times minimised the impact of sample movement on image quality. A system for rapid, automated generation of user-friendly reports was developed. This brings together images and sample details for assessment, patient records and clinical team discussions. To streamline the integration of XRH with existing protocols, we scanned samples in standard containers used to transfer surgical samples to the pathology lab. This allows fast, non-invasive, non-contact scanning in a sealed container, reducing sample handling and avoiding contamination.
The rapid XRH data were judged to be of potential diagnostic quality by pathologists. This approach provides opportunities for future research and diagnostic use.

Text
ToScA2020_Lung_intraoperative_abstract_v.final - Author's Original
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Slideshow
ToScA2020_Lung_intraoperative_Oral_presentation_v.final
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More information

Published date: 3 September 2020
Venue - Dates: 10th Annual Tomography for Scientific Advancement (ToScA) symposium, Online, Virtual, 2020-09-03
Keywords: intra-operative, Lung histology, Lung microanatomy, Pathology, Sample handling, Reporting, micro-Computed Tomography

Identifiers

Local EPrints ID: 448231
URI: http://eprints.soton.ac.uk/id/eprint/448231
PURE UUID: 6819a4be-f436-403e-b730-dcea9649969d
ORCID for Orestis L. Katsamenis: ORCID iD orcid.org/0000-0003-4367-4147
ORCID for Philip J Basford: ORCID iD orcid.org/0000-0001-6058-8270
ORCID for Peter Lackie: ORCID iD orcid.org/0000-0001-7138-3764

Catalogue record

Date deposited: 15 Apr 2021 16:34
Last modified: 16 Apr 2021 01:44

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Contributors

Author: Elena Konstantinopoulou
Author: Bethany Broadbent
Author: David Chatelet
Author: Ian Haig
Author: William Roche
Author: Aiman Alzetani
Author: Philipp Schneider
Author: Peter Lackie ORCID iD

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