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ToolsMassimi, Lorenzo, Suaris, Tamara, Hagen, Charlotte K., Endrizzi, Marco, Munro, Peter R. T., Havariyoun, Glafkos, Hawker, P. M. Sam, Smit, Bennie, Astolfo, Alberto, Larkin, Oliver J., Waltham, Richard M., Shah, Zoheb, Duffy, Stephen W., Nelan, Rachel L., Peel, Anthony, Jones, J. Louise, Haig, Ian G., Bate, David and Olivo, Alessandro (2021) Detection of involved margins in breast specimens with X-ray phase-contrast computed tomography. Scientific Reports, 11. ISSN 2045-2322
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Abstract
Margins of wide local excisions in breast conserving surgery are tested through histology, which can delay results by days and lead to second operations. Detection of margin involvement intraoperatively would allow the removal of additional tissue during the same intervention. X-ray phase contrast imaging (XPCI) provides soft tissue sensitivity superior to conventional X-rays: we propose its use to detect margin involvement intraoperatively. We have developed a system that can perform phase-based computed tomography (CT) scans in minutes, used it to image 101 specimens approximately half of which contained neoplastic lesions, and compared results against those of a commercial system. Histological analysis was carried out on all specimens and used as the gold standard. XPCI-CT showed higher sensitivity (83%, 95% CI 69–92%) than conventional specimen imaging (32%, 95% CI 20–49%) for detection of lesions at margin, and comparable specificity (83%, 95% CI 70–92% vs 86%, 95% CI 73–93%). Within the limits of this study, in particular that specimens obtained from surplus tissue typically contain small lesions which makes detection more difficult for both methods, we believe it likely that the observed increase in sensitivity will lead to a comparable reduction in the number of re-operations.
| Item Type: | Article |
|---|---|
| Additional Information: | Acknowledgments This work is funded by the Wellcome Trust (Grant 200137/Z/15/Z). Alessandro Olivo is funded by the Royal Academy of Engineering under their “Chairs in Emerging Technologies” scheme. Charlotte K. Hagen and Marco Endrizzi are funded by the Royal Academy of Engineering under their “Research Fellowships” scheme. Peter R. T. Munro is funded by the Royal Society under their “University Research Fellowships” scheme. |
| Uncontrolled Keywords: | general ,/dk/atira/pure/subjectarea/asjc/1000 |
| Faculty \ School: | |
| UEA Research Groups: | Faculty of Medicine and Health Sciences > Research Centres > Metabolic Health |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 02 Nov 2022 14:30 |
| Last Modified: | 06 Jun 2024 15:20 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/89528 |
| DOI: | 10.1038/s41598-021-83330-w |
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