Evaluating the feasibility of region-of-interest X-ray phase contrast imaging for lung cancer diagnostics

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dc.contributor.authorCostello, L.
dc.contributor.authorDonnelley, M.
dc.contributor.authorNesterets, Y.
dc.contributor.authorAhlers, J.
dc.contributor.authorAlloo, S.
dc.contributor.authorHall, C.
dc.contributor.authorHausermann, D.
dc.contributor.authorKitchen, M.
dc.contributor.authorD’Amico, L.
dc.contributor.authorMorgan, K.
dc.date.issued2025
dc.description.abstractLung cancer is one of the world’s deadliest cancers, often not diagnosed until it has spread beyond the lung, in part due to limitations in current medical imaging. Insufficient detail in diagnostic images can mean that patients require a biopsy to gain a full understanding of their prognosis. Here, we investigate the use of propagation-based X-ray phase-contrast imaging to capture high-resolution region-of-interest 3D Computed-Tomography (CT) images of suspicious masses, using a human chest phantom. In this study, we imaged a 3.5 cm region within the chest phantom, with each CT slice amounting to approximately 1% of the area of the whole chest at that height. X-ray energies ranging from 50 to 80 keV and propagation distances of 0 to 7 m were tested. We were able to quantify the experimental parameters that would be required to increase soft-tissue sensitivity and spatial resolution relative to conventional X-ray imaging methods, and hence improve the capacity for tumour characterisation. Our results suggest that propagation-based phase-contrast region-of-interest CT imaging could enable better tumour visualisation, which may aid in earlier detection and a better outcome for lung cancer patients.
dc.description.statementofresponsibilityLucy Costello, Martin Donnelley, Yakov Nesterets, Jannis Ahlers, Samantha Alloo, Chris Hall, Daniel Hausermann, Marcus Kitchen, Lorenzo D'Amico, Kaye Morgan
dc.identifier.citationScientific Reports, 2025; 15(1):19881-1-19881-12
dc.identifier.doi10.1038/s41598-025-04509-z
dc.identifier.issn2045-2322
dc.identifier.issn2045-2322
dc.identifier.orcidDonnelley, M. [0000-0002-5320-7756]
dc.identifier.urihttps://hdl.handle.net/2440/146164
dc.language.isoen
dc.publisherSpringer Science and Business Media LLC
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/2011204
dc.rights© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommo ns.org/licenses/by-nc-nd/4.0/.
dc.source.urihttps://doi.org/10.1038/s41598-025-04509-z
dc.subjectComputed tomography; Propagation-based CT; Local tomography; Chest phantom; Interior tomography
dc.subject.meshHumans
dc.subject.meshLung Neoplasms
dc.subject.meshTomography, X-Ray Computed
dc.subject.meshImaging, Three-Dimensional
dc.subject.meshFeasibility Studies
dc.subject.meshPhantoms, Imaging
dc.titleEvaluating the feasibility of region-of-interest X-ray phase contrast imaging for lung cancer diagnostics
dc.typeJournal article
pubs.publication-statusPublished

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