Evidence map›Paper›PMID 40481115›Full record

ArticleScientific reports2025

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

Lucy Costello, Martin Donnelley, Yakov Nesterets, Jannis Ahlers, Samantha Alloo, Chris Hall, Daniel Hausermann, Marcus Kitchen, Lorenzo D'Amico, Kaye Morgan

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Lucy CostelloSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia. lucy.costello@monash.edu.
Martin DonnelleyAdelaide Medical School and Robinson Research Institute, University of Adelaide, Adelaide, SA, 5000, Australia.
Yakov NesteretsCommonwealth Scientific and Industrial Research Organisation, Clayton, VIC, 3168, Australia.
Jannis AhlersSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia.
Samantha AllooSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia.
Chris HallAustralian Synchrotron, Imaging and Medical Beam Line (IMBL), Clayton, VIC, 3168, Australia.
Daniel HausermannAustralian Synchrotron, Imaging and Medical Beam Line (IMBL), Clayton, VIC, 3168, Australia.
Marcus KitchenSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia.
Lorenzo D'AmicoSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia.
Kaye MorganSchool of Physics and Astronomy, Monash University, Wellington Road, Clayton, VIC, 3800, Australia.

Funding

National Health and Medical Research Council (NMHRC) APP2011204
6 · The paper itself

Abstract

Lung 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.

Indexed as

Lung NeoplasmsTomography, X-Ray ComputedFeasibility StudiesHumansImaging, Three-DimensionalPhantoms, ImagingChest phantomComputed tomographyInterior tomographyLocal tomographyPropagation-based CT

Identifiers

PMID40481115
PMCPMC12144224

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.