Evidence map›Paper›PMID 40287648›Full record

ArticleRespiratory research2025

More accessible functional lung imaging: non-contrast CT-ventilation demonstrates strong association and agreement with PET-ventilation.

Hilary L Byrne, Nina Eikelis, Jonathan Dusting, Andreas Fouras, Paul J Keall, Piraveen Pirakalathanan

Abstract readComparative Study
In one paragraph

Article in Respiratory research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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4 · The record

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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

6 authors.

Hilary L ByrneImage X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Nina Eikelis4DMedical Ltd, Melbourne, Australia. neikelis@4dmedical.com.
Jonathan Dusting4DMedical Ltd, Melbourne, Australia.
Andreas Fouras4DMedical Ltd, Melbourne, Australia.
Paul J KeallImage X Institute, Sydney School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Piraveen Pirakalathanan4DMedical Ltd, Melbourne, Australia.

Funding

Australian Government fellowship REDIF147Cancer Institute NSW Translational Program Grant 2019/TPG2165
6 · The paper itself

Abstract

backgroundComputed Tomography (CT) ventilation imaging (CTVI) is an emerging ventilation imaging technique. CTVI implementations have been widely validated against alternative ventilation imaging techniques but have been limited to clinical research only. The first CTVI commercial product, CT LVAS (4DMedical, Melbourne, Australia), was recently released enabling its use in clinical practice. This study quantitatively compares ventilation images from CT LVAS and previously validated research CTVI algorithms to Galligas PET ventilation.

methods16 patients with Galligas PET and paired inhale/exhale breath-hold CT images were taken from a publicly available dataset on The Cancer Imaging Archive. Ventilation images were produced using CT LVAS and two previously published algorithms: (1) utilising the Hounsfield Unit difference (CTVI_HU); and (2) utilising the Jacobian determinant (CTVI_Jac). CTVI images were compared to the reference standard Galligas PET using Bland-Altman analysis of lobar ventilation, voxel-wise Spearman correlation, and Dice similarity coefficient (DSC) of regions of interest representing the top 85% and 15% of ventilation function.

resultsBland-Altman analysis showed overall bias of < 0.01% for all CTVI methods (95% confidence interval: ±7.4% for CT LVAS, ± 9.1% for CTVI_HU, ± 7.9% for CTVI_Jac). The mean Spearman correlation between CTVI and Galligas PET was 0.61 ± 0.14 (p < 0.01) for CT LVAS, 0.68 ± 0.10 (p < 0.01) for CTVI_HU, and 0.57 ± 0.15 (p < 0.01) for CTVI_Jac. The mean DSC for the top 85% was 0.91 ± 0.03 for CT LVAS, 0.92 ± 0.02 for CTVI_HU, and 0.91 ± 0.03 for CTVI_Jac, with the DSC for CTVI_HU significantly higher than the other two CTVI methods. The DSC for the top 15% was 0.47 ± 0.17 for CT LVAS, 0.53 ± 0.16 for CTVI_HU, and 0.47 ± 0.18 for CTVI_Jac.

conclusionsIn a comparison to Galligas PET ventilation imaging, CT LVAS performs similarly to previous CTVI methods. Bland-Altman analysis for quantification of lobar ventilation demonstrates negligible bias. Mean voxel-wise Spearman correlations are moderate to good. DSC of functionally thresholded lung regions are similar for all CTVI methods. These results warrant further investigation of CT LVAS as a readily available ventilation imaging tool in disease characterisation, lung health assessment, and surgical and targeted treatment planning.

trial registrationAustralian New Zealand Clinical Trials Registry (ANZCTR) registration number ACTRN12612000775819, registered on 23/07/2012.

Indexed as

LungLung NeoplasmsPositron-Emission TomographyPulmonary VentilationTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedFunctional imagingLungVentilation

Identifiers

PMID40287648
PMCPMC12034206

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LicenceCC BY-NC-ND
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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.