Evidence map›Paper›PMID 37984456›Full record

ArticleMagnetic resonance in medicine2024

Independent component analysis (ICA) applied to dynamic oxygen-enhanced MRI (OE-MRI) for robust functional lung imaging at 3 T.

Sarah H Needleman, Mina Kim, Jamie R McClelland, Josephine H Naish, Marta Tibiletti, James P B O'Connor, Geoff J M Parker

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2024. 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
0.5field-weighted citation impact, top 32% of its field
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, 2 citations in OpenAlex.

  1. Review
  2. 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

7 authors at 5 institutions in 1 country.

Sarah H NeedlemanCentre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.ORCID 0000-0001-6137-9075
Mina KimCentre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.ORCID 0000-0001-9779-4414
Jamie R McClellandCentre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.ORCID 0000-0002-4922-0093
Josephine H NaishBioxydyn Limited, Manchester, UK.ORCID 0000-0002-8980-8924
Marta TibilettiBioxydyn Limited, Manchester, UK.
James P B O'ConnorDivision of Radiotherapy and Imaging, Institute of Cancer Research, London, UK.ORCID 0000-0002-4044-8497
Geoff J M ParkerCentre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, UK.ORCID 0000-0003-2934-2234
Absynth Biologics (United Kingdom) · GBUniversity College London · GBInstitute of Cancer Research · GBManchester University NHS Foundation Trust · GBWellcome / EPSRC Centre for Interventional and Surgical Sciences · GB

Funding

Cancer Research UK 22746Wellcome Trust
6 · The paper itself

Abstract

purposeDynamic lung oxygen-enhanced MRI (OE-MRI) is challenging due to the presence of confounding signals and poor signal-to-noise ratio, particularly at 3 T. We have created a robust pipeline utilizing independent component analysis (ICA) to automatically extract the oxygen-induced signal change from confounding factors to improve the accuracy and sensitivity of lung OE-MRI.

methodsDynamic OE-MRI was performed on healthy participants using a dual-echo multi-slice spoiled gradient echo sequence at 3 T and cyclical gas delivery. ICA was applied to each echo within a thoracic mask. The ICA component relating to the oxygen-enhancement signal was automatically identified using correlation analysis. The oxygen-enhancement component was reconstructed, and the percentage signal enhancement (PSE) was calculated. The lung PSE of current smokers was compared with nonsmokers; scan-rescan repeatability, ICA pipeline repeatability, and reproducibility between two vendors were assessed.

resultsICA successfully extracted a consistent oxygen-enhancement component for all participants. Lung tissue and oxygenated blood displayed the opposite oxygen-induced signal enhancements. A significant difference in PSE was observed between the lungs of current smokers and nonsmokers. The scan-rescan repeatability and the ICA pipeline repeatability were good.

conclusionThe developed pipeline demonstrated sensitivity to the signal enhancements of the lung tissue and oxygenated blood at 3 T. The difference in lung PSE between current smokers and nonsmokers indicates a likely sensitivity to lung function alterations that may be seen in mild pathology, supporting future use of our methods in patient studies.

Indexed as

LungOxygenHumansMagnetic Resonance ImagingReproducibility of ResultsOxygendynamiclung functionoxygenationoxygen-enhanced MRIrepeatabilitysusceptibility contrast

Identifiers

PMID37984456
PMCPMC10952250
OpenAlexW4388852223

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.