Evidence map›Paper›PMID 39385845›Full record

ArticleEuropean heart journal. Imaging methods and practice2024

Quality control of cardiac magnetic resonance imaging segmentation, feature tracking, aortic flow, and native T1 analysis using automated batch processing in the UK Biobank study.

Sucharitha Chadalavada, Elisa Rauseo, Ahmed Salih, Hafiz Naderi, Mohammed Khanji, Jose D Vargas, Aaron M Lee, Alborz Amir-Kalili, Lisette Lockhart, Ben Graham and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in European heart journal. Imaging methods and practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Novel cardiovascular magnetic resonance strain heterogeneity phenotypes predict cardiovascular events: A prospective UK Biobank study.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025
    Article
  7. Prospective electrocardiographic and cardiovascular magnetic resonance alterations in the UK Biobank coronavirus disease 2019 repeat imaging study.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025
    Article
  8. Cardiac magnetic resonance imaging in the German National Cohort (NAKO): Automated segmentation of short-axis cine images and post-processing quality control.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    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

18 authors.

Sucharitha ChadalavadaWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0002-7854-5946
Elisa RauseoWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.
Ahmed SalihWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.
Hafiz NaderiWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0002-3217-780X
Mohammed KhanjiWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.
Jose D VargasDepartment of Cardiology, US Department of Veterans Affair Medical Center, Washington, D.C., USA.
Aaron M LeeWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0001-6008-5366
Alborz Amir-KaliliCircle Cardiovascular Imaging Inc., Calgary, Canada.
Lisette LockhartCircle Cardiovascular Imaging Inc., Calgary, Canada.
Ben GrahamCircle Cardiovascular Imaging Inc., Calgary, Canada.
Mihaela ChirvasaCircle Cardiovascular Imaging Inc., Calgary, Canada.
Kenneth FungWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0001-5271-1697
Jose PaivaWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.
Mihir M SanghviWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0002-1914-4149
Gregory G SlabaughDigital Environment Research Institute, Queen Mary University of London, London, UK.
Magnus T JensenWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.
Nay AungWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.ORCID https://orcid.org/0000-0001-5095-1611
Steffen E PetersenWilliam Harvey Research Institute, NIHR Barts Biomedical Research Centre, Queen Mary University of London, Charterhouse Square, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Automated algorithms are regularly used to analyse cardiac magnetic resonance (CMR) images. Validating data output reliability from this method is crucial for enabling widespread adoption. We outline a visual quality control (VQC) process for image analysis using automated batch processing. We assess the performance of automated analysis and the reliability of replacing visual checks with statistical outlier (SO) removal approach in UK Biobank CMR scans. Methods and results: We included 1987 CMR scans from the UK Biobank COVID-19 imaging study. We used batch processing software (Circle Cardiovascular Imaging Inc.-CVI42) to automatically extract chamber volumetric data, strain, native T1, and aortic flow data. The automated analysis outputs (∼62 000 videos and 2000 images) were visually checked by six experienced clinicians using a standardized approach and a custom-built R Shiny app. Inter-observer variability was assessed. Data from scans passing VQC were compared with a SO removal QC method in a subset of healthy individuals ( Conclusion: Automated image analysis using CVI42 prototypes for UK Biobank CMR scans demonstrated high quality. Larger UK Biobank data sets analysed using these automated algorithms do not require in-depth VQC. SO removal is sufficient as a QC measure, with operator discretion for visual checks based on population or research objectives.

Indexed as

automated image analysiscardiac magnetic resonance imagingmachine learningquality controlShiny app

Identifiers

PMID39385845
PMCPMC11462446

What OpenQuestion holds

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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.