Evidence map›Paper›PMID 34023269›Full record

ArticleJACC. Cardiovascular imaging2021

Prognostic Value of Pulmonary Transit Time and Pulmonary Blood Volume Estimation Using Myocardial Perfusion CMR.

Andreas Seraphim, Kristopher D Knott, Katia Menacho, Joao B Augusto, Rhodri Davies, Iain Pierce, George Joy, Anish N Bhuva, Hui Xue, Thomas A Treibel and 7 more

Open access · hybridAbstract read
In one paragraph

Article in JACC. Cardiovascular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
  2. Trial
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  11. Review
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  13. Imaging of Congestion in Cardio-renal Syndrome.Current heart failure reports · 2025
    Review
  14. Characterizing extravascular lung water-A dual-contrast agent extracellular volume approach by cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Association of pulmonary transit time by cardiac magnetic resonance with heart failure hospitalization in a large prospective cohort with diverse cardiac conditions.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2023
    Article
  19. Article
  20. Cardiovascular magnetic resonance for evaluation of cardiac involvement in COVID-19: recommendations by the Society for Cardiovascular Magnetic Resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors at 4 institutions in 2 countries.

Andreas SeraphimInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Kristopher D KnottInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Katia MenachoInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Joao B AugustoInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Rhodri DaviesInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Iain PierceBarts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
George JoyBarts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Anish N BhuvaInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Hui XueNational Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, Maryland, USA.
Thomas A TreibelInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Jackie A CooperWilliam Harvey Research Institute, Queen Mary University of London, United Kingdom.
Steffen E PetersenBarts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom; William Harvey Research Institute, Queen Mary University of London, United Kingdom.
Marianna FontanaInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Royal Free Hospital, Pond Street, London, United Kingdom.
Alun D HughesInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom.
James C MoonInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom.
Charlotte ManistyInstitute of Cardiovascular Science, University College London, Gower Street, London, United Kingdom; Barts Heart Centre, St Bartholomew's Hospital, West Smithfield, London, United Kingdom. Electronic address: c.manisty@ucl.ac.uk.
Peter KellmanNational Heart, Lung, and Blood Institute, National Institutes of Health, DHHS, Bethesda, Maryland, USA. Electronic address: kellmanp@nhlbi.nih.gov.
University College London · GBSt Bartholomew's Hospital · GBNational Heart Lung and Blood Institute · USQueen Mary University of London · GB

Funding

Gadgetron Global Network and Intelligence Computing: Clinical Imaging Application Development and Software InfrastructureZIAHL006214 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI KELLMAN, PETER · 2016 to 2025
$7.3M
Gadgetron Global Network and Artificial Intelligence Powered Cardiac ImagingZIAHL006242 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI KELLMAN, PETER · 2019 to 2023
$2.2M
British Heart Foundation FS/18/21/33447British Heart Foundation FS/18/83/34025British Heart Foundation FS/19/35/34374Intramural NIH HHS ZIA HL006214Intramural NIH HHS ZIA HL006242
6 · The paper itself

Abstract

objectivesThe purpose of this study was to explore the prognostic significance of PTT and PBVi using an automated, inline method of estimation using CMR.

backgroundPulmonary transit time (PTT) and pulmonary blood volume index (PBVi) (the product of PTT and cardiac index), are quantitative biomarkers of cardiopulmonary status. The development of cardiovascular magnetic resonance (CMR) quantitative perfusion mapping permits their automated derivation, facilitating clinical adoption.

methodsIn this retrospective 2-center study of patients referred for clinical myocardial perfusion assessment using CMR, analysis of right and left ventricular cavity arterial input function curves from first pass perfusion was performed automatically (incorporating artificial intelligence techniques), allowing estimation of PTT and subsequent derivation of PBVi. Association with major adverse cardiovascular events (MACE) and all-cause mortality were evaluated using Cox proportional hazard models, after adjusting for comorbidities and CMR parameters.

resultsA total of 985 patients (67% men, median age 62 years [interquartile range (IQR): 52 to 71 years]) were included, with median left ventricular ejection fraction (LVEF) of 62% (IQR: 54% to 69%). PTT increased with age, male sex, atrial fibrillation, and left atrial area, and reduced with LVEF, heart rate, diabetes, and hypertension (model r

conclusionsPulmonary transit time (and its derived parameter pulmonary blood volume index), measured automatically without user interaction as part of CMR perfusion mapping, independently predicted adverse cardiovascular outcomes. These biomarkers may offer additional insights into cardiopulmonary function beyond conventional predictors including ejection fraction.

Indexed as

Artificial IntelligenceVentricular Function, LeftBlood VolumeFemaleHumansMagnetic Resonance Imaging, CineMagnetic Resonance SpectroscopyMaleMiddle AgedPerfusionPredictive Value of TestsPrognosisRetrospective StudiesRisk FactorsStroke Volumefirst pass perfusionoutcomespulmonary blood volume

Identifiers

PMID34023269
PMCPMC8560640
OpenAlexW3162182815

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.