Evidence map›Paper›PMID 37301099›Full record

ArticleComputers in biology and medicine2023

Evaluation of an open-source pipeline to create patient-specific left atrial models: A reproducibility study.

José Alonso Solís-Lemus, Tiffany Baptiste, Rosie Barrows, Charles Sillett, Ali Gharaviri, Giulia Raffaele, Orod Razeghi, Marina Strocchi, Iain Sim, Irum Kotadia and 6 more

Open access · hybridAbstract read
In one paragraph

Article in Computers in biology and medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
5.0field-weighted citation impact, top 4% 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

16 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Assessment of Left Atrial Fibrosis With Cardiac MRI.Journal of magnetic resonance imaging : JMRI · 2025
    Article
  5. Article
  6. Article
  7. Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. 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

16 authors at 3 institutions in 1 country.

José Alonso Solís-LemusSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK. Electronic address: jsolislemus@kcl.ac.uk.
Tiffany BaptisteSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Rosie BarrowsSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Charles SillettSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Ali GharaviriSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; Centre for Cardiovascular Science, University of Edinburgh, Old College, South Bridge, Edinburgh, EH8 9YL, Scotland, UK.
Giulia RaffaeleSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; School of Medical Education, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Orod RazeghiSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; Department of Haematology, NHS Blood and Transplant Centre, University of Cambridge, Cambridge, UK.
Marina StrocchiSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Iain SimSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Irum KotadiaSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Neil BodaghSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Daniel O'HareSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Mark O'NeillSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK.
Steven E WilliamsSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; Centre for Cardiovascular Science, University of Edinburgh, Old College, South Bridge, Edinburgh, EH8 9YL, Scotland, UK.
Caroline RoneySchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; Queen Mary University of London, Mile End Rd, Bethnal Green, London, E1 4NS, UK.
Steven NiedererSchool of Biomedical Engineering & Imaging Sciences, King's College London, St Thomas Hospital, London, SE1 7EH, UK; Alan Turing Institute, British Library, 96 Euston Rd, London, NW1 2DB, UK.
St Thomas' Hospital · GBNHS Blood and Transplant · GBTuring Institute · GB

Funding

Using Atrial Mechanics To Identify Fibrosis In Patients with Atrial FibrillationR01HL152256 · NHLBI · STANFORD UNIVERSITY · PI ENNIS, DANIEL B · 2020 to 2023
$2.8M
British Heart Foundation FS/20/26/34952British Heart Foundation PG/13/37/30280British Heart Foundation PG/15/91/31812NHLBI NIH HHS R01 HL152256Wellcome TrustWellcome Trust WT 203148/Z/16/Z
6 · The paper itself

Abstract

This work presents an open-source software pipeline to create patient-specific left atrial models with fibre orientations and a fibrDEFAULTosis map, suitable for electrophysiology simulations, and quantifies the intra and inter observer reproducibility of the model creation. The semi-automatic pipeline takes as input a contrast enhanced magnetic resonance angiogram, and a late gadolinium enhanced (LGE) contrast magnetic resonance (CMR). Five operators were allocated 20 cases each from a set of 50 CMR datasets to create a total of 100 models to evaluate inter and intra-operator variability. Each output model consisted of: (1) a labelled surface mesh open at the pulmonary veins and mitral valve, (2) fibre orientations mapped from a diffusion tensor MRI (DTMRI) human atlas, (3) fibrosis map extracted from the LGE-CMR scan, and (4) simulation of local activation time (LAT) and phase singularity (PS) mapping. Reproducibility in our pipeline was evaluated by comparing agreement in shape of the output meshes, fibrosis distribution in the left atrial body, and fibre orientations. Reproducibility in simulations outputs was evaluated in the LAT maps by comparing the total activation times, and the mean conduction velocity (CV). PS maps were compared with the structural similarity index measure (SSIM). The users processed in total 60 cases for inter and 40 cases for intra-operator variability. Our workflow allows a single model to be created in 16.72 ± 12.25 min. Similarity was measured with shape, percentage of fibres oriented in the same direction, and intra-class correlation coefficient (ICC) for the fibrosis calculation. Shape differed noticeably only with users' selection of the mitral valve and the length of the pulmonary veins from the ostia to the distal end; fibrosis agreement was high, with ICC of 0.909 (inter) and 0.999 (intra); fibre orientation agreement was high with 60.63% (inter) and 71.77% (intra). The LAT showed good agreement, where the median ± IQR of the absolute difference of the total activation times was 2.02 ± 2.45 ms for inter, and 1.37 ± 2.45 ms for intra. Also, the average ± sd of the mean CV difference was -0.00404 ± 0.0155 m/s for inter, and 0.0021 ± 0.0115 m/s for intra. Finally, the PS maps showed a moderately good agreement in SSIM for inter and intra, where the mean ± sd SSIM for inter and intra were 0.648 ± 0.21 and 0.608 ± 0.15, respectively. Although we found notable differences in the models, as a consequence of user input, our tests show that the uncertainty caused by both inter and intra-operator variability is comparable with uncertainty due to estimated fibres, and image resolution accuracy of segmentation tools.

Indexed as

Atrial FibrillationFibrosisHeart AtriaHumansMagnetic Resonance ImagingPredictive Value of TestsReproducibility of ResultsAtrial imagingCardiac electrophysiologyDigital twinsImage analysisPatient-specific modellingReproducibility

Identifiers

PMID37301099
PMCPMC10790305
OpenAlexW4380225101

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.