Evidence map›Paper›PMID 31447108›Full record

ArticleBiophysical journal2019

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart.

Dongdong Deng, Adityo Prakosa, Julie Shade, Plamen Nikolov, Natalia A Trayanova

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Reply to: Stochastic virtual heart model predictions.Nature cardiovascular research · 2025
    Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. The Heart by Numbers.Biophysical journal · 2019
    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

5 authors at 1 institution in 2 countries.

Dongdong DengSchool of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning, China; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Adityo PrakosaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Julie ShadeDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Plamen NikolovDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
Natalia A TrayanovaDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland. Electronic address: ntrayanova@jhu.edu.
Johns Hopkins University · US

Funding

Virtual Electrophysiology LaboratoryDP1HL123271 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2013 to 2017
$4.0M
Simulation Guidance of Ablation Therapy for Persistent Atrial FibrillationU01HL141074 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI CALKINS, HUGH G, TRAYANOVA, NATALIA A. · 2018 to 2021
$3.1M
Infarct-related Ventricular Tachycardia Mechanisms: From Micro to ClinicalR01HL142496 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TRAYANOVA, NATALIA A. · 2019 to 2022
$3.1M
Exploration of Arrhythmogenic Triggers and Substrates in Heart FailureR01HL126802 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI EFIMOV, IGOR R, GORELIK, JULIA · 2016 to 2019
$2.8M
NHLBI NIH HHS DP1 HL123271NHLBI NIH HHS R01 HL126802NHLBI NIH HHS R01 HL142496NHLBI NIH HHS U01 HL141074
6 · The paper itself

Abstract

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs' 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients.

Indexed as

Patient-Specific ModelingHeart Conduction SystemHumansModels, CardiovascularMyocardial InfarctionUser-Computer Interface

Identifiers

PMID31447108
PMCPMC6990147
OpenAlexW2962938975

What OpenQuestion holds

Textmetadata
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.