Evidence map›Paper›PMID 37670097›Full record

ArticleCardiovascular engineering and technology2023

Patient-Specific Quantitative In-Vivo Assessment of Human Mitral Valve Leaflet Strain Before and After MitraClip Repair.

Natalie T Simonian, Hao Liu, Sneha Vakamudi, Mark J Pirwitz, Alison M Pouch, Joseph H Gorman, Robert C Gorman, Michael S Sacks

Abstract read
PubMed Publisher
In one paragraph

Article in Cardiovascular engineering and technology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Characterisation of global and regional mitral annular strains in an acute porcine model.Interdisciplinary cardiovascular and thoracic surgery · 2024
    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

8 authors at 2 institutions in 1 country.

Natalie T SimonianJames T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin , 201 East 24th St., Stop C0200, Austin, TX, 78712-1229, USA.
Hao LiuJames T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin , 201 East 24th St., Stop C0200, Austin, TX, 78712-1229, USA.
Sneha VakamudiAscension Texas Cardiovascular & Division of Cardiology, Department of Internal Medicine, Dell Medical School, University of Texas, Austin, TX, USA.
Mark J PirwitzAscension Texas Cardiovascular & Division of Cardiology, Department of Internal Medicine, Dell Medical School, University of Texas, Austin, TX, USA.
Alison M PouchGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Joseph H GormanGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Robert C GormanGorman Cardiovascular Research Group, Smilow Center for Translational Research, Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Michael S SacksJames T. Willerson Center for Cardiovascular Modeling and Simulation, The Oden Institute for Computational Engineering and Sciences and the Department of Biomedical Engineering, The University of Texas at Austin , 201 East 24th St., Stop C0200, Austin, TX, 78712-1229, USA. msacks@oden.utexas.edu.ORCID 0000-0002-3199-2204
The University of Texas at Austin · USUniversity of Pennsylvania · US

Funding

Quantitative Methods for Optimizing IMR RepairR01HL073021 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI GORMAN, ROBERT C, SACKS, MICHAEL S · 2004 to 2022
$7.6M
NIH HHS R01 HL073021
6 · The paper itself

Abstract

purposeMitral regurgitation (MR) is a highly prevalent and deadly cardiac disease characterized by improper mitral valve (MV) leaflet coaptation. Among the plethora of available treatment strategies, the MitraClip is an especially safe option, but optimizing its long-term efficacy remains an urgent challenge.

methodsWe applied our noninvasive image-based strain computation pipeline [1] to intraoperative transesophageal echocardiography datasets taken from ten patients undergoing MitraClip repair, spanning a range of MR etiologies and MitraClip configurations. We then analyzed MV leaflet strains before and after MitraClip implementation to develop a better understanding of (1) the pre-operative state of human regurgitant MV, and (2) the MitraClip's impact on the MV leaflet deformations.

resultsThe MV pre-operative strain fields were highly variable, underscoring both the heterogeneity of the MR in the patient population and the need for patient-specific treatment approaches. Similarly, there were no consistent overall post-operative strain patterns, although the average A2 segment radial strain difference between pre- and post-operative states was consistently positive. In contrast, the post-operative strain fields were better correlated to their respective pre-operative strain fields than to the inter-patient post-operative strain fields. This quantitative result implies that the patient specific pre-operative state of the MV guides its post-operative deformation, which suggests that the post-operative state can be predicted using pre-operative data-derived modelling alone.

conclusionsThe pre-operative MV leaflet strain patterns varied considerably across the range of MR disease states and after MitraClip repair. Despite large inter-patient heterogeneity, the post-operative deformation appears principally dictated by the pre-operative deformation state. This novel finding suggests that though the variation in MR functional state and MitraClip-induced deformation were substantial, the post-operative state can be predicted from the pre-operative data alone. This study suggests that, with use of larger patient cohort and corresponding long-term outcomes, quantitative predictive factors of MitraClip durability can be identified.

Indexed as

Echocardiography, Three-DimensionalHeart Valve Prosthesis ImplantationMitral Valve InsufficiencyEchocardiographyHumansMitral ValveTreatment OutcomeComputational modellingEchocardiographyMitraClipMitral regurgitationMitral valvePatient-specific

Identifiers

PMID37670097
OpenAlexW4386453086

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.