Evidence map›Paper›PMID 37060701›Full record

ArticleMedical image analysis2023

Strain estimation in aortic roots from 4D echocardiographic images using medial modeling and deformable registration.

Ankush Aggarwal, Peter Mortensen, Jilei Hao, Łukasz Kaczmarczyk, Albert T Cheung, Lourdes Al Ghofaily, Robert C Gorman, Nimesh D Desai, Joseph E Bavaria, Alison M Pouch

Open access · greenAbstract read
In one paragraph

Article in Medical image analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 17% 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

7 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Streamlining 4D Cardiac Image Workflows: Open-Source Tools for Segmentation, Registration, and Visualization.Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference) · 2025
    Article
  5. Article
  6. Article
  7. 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

10 authors at 3 institutions in 2 countries.

Ankush AggarwalGlasgow Computational Engineering Centre, James Watt School of Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, United Kingdom.
Peter MortensenGlasgow Computational Engineering Centre, James Watt School of Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, United Kingdom.
Jilei HaoDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Łukasz KaczmarczykGlasgow Computational Engineering Centre, James Watt School of Engineering, University of Glasgow, Glasgow, G12 8LT, Scotland, United Kingdom.
Albert T CheungDepartment of Anesthesiology, Perioperative and Pain Medicine, Stanford University, Stanford, CA, USA.
Lourdes Al GhofailyDepartment of Anesthesiology, University of Pennsylvania, Philadelphia, PA, USA.
Robert C GormanDepartment of Surgery, University of Pennsylvania, Philadelphia, PA, USA.
Nimesh D DesaiDepartment of Surgery, University of Pennsylvania, Philadelphia, PA, USA.
Joseph E BavariaDepartment of Surgery, University of Pennsylvania, Philadelphia, PA, USA.
Alison M PouchDepartment of Radiology, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA. Electronic address: pouch@pennmedicine.upenn.edu.
University of Pennsylvania · USUniversity of Glasgow · GBStanford Medicine · US

Funding

4D Multimodal Image-Based Modeling for Bicuspid Aortic Valve Repair SurgeryR01HL163202 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI Alison Marie Pouch · 2022 to 2026
$3.5M
A Platform for Outcomes Data Sharing and Pre-Operative Image-Guided Mechanistic Assessment for Bicuspid Aortic Valve Repair SurgeryK01HL141643 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI POUCH, ALISON MARIE · 2018 to 2022
$532k
NHLBI NIH HHS K01 HL141643NHLBI NIH HHS R01 HL163202
6 · The paper itself

Abstract

Even though the central role of mechanics in the cardiovascular system is widely recognized, estimating mechanical deformation and strains in-vivo remains an ongoing practical challenge. Herein, we present a semi-automated framework to estimate strains from four-dimensional (4D) echocardiographic images and apply it to the aortic roots of patients with normal trileaflet aortic valves (TAV) and congenital bicuspid aortic valves (BAV). The method is based on fully nonlinear shell-based kinematics, which divides the strains into in-plane (shear and dilatational) and out-of-plane components. The results indicate that, even for size-matched non-aneurysmal aortic roots, BAV patients experience larger regional shear strains in their aortic roots. This elevated strains might be a contributing factor to the higher risk of aneurysm development in BAV patients. The proposed framework is openly available and applicable to any tubular structures.

Indexed as

Bicuspid Aortic Valve DiseaseHeart Valve DiseasesAortaAorta, ThoracicAortic ValveEchocardiographyHumans4D echocardiographyAortic rootBicuspid aortic valveBiomechanicsStrain estimation

Identifiers

PMID37060701
PMCPMC10358753
OpenAlexW4362455043

What OpenQuestion holds

Textmetadata
LicenceTDM
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.