Evidence map›Paper›PMID 38300772›Full record

ArticleIEEE transactions on bio-medical engineering2024

Virtual Shape-Editing of Patient-Specific Vascular Models Using Regularized Kelvinlets.

Jonathan Pham, Fanwei Kong, Doug L James, Alison L Marsden

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.2field-weighted citation impact, top 15% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Thoracic Aortic Shape: A Data-Driven Scale Space Approach.medRxiv : the preprint server for health sciences · 2025
    Article
  2. Article
  3. 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

4 authors at 1 institution in 1 country.

Jonathan Pham
Fanwei Kong
Doug L James
Alison L Marsden
Stanford University · US

Funding

Comprehensive CT Guided Coronary Artery Bypass Graft SurgeryR01HL141712 · NHLBI · STANFORD UNIVERSITY · PI NIEMAN, KOEN · 2019 to 2023
$3.5M
Uncertainty aware virtual treatment planning for peripheral pulmonary artery stenosisR01HL167516 · NHLBI · STANFORD UNIVERSITY · PI Jeffrey A. Feinstein, Alison L Marsden · 2023 to 2026
$2.7M
Enabling reliable cardiovascular simulations via uncertainty quantificationR01EB018302 · NIBIB · STANFORD UNIVERSITY · PI MARSDEN, ALISON L · 2016 to 2019
$1.7M
SCH: INT: A Virtual Surgery Simulator to Accelerate Medical Training in Cardiovascular Disease R01EB029362 · NIBIB · STANFORD UNIVERSITY · PI MARSDEN, ALISON L · 2019 to 2022
$1.4M
Automated data curation to ensure model credibility in the Vascular Model RepositoryR01LM013120 · NLM · STANFORD UNIVERSITY · PI MARSDEN, ALISON L · 2019 to 2021
$1.0M
NHLBI NIH HHS R01 HL141712NHLBI NIH HHS R01 HL167516NIBIB NIH HHS R01 EB018302NIBIB NIH HHS R01 EB029362NLM NIH HHS R01 LM013120
6 · The paper itself

Abstract

objectiveCardiovascular diseases, and the interventions performed to treat them, can lead to changes in the shape of patient vasculatures and their hemodynamics. Computational modeling and simulations of patient-specific vascular networks are increasingly used to quantify these hemodynamic changes, but they require modifying the shapes of the models. Existing methods to modify these shapes include editing 2D lumen contours prescribed along vessel centerlines and deforming meshes with geometry-based approaches. However, these methods can require extensive by-hand prescription of the desired shapes and often do not work robustly across a range of vascular anatomies. To overcome these limitations, we develop techniques to modify vascular models using physics-based principles that can automatically generate smooth deformations and readily apply them across different vascular anatomies.

methodsWe adapt Regularized Kelvinlets, analytical solutions to linear elastostatics, to perform elastic shape-editing of vascular models. The Kelvinlets are packaged into three methods that allow us to artificially create aneurysms, stenoses, and tortuosity.

resultsOur methods are able to generate such geometric changes across a wide range of vascular anatomies. We demonstrate their capabilities by creating sets of aneurysms, stenoses, and tortuosities with varying shapes and sizes on multiple patient-specific models.

conclusionOur Kelvinlet-based deformers allow us to edit the shape of vascular models, regardless of their anatomical locations, and parametrically vary the size of the geometric changes. SIGNIFICANCE: These methods will enable researchers to more easily perform virtual-surgery-like deformations, computationally explore the impact of vascular shape on patient hemodynamics, and generate synthetic geometries for data-driven research.

Indexed as

Models, CardiovascularBlood VesselsComputer SimulationHemodynamicsHumansPatient-Specific Modeling

Identifiers

PMID38300772
PMCPMC11138343
OpenAlexW4391430015

What Socratic holds

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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 Socratic graph.