Evidence map›Paper›PMID 40152008›Full record

ArticleCatheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions2025

Quantitative Analysis of 3D Anatomy to Inform Planning of Ductal Arteriosus Stenting.

Mudit Gupta, Silvani Amin, Alana Cianciulli, Yuval Barak-Corren, Csaba Pinter, Hannah Dewey, Andras Lasso, William Russell, Stephanie Colello, Ari J Gartenberg and 6 more

Abstract read
In one paragraph

Article in Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. 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.

Mudit GuptaDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-8155-5897
Silvani AminDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Alana CianciulliDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Yuval Barak-CorrenDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Csaba PinterEBATINCA S.L., Las Palmas, Gran Canaria, Spain.
Hannah DeweyDepartment of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID 0009-0000-1225-3249
Andras LassoLaboratory for Percutaneous Surgery, School of Computing, Queen's University, Kingston, Canada.
William RussellDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Stephanie ColelloDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Ari J GartenbergDivision of Pediatric Cardiology, Akron Children's Hospital, Akron, Ohio, USA.ORCID 0000-0001-9509-2945
Vlad ObsekovDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Trevor WilliamsDivision of Cardiology, University of Colorado School of Medicine and Children's Hospital of Colorado, Aurora, Colorado, USA.
Elizabeth SilvestroDepartment of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
Michael L O'ByrneDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID 0000-0001-6023-1634
Andrew C GlatzDivision of Cardiology, Washington University School of Medicine and St. Louis Children's Hospital, St. Louis, Missouri, USA.
Matthew A JolleyDivision of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.ORCID 0000-0002-5626-0130

Funding

Training in Molecular Therapeutics for Pediatric CardiologyT32HL007915 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI Robert J Levy, JOSEPH W ROSSANO · 1999 to 2026
$13.4M
Computer Modeling of the Tricuspid Valve in Hypoplastic Left Heart SyndromeR01HL153166 · NHLBI · CHILDREN'S HOSP OF PHILADELPHIA · PI JOLLEY, MATTHEW · 2020 to 2024
$3.7M
NHLBI NIH HHS R01 HL153166NHLBI NIH HHS T32 HL007915This study was supported by NIH R01HL153166, an Additional Ventures Expansion Award, Additional Ventures Single Ventricle Research Fund, The Topolewski Endowed Chair at the Children's Hospital of Philadelphia, T32 HL0097915, CHOP Cardiac Center Research Grant.
6 · The paper itself

Abstract

backgroundDuctus arteriosus stenting (DAS) is used to palliate infants with ductal-dependent pulmonary blood flow (DD-PBF), however patent ductus arteriosus (PDA) anatomy can be complex and heterogenous.

aimsWe developed custom, open-source software to model and quantify PDA anatomy.

methodsWe retrospectively identified 33 neonates with DD-PBF with a CTA before DAS. A novel custom workflow was implemented in 3D Slicer and SlicerHeart to semi-automatically extract centerlines of the course of the PDA and surrounding vessels. 3D ductal length, diameter, curvature and tortuosity were automatically calculated (3D automatic) and compared to manually adjusted 3D measurements (3D semi-automatic), and manual measurements of PDA dimensions in 2D projectional angiograms before and after stent angioplasty.

resultsDuctal anatomy was successfully modeled and quantified in all subjects. 3D automatic and semi-automatic measurements of straight-line aortic to pulmonary artery length were not significantly different than 2D measurements. Semi-automatic 3D measurements were similar to 2D measurements of the total length. Minimum and maximum ductal diameters were not significantly different by 3D automatic and 2D measurements, however semi-automatic 3D diameters were significantly larger. Inter-reader reliability of ductal length and diameter was higher with manual adjustment of 3D centerlines compared to standard measurement of 2D angiograms. These differences were consistent across PGE doses between CTA and DAS.

conclusionsAutomatic PDA modeling is feasible and efficient, enabling reproducible quantification of ductal anatomy for procedural planning of DAS in patients with DD-PBF. Further development is needed as well as investigation of whether 3D modeling-derived measurements influence procedural duration or outcome.

Indexed as

Cardiac CatheterizationComputed Tomography AngiographyDuctus ArteriosusDuctus Arteriosus, PatentImaging, Three-DimensionalMultidetector Computed TomographyPatient-Specific ModelingRadiographic Image Interpretation, Computer-AssistedStentsFemaleHumansInfant, NewbornMaleModels, CardiovascularPredictive Value of TestsPulmonary Circulation3D modelingcongenital heart diseaseCT angiographyPDA stentquantification

Identifiers

PMID40152008
PMCPMC12162213

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Registered trials

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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.