Evidence map›Paper›PMID 35845036›Full record

ArticleFrontiers in cardiovascular medicine2022

Improved Functional Assessment of Ischemic Severity Using 3D Printed Models.

Kranthi K Kolli, Sun-Joo Jang, Abdul Zahid, Alexandre Caprio, Seyedhamidreza Alaie, Amir Ali Amiri Moghadam, Patricia Xu, Robert Shepherd, Bobak Mosadegh, Simon Dunham

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 45% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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 1 institution in 1 country.

Kranthi K KolliDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Sun-Joo JangDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Abdul ZahidDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Alexandre CaprioDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Seyedhamidreza AlaieDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Amir Ali Amiri MoghadamDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Patricia XuDepartment of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, United States.
Robert ShepherdDepartment of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, United States.
Bobak MosadeghDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Simon DunhamDepartment of Radiology, Dalio Institute of Cardiovascular Imaging, Weill Cornell Medical College, New York, NY, United States.
Cornell University · US

Funding

Patient-Specific Coronary Hemodynamics by 3D PrintingR01HL118019 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI DUNHAM, SIMON, LIN, FAY YU-HUEI · 2013 to 2022
$5.8M
Gender-Specific Coronary Plaque Characteristics and Risk of Myocardial InfarctionR01HL115150 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI MIN, JAMES K · 2012 to 2016
$3.5M
Computerized Visualization and Prediction of Coronary Artery IschemiaR21HL132277 · NHLBI · WEILL MEDICAL COLL OF CORNELL UNIV · PI KUCEYESKI, AMY FRANCES, MIN, JAMES K · 2016 to 2017
$466k
NHLBI NIH HHS R01 HL115150NHLBI NIH HHS R01 HL118019NHLBI NIH HHS R21 HL132277
6 · The paper itself

Abstract

Objective: To develop a novel Methods: Twenty eight patients with varying degrees of coronary artery disease who underwent non-invasive CCTA scans and invasive fractional flow reserve (FFR) of their epicardial coronary arteries were included in this study. Coronary arteries were segmented and reconstructed from CCTA scans using Mimics (Materialize). The segmented models were then 3D printed using a Carbon M1 3D printer with urethane methacrylate (UMA) family of rigid resins. Physiological coronary circulation was modeled Results: There was a good positive correlation ( Conclusions: 3D printed patient-specific models can be used in a non-invasive

Indexed as

3D printingblood analog fluidcatheterizationCCTAfractional flow reservein vitroradiology

Identifiers

PMID35845036
PMCPMC9279862
OpenAlexW4283723810

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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 OpenQuestion graph.