Evidence map›Paper›PMID 36978751›Full record

ArticleBioengineering (Basel, Switzerland)2023

Pericoronary Adipose Tissue Radiomics from Coronary Computed Tomography Angiography Identifies Vulnerable Plaques.

Justin N Kim, Lia Gomez-Perez, Vladislav N Zimin, Mohamed H E Makhlouf, Sadeer Al-Kindi, David L Wilson, Juhwan Lee

Open access · goldFull text read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Justin N KimDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.ORCID 0000-0003-4713-8552
Lia Gomez-PerezDepartment of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA.
Vladislav N ZiminCardiovascular Imaging Core Laboratory, Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.
Mohamed H E MakhloufCardiovascular Imaging Core Laboratory, Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.ORCID 0000-0002-3592-2844
Sadeer Al-KindiCardiovascular Imaging Core Laboratory, Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA.
David L WilsonDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Juhwan LeeDepartment of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA.
Case Western Reserve University · USThe Ohio State University · US

Funding

Cardiovascular risk from comprehensive evaluation of the CT calcium score examR01HL165218 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI Sanjay Rajagopalan, DAVID Lynn WILSON · 2023 to 2026
$3.8M
Pericoronary fat: MACE risk from non-contrast CT and the role of iodine perfusion in contrast CTR01HL167199 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI Sanjay Rajagopalan, DAVID Lynn WILSON · 2023 to 2026
$3.1M
Computer assisted coronary artery stent interventionsR01HL143484 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI BEZERRA, HIRAM, WILSON, DAVID LYNN · 2018 to 2021
$2.9M
In vivo Characterization of Stents using Intravascular OCT ImagingR01HL114406 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI BEZERRA, HIRAM, ROLLINS, ANDREW MARTIN · 2013 to 2016
$1.7M
Coronary Plaque Characterization with Vascular OCT ImagingR21HL108263 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI COSTA, MARCO A, WILSON, DAVID LYNN · 2011 to 2012
$423k
System-independent quantitative cardiac CT perfusionR41HL144271 · NHLBI · BIOINVISION, INC. · PI WILSON, DAVID LYNN · 2018 to 2018
$224k
BIOMEDICAL ENGINEERING RESEARCH FACILITIESC06RR012463 · NCRR · CASE WESTERN RESERVE UNIVERSITY · PI KUTINA, KENNETH L · 1997 to 1997
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Case Western Reserve University C06 RR12463National Science Foundation 1937968NCRR NIH HHS C06 RR012463NHLBI NIH HHS R01 HL114406NHLBI NIH HHS R01 HL143484NHLBI NIH HHS R01 HL165218NHLBI NIH HHS R01 HL167199NHLBI NIH HHS R21 HL108263NHLBI NIH HHS R41 HL144271
6 · The paper itself

Abstract

Pericoronary adipose tissue (PCAT) features on Computed Tomography (CT) have been shown to reflect local inflammation and increased cardiovascular risk. Our goal was to determine whether PCAT radiomics extracted from coronary CT angiography (CCTA) images are associated with intravascular optical coherence tomography (IVOCT)-identified vulnerable-plaque characteristics (e.g., microchannels (MC) and thin-cap fibroatheroma (TCFA)). The CCTA and IVOCT images of 30 lesions from 25 patients were registered. The vessels with vulnerable plaques were identified from the registered IVOCT images. The PCAT-radiomics features were extracted from the CCTA images for the lesion region of interest (PCAT-LOI) and the entire vessel (PCAT-Vessel). We extracted 1356 radiomic features, including intensity (first-order), shape, and texture features. The features were reduced using standard approaches (e.g., high feature correlation). Using stratified three-fold cross-validation with 1000 repeats, we determined the ability of PCAT-radiomics features from CCTA to predict IVOCT vulnerable-plaque characteristics. In the identification of TCFA lesions, the PCAT-LOI and PCAT-Vessel radiomics models performed comparably (Area Under the Curve (AUC) ± standard deviation 0.78 ± 0.13, 0.77 ± 0.14). For the identification of MC lesions, the PCAT-Vessel radiomics model (0.89 ± 0.09) was moderately better associated than the PCAT-LOI model (0.83 ± 0.12). In addition, both the PCAT-LOI and the PCAT-Vessel radiomics model identified coronary vessels thought to be highly vulnerable to a similar standard (i.e., both TCFA and MC; 0.88 ± 0.10, 0.91 ± 0.09). The most favorable radiomic features tended to be those describing the texture and size of the PCAT. The application of PCAT radiomics can identify coronary vessels with TCFA or MC, consistent with IVOCT. Furthermore, the use of CCTA radiomics may improve risk stratification by noninvasively detecting vulnerable-plaque characteristics that are only visible with IVOCT.

Indexed as

coronary computed tomography angiographymachine learningmicrochannelmicrovesseloptical coherence tomographypericoronary adipose tissuethin-cap fibroatheroma

Identifiers

PMID36978751
PMCPMC10045206
OpenAlexW4324357631

What Socratic holds

Textfull text, public
LicenceCC BY
measurements read37
table measurements read3
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 Socratic graph.