Evidence map›Paper›PMID 33650227›Full record

ArticleJournal of magnetic resonance imaging : JMRI2021

Sensitivity of Myocardial Radiomic Features to Imaging Parameters in Cardiac MR Imaging.

Jihye Jang, Hossam El-Rewaidy, Long H Ngo, Jennifer Mancio, Ibolya Csecs, Jennifer Rodriguez, Patrick Pierce, Beth Goddu, Ulf Neisius, Warren Manning and 1 more

Abstract read
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Trial
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  13. Radiomics and deep learning for myocardial scar screening in hypertrophic cardiomyopathy.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2022
    Article
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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

11 authors.

Jihye JangDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-4333-1083
Hossam El-RewaidyDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Long H NgoDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Jennifer MancioDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Ibolya CsecsDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Jennifer RodriguezDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Patrick PierceDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Beth GodduDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Ulf NeisiusDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-4744-9166
Warren ManningDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.
Reza NezafatDepartment of Medicine (Cardiovascular Division), Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0002-1963-7138

Funding

Cardiovascular MRI Characterization of the Arrhythmogenic Heart in Nonischemic CardiomyopathyR01HL129185 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI NEZAFAT, REZA · 2015 to 2024
$6.4M
Gadolinium Free Cardiac MR Imaging of Scar and FibrosisR01HL154744 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI NEZAFAT, REZA · 2020 to 2023
$3.5M
Imaging Markers of Subclinical Cardiotoxicity in Breast CancerR01HL127015 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI NEZAFAT, REZA · 2016 to 2020
$3.5M
Myocardial Tissue Characterization with MR Relaxometry in Heart FailureR01HL129157 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI NEZAFAT, REZA · 2017 to 2020
$3.2M
American Heart Association 15EIA22710040National Institute of Health 1R01HL127015National Institute of Health 1R01HL129157National Institute of Health 1R01HL129185-01National Institute of Health 1R01HL154744NHLBI NIH HHS R01 HL127015NHLBI NIH HHS R01 HL129157NHLBI NIH HHS R01 HL129185NHLBI NIH HHS R01 HL154744
6 · The paper itself

Abstract

backgroundCardiac magnetic resonance (MR) images are often collected with different imaging parameters, which may impact the calculated values of myocardial radiomic features. PURPOSE: To investigate the sensitivity of myocardial radiomic features to changes in imaging parameters in cardiac MR images. STUDY TYPE: Prospective. POPULATION: A total of 11 healthy participants/five patients. FIELD STRENGTH/ SEQUENCE: A 3 T/cine balanced steady-state free-precession, T ASSESSMENT: Myocardial contours were manually delineated by experienced readers, and a total of 1023 radiomic features were extracted using PyRadiomics with 11 image filters and six feature families. STATISTICAL TESTS: Sensitivity was defined as the standardized mean difference (D effect size), and the robust features were defined at sensitivity < 0.2. Sensitivity analysis was performed on predefined sets of reproducible features. The analysis was performed using the entire cohort of 16 subejcts.

results64% of radiomic features were robust (sensitivity < 0.2) to changes in any imaging parameter. In qualitative sequences, radiomic features were most sensitive to changes in in-plane spatial resolution (spatial resolution: 0.6 vs. flip angle: 0.19, parallel imaging: 0.18, slice thickness: 0.07; P < 0.01 for all); in quantitative sequences, radiomic features were least sensitive to changes in spatial resolution (spatial resolution: 0.07 vs. slice thickness: 0.16, flip angle: 0.24; P < 0.01 for all). In an individual feature level, no singular feature family/image filter was identified as robust (sensitivity < 0.2) across sequences; however, highly sensitive features were predominantly associated with high-frequency wavelet filters across all sequences (32/50 features). DATA

conclusionIn cardiac MR, a considerable number of radiomic features are sensitive to changes in sequence parameters. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Indexed as

HeartMagnetic Resonance ImagingHumansMyocardiumProspective Studiescardiac MRMR imaging parametersradiomic featuressensitivity

Identifiers

PMID33650227
PMCPMC9190024

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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.