Evidence map›Paper›PMID 41619974›Full record

ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance

Feasibility and reproducibility of semi-automated magnetic resonance angiography measurements of the thoracic aorta using commercial software.

Jason Craft, Amirhossein Moaddab, Naman Upadhyay, Roosha Parikh, Josh Y Cheng, Karl P Kunze, Radhouene Neji, Michaela Schmidt, Karli Pipitone, Amanda Leung and 7 more

Abstract readComparative Study
In one paragraph

Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

17 authors.

Jason CraftSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA. Electronic address: jason.craft@chsli.org.
Amirhossein MoaddabSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Naman UpadhyaySt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Roosha ParikhSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Josh Y ChengSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Karl P KunzeMR Research Collaborations, Siemens Healthcare Limited, Camberley, UK.
Radhouene NejiSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Michaela SchmidtSiemens Healthineers, Erlangen, Germany.
Karli PipitoneSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Amanda LeungSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Suzanne WeberSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Jonathan WeberSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Timothy CarterGood Samaritan University Hospital, Department of Cardiothoracic Surgery, West Islip, New York, USA.
Sylvia BisoSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Ann-Marie YamashitaSt. Francis Hospital and Heart Center, DeMatteis Cardiovascular Institute, Greenvale, New York, USA.
Claudia PrietoSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Millenium Institute for Intelligent Healthcare Engineering, Santiago, Chile.
Rene M BotnarSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK; School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Millenium Institute for Intelligent Healthcare Engineering, Santiago, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCenterline semi-automatic measurements (CSAM) of the thoracic aorta have been shown to reduce interobserver variability of diameter measurements. The purpose of this study is to demonstrate the feasibility and efficiency of non-expert CSAM using contrast-enhanced magnetic resonance angiography (CE-MRA) versus double oblique (DO) multiplanar reformation (MPR) measurements obtained by experts, and to assess CSAM failure rate in subjects with and without thoracic aortic disease (TAD).

methodsImage-based navigator (iNAV) and variable density sampling with Cartesian spiral-like trajectories (VD-CASPR) framework for non-rigid motion correction and image acceleration were utilized for inversion recovery gradient echo MRA. Thoracic MRA was obtained in 41 TAD subjects and 27 normals and independently analyzed by expert cardiologists for DO MPR measurements; one cardiovascular imaging fellow (CSAM1) obtained CSAM in all subjects; another (CSAM2) obtained CSAM in TAD patients. Nine prior MRA exams were analyzed for CSAM in seven subjects with stable aneurysms. Post-processing efficiency and intra/interobserver agreement were assessed at the sinus of Valsalva (SOV), sinotubular junction (STJ), and ascending aorta (AAO) using intra/interclass correlation coefficients. Contour failures were graded on a four-point scale: 1- failure of ≤25% vessel circumference; 2- 26-50% circumference failure; 3- 51-75% circumference failure; 4- >75% failure.

resultsCSAM1 failure rate was 13% and 14% in the TAD and normal cohorts, respectively (p = 0.78). CSAM 2 failure rate was 2% in the TAD cohort. Intraobserver agreement was excellent for both methods. SOV interobserver agreement with DO MPR performed the worst, with the lowest interclass correlation (ICC) for SOV major (vs physician 1) in the normal cohort (ICC = .69). Otherwise, agreement with DO MPR was near excellent. Major diameter interobserver agreement was excellent in the TAD cohort. Efficiency was highest for CSAM2. In stable TAD, baseline and follow-up major diameter measurements were not significantly different.

conclusionNon-expert MRA CSAM is feasible with excellent intraobserver and excellent to near excellent interobserver agreement at the STJ and AAO levels compared to expert DO MPR. CSAM failure rates varied significantly between non-expert readers; inter-study CSAM were overall precise.

Indexed as

Aorta, ThoracicAortic Aneurysm, ThoracicAortic DiseasesImage Interpretation, Computer-AssistedMagnetic Resonance AngiographySoftwareAdultAgedAutomationCase-Control StudiesContrast MediaFeasibility StudiesFemaleHumansMaleMiddle AgedContrast MediaImage-based navigatorMagnetic resonance angiographySemi-automated segmentationThoracic aortic aneurysmVariable density sampling

Identifiers

PMID41619974
PMCPMC13213861

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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.