Evidence map›Paper›PMID 33196972›Full record

ArticleInternational journal of computer assisted radiology and surgery2021

CardIAc: an open-source application for myocardial strain analysis.

Ariel Hernán Curiale, Agustín Bernardo, Rodrigo Cárdenas, German Mato

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Article in International journal of computer assisted radiology and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ariel Hernán CurialeConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina. ariel.curiale@cab.cnea.gov.ar.ORCID http://orcid.org/0000-0003-3102-4374
Agustín BernardoDepartamento de Física Médica, Centro Atómico Bariloche e Instituto Balseiro, Av. Bustillo 9500, R8402AGP, San Carlos de Bariloche, Río Negro, Argentina.
Rodrigo CárdenasConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.
German MatoConsejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina.

Funding

CONICET PIP 112 201301 00256
6 · The paper itself

Abstract

purposeThis paper presents CardIAc, an open-source application designed as an alternative to commercial software for left ventricle myocardial strain quantification in short-axis cardiac magnetic resonance images. The aim is to provide a useful extension for myocardial strain analysis that can be easily adapted to incorporate different strategies of motion tracking to improve the strain accuracy. In this way, users with programming skills can easily modify the code and adjust the program's performance according to their own scientific or clinical requirements. The software is intended for research and clinical use is not advised.

methodsCardIAc was developed as a 3D Slicer extension for an easy installation and usability. The main contribution of this article is to provide a general workflow, going from data and segmentation loading, 3D heart modeling, analysis and several options for visualization of the myocardial strain.

resultsCardIAc strain feature was evaluated on a public dataset (Cardiac Motion Analysis Challenge-STACOM 2011) of 15 volunteers, and a synthetic one generated from this real dataset. Results on the real dataset show that cardIAc achieves suitable accuracy for myocardial motion estimation with a median error of 3.66 mm. In particular, global strain curves show strong correlation with the bibliography for healthy patients and similar approaches. On the other hand, results on the synthetic dataset show a mean global error of 4.07%, 7.76% and 8.18% for circumferential, radial and longitudinal strain.

conclusionThis paper introduces a new open-source application for strain analysis distributed under a BSD-style open-source license. Results demonstrate the capability and merits of the proposed application for strain analysis.

Indexed as

MyocardiumSoftwareHeartHeart VentriclesHumansMagnetic Resonance ImagingMagnetic Resonance Imaging, CineModels, CardiovascularReproducibility of ResultsVentricular Function, Left3D Slicer extensionCardiac quantificationOpen sourceStrainStrain rate

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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.