Evidence map›Paper›PMID 29627686›Full record

ArticleMedical image analysis2018

SiSSR: Simultaneous subdivision surface registration for the quantification of cardiac function from computed tomography in canines.

Davis M Vigneault, Amir Pourmorteza, Marvin L Thomas, David A Bluemke, J Alison Noble

Open access · greenAbstract read
In one paragraph

Article in Medical image analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. M-SiSSR: Regional Endocardial Function Using Multilabel Simultaneous Subdivision Surface Registration.Functional imaging and modeling of the heart : ... International Workshop, FIMH ..., proceedings. FIMH (Conference) · 2021
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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

5 authors at 4 institutions in 2 countries.

Davis M VigneaultInstitute of Biomedical Engineering, Department of Engineering, University of Oxford, United Kingdom; Department of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA; Tufts University School of Medicine, Sackler School of Graduate Biomedical Sciences, USA. Electronic address: davis.vigneault@gmail.com.
Amir PourmortezaDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA.
Marvin L ThomasDivision of Veterinary Resources, National Institutes of Health, USA.
David A BluemkeDepartment of Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, USA.
J Alison NobleInstitute of Biomedical Engineering, Department of Engineering, University of Oxford, United Kingdom.
National Institutes of Health Clinical Center · USNational Institutes of Health · USTufts University · USUniversity of Oxford · GB

Funding

Intramural NIH HHS Z99 CL999999
6 · The paper itself

Abstract

Recent improvements in cardiac computed tomography (CCT) allow for whole-heart functional studies to be acquired at low radiation dose (<2mSv) and high-temporal resolution (<100ms) in a single heart beat. Although the extraction of regional functional information from these images is of great clinical interest, there is a paucity of research into the quantification of regional function from CCT, contrasting with the large body of work in echocardiography and cardiac MR. Here we present the Simultaneous Subdivision Surface Registration (SiSSR) method: a fast, semi-automated image analysis pipeline for quantifying regional function from contrast-enhanced CCT. For each of thirteen adult male canines, we construct an anatomical reference mesh representing the left ventricular (LV) endocardium, obviating the need for a template mesh to be manually sculpted and initialized. We treat this generated mesh as a Loop subdivision surface, and adapt a technique previously described in the context of 3-D echocardiography to register these surfaces to the endocardium efficiently across all cardiac frames simultaneously. Although previous work performs the registration at a single resolution, we observe that subdivision surfaces naturally suggest a multiresolution approach, leading to faster convergence and avoiding local minima. We additionally make two notable changes to the cost function of the optimization, explicitly encouraging plausible biological motion and high mesh quality. Finally, we calculate an accepted functional metric for CCT from the registered surfaces, and compare our results to an alternate state-of-the-art CCT method.

Indexed as

AlgorithmsAnimalsCardiac Imaging TechniquesContrast MediaDogsIopamidolRadiographic Image Interpretation, Computer-AssistedTomography, X-Ray ComputedContrast MediaIopamidolCardiac computed tomographyLoop subdivision surfacePersonalized cardiac mesh generationRegional cardiac function

Identifiers

PMID29627686
PMCPMC5942600
OpenAlexW2795012042

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.