Evidence map›Paper›PMID 20378447›Full record

ArticleIEEE transactions on ultrasonics, ferroelectrics, and frequency control2010

3-D phantom and in vivo cardiac speckle tracking using a matrix array and raw echo data.

Brett Byram, Greg Holley, Doug Giannantonio, Gregg Trahey

Abstract read
In one paragraph

Article in IEEE transactions on ultrasonics, ferroelectrics, and frequency control, 2010. 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
–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

3 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Brett ByramDepartment of Biomedical Engineering, Duke University, Durham, NC, USA. bcb16@duke.edu
Greg Holley
Doug Giannantonio
Gregg Trahey

Funding

Acoustic Radiation Force Impulse (ARFI) Imaging of Cardiac TissueR37HL096023 · NHLBI · DUKE UNIVERSITY · PI TRAHEY, GREGG E. · 2009 to 2018
$5.2M
Training in Medical ImagingT32EB001040 · NIBIB · DUKE UNIVERSITY · PI NIGHTINGALE, KATHRYN RADABAUGH · 2003 to 2018
$4.4M
NHLBI NIH HHS 1R01HL096023-01NHLBI NIH HHS R37 HL096023NIBIB NIH HHS 5T32EB001040NIBIB NIH HHS T32 EB001040
6 · The paper itself

Abstract

Cardiac motion has been tracked using various methods, which vary in their invasiveness and dimensionality. One such noninvasive modality for cardiac motion tracking is ultrasound. Three-dimensional ultrasound motion tracking has been demonstrated using detected data at low volume rates. However, the effects of volume rate, kernel size, and data type (raw and detected) have not been sufficiently explored. First comparisons are made within the stated variables for 3-D speckle tracking. Volumetric data were obtained in a raw, baseband format using a matrix array attached to a high parallel receive beam count scanner. The scanner was used to acquire phantom and human in vivo cardiac volumetric data at 1000-Hz volume rates. Motion was tracked using phase-sensitive normalized cross-correlation. Subsample estimation in the lateral and elevational dimensions used the grid-slopes algorithm. The effects of frame rate, kernel size, and data type on 3-D tracking are shown. In general, the results show improvement of motion estimates at volume rates up to 200 Hz, above which they become stable. However, peak and pixel hopping continue to decrease at volume rates higher than 200 Hz. The tracking method and data show, qualitatively, good temporal and spatial stability (for independent kernels) at high volume rates.

Indexed as

Databases, FactualEchocardiography, Three-DimensionalHumansMovementPhantoms, ImagingReproducibility of Results

Identifiers

PMID20378447
PMCPMC3479244

What OpenQuestion holds

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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.