Evidence map›Paper›PMID 27425150›Full record

ArticleUltrasound in medicine & biology2016

Fully Automated and Robust Tracking of Transient Waves in Structured Anatomies Using Dynamic Programming.

Zeynettin Akkus, Mahdi Bayat, Mathew Cheong, Kumar Viksit, Bradley J Erickson, Azra Alizad, Mostafa Fatemi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ultrasound in medicine & biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Trial
  2. Article
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

7 authors.

Zeynettin AkkusDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA; Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA. Electronic address: akkus.zeynettin@mayo.edu.
Mahdi BayatDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Mathew CheongDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Kumar ViksitDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Bradley J EricksonDepartment of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Azra AlizadDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA; Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
Mostafa FatemiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.

Funding

Classification of breast masses based on visco-elastic propertiesR01CA168575 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA, INSANA, MICHAEL F · 2013 to 2018
$2.5M
Combined Acoustic Imaging and Viscoelastic Parameters Estimation in Breast CancerR01CA148994 · NCI · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA · 2011 to 2015
$2.4M
Viscoelastic Parameters estimation and imaging for Thyroid Nodule differentiationR01EB017213 · NIBIB · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA, CHEN, SHIGAO · 2014 to 2017
$2.2M
Generalized waveform methods for breast viscoelasticity mappingR01CA174723 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA · 2014 to 2018
$1.8M
In Vivo Breast Imaging and Tissue Evaluation by Vibro-acoustic MethodsR01CA127235 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA · 2007 to 2011
$1.6M
Ultrasonic Techniques for Bladder Compliance MeasurementR01DK099231 · NIDDK · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA · 2013 to 2016
$979k
NCI NIH HHS R01 CA127235NCI NIH HHS R01 CA148994NCI NIH HHS R01 CA168575NCI NIH HHS R01 CA174723NIBIB NIH HHS R01 EB017213NIDDK NIH HHS R01 DK099231
6 · The paper itself

Abstract

Tissue stiffness is often linked to underlying pathology and can be quantified by measuring the mechanical transient transverse wave speed (TWS) within the medium. Time-of-flight methods based on correlation of the transient signals or tracking of peaks have been used to quantify the TWS from displacement maps obtained with ultrasound pulse-echo techniques. However, it is challenging to apply these methods to in vivo data because of tissue inhomogeneity, noise and artifacts that produce outliers. In this study, we introduce a robust and fully automated method based on dynamic programming to estimate TWS in tissues with known geometries. The method is validated using ultrasound bladder vibrometry data from an in vivo study. We compared the results of our method with those of time-of-flight techniques. Our method performs better than time-of-flight techniques. In conclusion, we present a robust and accurate TWS detection method that overcomes the difficulties of time-of-flight methods.

Indexed as

ArtifactsHumansImage Processing, Computer-AssistedUltrasonographyUrinary BladderUrinary Bladder DiseasesBladderDynamic programmingTime-of-flightUltrasound vibrometeryWall stiffnessWave tracking

Identifiers

PMID27425150
PMCPMC6494618

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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.