Evidence map›Paper›PMID 31806499›Full record

ArticleUltrasound in medicine & biology2020

Physiological Motion Reduction Using Lagrangian Tracking for Electrode Displacement Elastography.

Robert M Pohlman, Tomy Varghese

Abstract read
In one paragraph

Article in Ultrasound in medicine & biology, 2020. 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. Article
  2. Adaptation of Dictionary Learning for Electrode Displacement ElastographyAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020
    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

2 authors.

Robert M PohlmanDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA. Electronic address: rpohlman2@wisc.edu.
Tomy VargheseDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, USA; Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA.

Funding

U.W. RADIOLOGICAL SCIENCES TRAINING PROGRAMT32CA009206 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI Bryan Patrick Bednarz · 1985 to 2026
$12.1M
Real-time Ultrasonic Monitoring of Tumor AblationR01CA112192 · NCI · UNIVERSITY OF WISCONSIN-MADISON · PI VARGHESE, TOMY · 2007 to 2017
$2.6M
NCI NIH HHS R01 CA112192NCI NIH HHS T32 CA009206
6 · The paper itself

Abstract

Minimally invasive treatments such as microwave ablation (MWA) have been growing in popularity for extending liver cancer survival rates in patients, when surgery is not an option. As a non-ionizing, real-time alternative to contrast-enhanced computed tomography, electrode displacement elastography (EDE) has shown promise as an imaging modality for MWA. Despite imaging efficacy, motion artifacts caused by physiological motion result in unintended speckle pattern variance, thereby inhibiting consistent and accurate ablated region visualization. To combat these unavoidable motion artifacts, a Lagrangian deformation tracking (LDT) approach based on freehand EDE was developed to track tissue movement and better define tissue properties. For validating LDT efficacy, a spherical inclusion phantom as well as seven in vivo data sets were processed, and strain tensor images were compared with identical time sampled images estimated using a traditional Eulerian approach. In vivo results revealed greater consistency among visualized LDT strain tensor images, with segmented ablated regions exhibiting standard deviation reductions of up to 98% when compared with Eulerian strain tensor images. Additionally, Lagrangian strain tensor images provided Dice coefficient improvements up to 25%, and success rates improved from approximately 50% to nearly 100% for ablated region visualization.

Indexed as

Ablation TechniquesArtifactsElasticity Imaging TechniquesHumansLiver NeoplasmsMicrowavesMotionElastographyElectrode displacement elastographyImaging microwave liver ablationsLagrangian description of motionMotion artifact reduction

Identifiers

PMID31806499
PMCPMC7241290

What OpenQuestion holds

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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.