Evidence map›Paper›PMID 23261655›Full record

ArticleJournal of neuroscience methods2013

Semi-automated method for estimating lesion volumes.

Hyun-Joo Park, Andre G Machado, Jessica Cooperrider, Havan Truong-Furmaga, Matthew Johnson, Vibhuti Krishna, Zhihong Chen, John T Gale

Abstract read
In one paragraph

Article in Journal of neuroscience methods, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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

8 authors.

Hyun-Joo ParkDepartment of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.
Andre G Machado
Jessica Cooperrider
Havan Truong-Furmaga
Matthew Johnson
Vibhuti Krishna
Zhihong Chen
John T Gale

Funding

Dentatothalamocortical electrical stimulation in post-stroke motor recoveryR01HD061363 · NICHD · CLEVELAND CLINIC LERNER COM-CWRU · PI MACHADO, ANDRE GUELMAN · 2010 to 2014
$1.5M
NICHD NIH HHS 5R01HD061363NICHD NIH HHS R01 HD061363
6 · The paper itself

Abstract

Accurately measuring the volume of tissue damage in experimental lesion models is crucial to adequately control for the extent and location of the lesion, variables that can dramatically bias the outcome of preclinical studies. Many of the current commonly used techniques for this assessment, such as measuring the lesion volume with primitive software macros and plotting the lesion location manually using atlases, are time-consuming and offer limited precision. Here we present an easy to use semi-automated computational method for determining lesion volume and location, designed to increase precision and reduce the manual labor required. We compared this novel method to currently used methods and demonstrate that this tool is comparable or superior to current techniques in terms of precision and has distinct advantages with respect to user interface, labor intensiveness and quality of data presentation.

Indexed as

AlgorithmsAnatomy, Cross-SectionalAnimalsAutomationBrainEndothelinsImage Processing, Computer-AssistedRatsSoftwareStereotaxic TechniquesStrokeTissue FixationEndothelins

Identifiers

PMID23261655
PMCPMC3570743

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.