Evidence map›Paper›PMID 27909266›Full record

ArticleJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2017

Reliability of infarct volumetry: Its relevance and the improvement by a software-assisted approach.

Felix Friedländer, Ferdinand Bohmann, Max Brunkhorst, Ju-Hee Chae, Kavi Devraj, Yvette Köhler, Peter Kraft, Hannah Kuhn, Alexandra Lucaciu, Sebastian Luger and 7 more

Abstract read
In one paragraph

Article in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  7. Machine learning based analysis of stroke lesions on mouse tissue sections.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
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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

17 authors.

Felix Friedländer1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Ferdinand Bohmann1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Max Brunkhorst1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Ju-Hee Chae1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Kavi Devraj1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Yvette Köhler2 Department of General Pharmacology and Toxicology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Peter Kraft3 Department of Neurology, University Hospital of Würzburg, Würzburg, Germany.
Hannah Kuhn1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Alexandra Lucaciu1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Sebastian Luger1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Waltraud Pfeilschifter1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Rebecca Sadler4 Institute for Stroke and Dementia Research, Hospital of the Ludwig-Maximilians-University, München, Germany.
Arthur Liesz4 Institute for Stroke and Dementia Research, Hospital of the Ludwig-Maximilians-University, München, Germany.
Karolina Scholtyschik3 Department of Neurology, University Hospital of Würzburg, Würzburg, Germany.
Leonie Stolz1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Rajkumar Vutukuri1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.
Robert Brunkhorst1 Department of Neurology, Hospital of the Goethe University Frankfurt, Frankfurt am Main, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite the efficacy of neuroprotective approaches in animal models of stroke, their translation has so far failed from bench to bedside. One reason is presumed to be a low quality of preclinical study design, leading to bias and a low a priori power. In this study, we propose that the key read-out of experimental stroke studies, the volume of the ischemic damage as commonly measured by free-handed planimetry of TTC-stained brain sections, is subject to an unrecognized low inter-rater and test-retest reliability with strong implications for statistical power and bias. As an alternative approach, we suggest a simple, open-source, software-assisted method, taking advantage of automatic-thresholding techniques. The validity and the improvement of reliability by an automated method to tMCAO infarct volumetry are demonstrated. In addition, we show the probable consequences of increased reliability for precision, p-values, effect inflation, and power calculation, exemplified by a systematic analysis of experimental stroke studies published in the year 2015. Our study reveals an underappreciated quality problem in translational stroke research and suggests that software-assisted infarct volumetry might help to improve reproducibility and therefore the robustness of bench to bedside translation.

Indexed as

SoftwareAnimalsBrainBrain InfarctionDisease Models, AnimalImage Processing, Computer-AssistedIschemic Attack, TransientMaleMice, Inbred C57BLReproducibility of ResultsSensitivity and SpecificityTranslational Research, Biomedicalexperimental strokeimage analysismiddle cerebral artery occlusionNeuroprotectionpower

Identifiers

PMID27909266
PMCPMC5536806

What OpenQuestion holds

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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.