Evidence map›Paper›PMID 26661203›Full record

ArticleJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2016

A benchmarking tool to evaluate computer tomography perfusion infarct core predictions against a DWI standard.

Carlo W Cereda, Søren Christensen, Bruce C V Campbell, Nishant K Mishra, Michael Mlynash, Christopher Levi, Matus Straka, Max Wintermark, Roland Bammer, Gregory W Albers and 2 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, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 1 pooled it
–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

78 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. A multicenter randomized controlled trial of endovascular therapy following imaging evaluation for ischemic stroke (DEFUSE 3).International journal of stroke : official journal of the International Stroke Society · 2017
    Trial
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18 more citing papers are in PubMed but not listed here.

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

12 authors.

Carlo W CeredaStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA Stroke Center, Neurocenter (EOC) of Southern Switzerland, Lugano, Switzerland.
Søren ChristensenStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Bruce C V CampbellDepartments of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Australia Department of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia.
Nishant K MishraStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Michael MlynashStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Christopher LeviDepartment of Neurology, John Hunter Hospital, University of Newcastle and Hunter Medical Research Institute, Newcastle, Australia.
Matus StrakaStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Max WintermarkStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Roland BammerStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Gregory W AlbersStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA.
Mark W ParsonsDepartment of Neurology, John Hunter Hospital, University of Newcastle and Hunter Medical Research Institute, Newcastle, Australia.
Maarten G LansbergStanford Stroke Center, Stanford University Medical Center, Stanford, CA, USA lansberg@stanford.edu.

Funding

Medical Research Council 1013719
6 · The paper itself

Abstract

Differences in research methodology have hampered the optimization of Computer Tomography Perfusion (CTP) for identification of the ischemic core. We aim to optimize CTP core identification using a novel benchmarking tool. The benchmarking tool consists of an imaging library and a statistical analysis algorithm to evaluate the performance of CTP. The tool was used to optimize and evaluate an in-house developed CTP-software algorithm. Imaging data of 103 acute stroke patients were included in the benchmarking tool. Median time from stroke onset to CT was 185 min (IQR 180-238), and the median time between completion of CT and start of MRI was 36 min (IQR 25-79). Volumetric accuracy of the CTP-ROIs was optimal at an rCBF threshold of <38%; at this threshold, the mean difference was 0.3 ml (SD 19.8 ml), the mean absolute difference was 14.3 (SD 13.7) ml, and CTP was 67% sensitive and 87% specific for identification of DWI positive tissue voxels. The benchmarking tool can play an important role in optimizing CTP software as it provides investigators with a novel method to directly compare the performance of alternative CTP software packages.

Indexed as

AlgorithmsBenchmarkingBrainCerebral InfarctionCerebrovascular CirculationComputed Tomography AngiographyDiffusion Magnetic Resonance ImagingHumansImage Processing, Computer-AssistedPredictive Value of TestsSoftwareStrokeTime Factorsbrain imagingbrain ischemiacerebral blood flow measurementCerebrovascular diseasediffusion weighted MRI

Identifiers

PMID26661203
PMCPMC5076783

What OpenQuestion holds

Textmetadata
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.