Evidence map›Paper›PMID 36070033›Full record

ArticleInternational journal of computer assisted radiology and surgery2023

Karawun: a software package for assisting evaluation of advances in multimodal imaging for neurosurgical planning and intraoperative neuronavigation.

Richard Beare, Bonnie Alexander, Aaron Warren, Michael Kean, Marc Seal, Alison Wray, Wirginia Maixner, Joseph Yuan-Mou Yang

Open access · hybridAbstract read
In one paragraph

Article in International journal of computer assisted radiology and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

9 citing papers in PubMed, 13 citations in OpenAlex.

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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 at 3 institutions in 2 countries.

Richard BeareDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia. Richard.Beare@mcri.edu.au.ORCID http://orcid.org/0000-0002-7530-5664
Bonnie AlexanderDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
Aaron WarrenDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
Michael KeanDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
Marc SealDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
Alison WrayDepartment of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia.
Wirginia MaixnerDepartment of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia.
Joseph Yuan-Mou YangDevelopmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia.
Royal Children's Hospital · AUPeninsula Health · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe neuroimaging research community-which includes a broad range of scientific, medical, statistical, and engineering disciplines-has developed many tools to advance our knowledge of brain structure, function, development, aging, and disease. Past research efforts have clearly shaped clinical practice. However, translation of new methodologies into clinical practice is challenging. Anything that can reduce these barriers has the potential to improve the rate at which research outcomes can contribute to clinical practice. In this article, we introduce Karawun, a file format conversion tool, that has become a key part of our work in translating advances in diffusion imaging acquisition and analysis into neurosurgical practice at our institution.

methodsKarawun links analysis workflows created using open-source neuroimaging software, to Brainlab (Brainlab AG, Munich, Germany), a commercially available surgical planning and navigation suite. Karawun achieves this using DICOM standards supporting representation of 3D structures, including tractography streamlines, and thus offers far more than traditional screenshot or color overlay approaches.

resultsWe show that neurosurgical planning data, created from multimodal imaging data using analysis methods implemented in open-source research software, can be imported into Brainlab. The datasets can be manipulated as if they were created by Brainlab, including 3D visualizations of white matter tracts and other objects.

conclusionClinicians can explore and interact with the results of research neuroimaging pipelines using familiar tools within their standard clinical workflow, understand the impact of the new methods on their practice and provide feedback to methods developers. This capability has been important to the translation of advanced analysis techniques into practice at our institution.

Indexed as

Imaging, Three-DimensionalNeuronavigationBrainHumansMultimodal ImagingNeurosurgical ProceduresSoftwareDICOMDiffusion imagingImage-guided surgeryTractography

Identifiers

PMID36070033
PMCPMC9883338
OpenAlexW4295015171

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.