Evidence map›Paper›PMID 35094103›Full record

ArticleNeuroradiology2022

Stroke population-specific neuroanatomical CT-MRI brain atlas.

Tina Kaffenberger, Vijay Venkatraman, Chris Steward, Vincent N Thijs, Julie Bernhardt, Patricia M Desmond, Bruce C V Campbell, Nawaf Yassi

Open access · hybridAbstract read
In one paragraph

Article in Neuroradiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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  3. Article
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  5. 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

8 authors at 2 institutions in 1 country.

Tina KaffenbergerThe Florey Institute of Neuroscience and Mental Health, University of Melbourne, 245 Burgundy Street, Heidelberg, VIC, 3084, Australia. tina.kaffenberger@florey.edu.au.ORCID http://orcid.org/0000-0001-9848-2666
Vijay VenkatramanDepartment of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Chris StewardDepartment of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Vincent N ThijsThe Florey Institute of Neuroscience and Mental Health, University of Melbourne, 245 Burgundy Street, Heidelberg, VIC, 3084, Australia.
Julie BernhardtThe Florey Institute of Neuroscience and Mental Health, University of Melbourne, 245 Burgundy Street, Heidelberg, VIC, 3084, Australia.
Patricia M DesmondDepartment of Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, VIC, Australia.
Bruce C V CampbellDepartment of Medicine and Neurology, Royal Melbourne Hospital, Parkville, VIC, Australia.
Nawaf YassiDepartment of Medicine and Neurology, Royal Melbourne Hospital, Parkville, VIC, Australia.
The Royal Melbourne Hospital · AUThe University of Melbourne · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeDevelopment of a freely available stroke population-specific anatomical CT/MRI atlas with a reliable normalisation pipeline for clinical CT.

methodsBy reviewing CT scans in suspected stroke patients and filtering the AIBL MRI database, respectively, we collected 50 normal-for-age CT and MRI scans to build a standard-resolution CT template and a high-resolution MRI template. The latter was manually segmented into anatomical brain regions. We then developed and validated a MRI to CT registration pipeline to align the MRI atlas onto the CT template. Finally, we developed a CT-to-CT-normalisation pipeline and tested its reliability by calculating Dice coefficient (Dice) and Average Hausdorff Distance (AHD) for predefined areas in 100 CT scans from ischaemic stroke patients.

resultsThe resulting CT/MRI templates were age and sex matched to a general stroke population (median age 71.9 years (62.1-80.2), 60% male). Specifically, this accounts for relevant structural changes related to aging, which may affect registration. Applying the validated MRI to CT alignment (Dice > 0.78, Average Hausdorff Distance < 0.59 mm) resulted in our final CT-MRI atlas. The atlas has 52 manually segmented regions and covers the whole brain. The alignment of four cortical and subcortical brain regions with our CT-normalisation pipeline was reliable for small/medium/large infarct lesions (Dice coefficient > 0.5).

conclusionThe newly created CT-MRI brain atlas has the potential to standardise stroke lesion segmentation. Together with the automated normalisation pipeline, it allows analysis of existing and new datasets to improve prediction tools for stroke patients (free download at https://forms.office.com/r/v4t3sWfbKs ).

Indexed as

Brain IschemiaStrokeAgedBrainFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleReproducibility of ResultsTomography, X-Ray ComputedComputed tomography (CT)Magnetic resonance imaging (MRI)Neuroanatomical atlasPopulation specificStrokeTemplate

Identifiers

PMID35094103
PMCPMC9271109
OpenAlexW4210308012

What OpenQuestion holds

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LicenceCC BY
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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.