Evidence map›Paper›PMID 39327046›Full record

ArticleJournal of neurointerventional surgery2025

Impact of imaging biomarkers from body composition analysis on outcome of endovascularly treated acute ischemic stroke patients.

Hanna Styczen, Volker Maus, Daniel Weiss, Lukas Goertz, René Hosch, Christian Rubbert, Nikolas Beck, Mathias Holtkamp, Luca Salhöfer, Rosa Schubert and 3 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of neurointerventional surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Hanna StyczenInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany Hanna.Styczen@uk-essen.de.ORCID http://orcid.org/0000-0002-9623-4156
Volker MausDepartment of Radiology, Neuroradiology and Nuclear Medicine, Knappschaftskrankenhaus Langendreer, Ruhr-University Bochum, Bochum, Germany.
Daniel WeissDepartment of Diagnostic and Interventional Radiology, Heinrich Heine University Duesseldorf, Duesseldorf, Germany.
Lukas GoertzDepartment of Diagnostic and Interventional Radiology, University Hospital of Cologne, Cologne, Germany.ORCID http://orcid.org/0000-0002-2620-7611
René HoschInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Christian RubbertDepartment of Diagnostic and Interventional Radiology, Heinrich Heine University Duesseldorf, Duesseldorf, Germany.
Nikolas BeckInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Mathias HoltkampInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Luca SalhöferInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Rosa SchubertInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Cornelius DeuschlInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.ORCID http://orcid.org/0000-0001-9262-7289
Felix NensaInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Johannes HauboldInstitute for Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe investigate the association of imaging biomarkers extracted from fully automated body composition analysis (BCA) of computed tomography (CT) angiography images of endovascularly treated acute ischemic stroke (AIS) patients regarding angiographic and clinical outcome.

methodsRetrospective analysis of AIS patients treated with mechanical thrombectomy (MT) at three tertiary care-centers between March 2019-January 2022. Baseline demographics, angiographic outcome and clinical outcome evaluated by the modified Rankin Scale (mRS) at discharge were noted. Multiple tissues, such as muscle, bone, and adipose tissue were acquired with a deep-learning-based, fully automated BCA from CT images of the supra-aortic angiography.

resultsA total of 290 stroke patients who underwent MT due to cerebral vessel occlusion in the anterior circulation were included in the study. In the univariate analyses, among all BCA markers, only the lower sarcopenia marker was associated with a poor outcome (P=0.007). It remained an independent predictor for an unfavorable outcome in a logistic regression analysis (OR 0.6, 95% CI 0.3 to 0.9, P=0.044). Fat index (total adipose tissue/bone) and myosteatosis index (inter- and intramuscular adipose tissue/total adipose tissue*100) did not affect clinical outcomes.

conclusionAcute ischemic stroke patients with a lower sarcopenia marker are at risk for an unfavorable outcome. Imaging biomarkers extracted from BCA can be easily obtained from existing CT images, making it readily available at the beginning of treatment. However, further research is necessary to determine whether sarcopenia provides additional value beyond established outcome predictors. Understanding its role could lead to optimized, individualized treatment plans for post-stroke patients, potentially improving recovery outcomes.

Indexed as

Body CompositionEndovascular ProceduresIschemic StrokeAgedAged, 80 and overBiomarkersComputed Tomography AngiographyFemaleHumansMaleMiddle AgedRetrospective StudiesSarcopeniaThrombectomyTreatment OutcomeBiomarkersCT AngiographyStrokeThrombectomy

Identifiers

PMID39327046
PMCPMC12703279

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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.