Evidence map›Paper›PMID 36549849›Full record

ArticleAJNR. American journal of neuroradiology2023

Artificial Intelligence-Assisted Evaluation of the Spatial Relationship between Brain Arteriovenous Malformations and the Corticospinal Tract to Predict Postsurgical Motor Defects.

Y Jiao, J Zhang, X Yang, T Zhan, Z Wu, Y Li, S Zhao, H Li, J Weng, R Huo and 5 more

Open access · hybridAbstract read

In one paragraph

Article in AJNR. American journal of neuroradiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it

0cells of the map it votes in

5citing papers in PubMed, 3 pooled it

0.9field-weighted citation impact, top 24% 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, 3 syntheses or guidelines pooled it, 7 citations in OpenAlex.

Artificial intelligence and machine learning driven segmentation and quantification models for brain arteriovenous malformations: A systematic review.Neuroradiology · 2025
Pooled it
Impact of embolization on stereotactic radiosurgery outcomes for intracranial arteriovenous malformations Spetzler-Martin grades III-V: a systematic review and meta-analysis.Frontiers in surgery · 2025
Pooled it
The current landscape of machine learning-based radiomics in arteriovenous malformations: a systematic review and radiomics quality score assessment.Frontiers in neurology · 2024
Pooled it
Cerebral vascular malformations: pathogenesis and therapy.MedComm · 2024
Review
Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.Frontiers in human neuroscience · 2023
Review

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

15 authors at 2 institutions in 2 countries.

Y JiaoFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-8351-4602

J ZhangFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-1764-4959

X YangChina National Clinical Research Center for Neurological Diseases (Y.J., J.Z., X.Y., T.Z., Z.W., Y.L., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing, China.ORCID 0000-0002-6828-7744

T ZhanChina National Clinical Research Center for Neurological Diseases (Y.J., J.Z., X.Y., T.Z., Z.W., Y.L., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing, China.ORCID 0000-0003-4587-8557

Z WuChina National Clinical Research Center for Neurological Diseases (Y.J., J.Z., X.Y., T.Z., Z.W., Y.L., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing, China.ORCID 0000-0002-9119-4554

Y LiChina National Clinical Research Center for Neurological Diseases (Y.J., J.Z., X.Y., T.Z., Z.W., Y.L., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing, China.ORCID 0000-0003-1330-9827

S ZhaoFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-7527-5226

H LiFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-3272-8392

J WengFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-8337-4670

R HuoFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-4708-3133

J WangFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-9429-5094

H XuFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-9294-8349

Y SunFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-3986-4896

S WangFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-4919-5390

Y CaoFrom the Department of Neurosurgery (Y.J., J.Z., S.Z., H.L., J. Weng, R.H., J. Wang, H.X., Y.S., S.W., Y.C.), Beijing Tiantan Hospital, Capital Medical University, Beijing, China caoyong@bjtth.org.ORCID 0000-0002-8289-1120

Capital Medical University · CNWorld Wide Web Consortium · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposePreoperative evaluation of brain AVMs is crucial for the selection of surgical candidates. Our goal was to use artificial intelligence to predict postsurgical motor defects in patients with brain AVMs involving motor-related areas. MATERIALS AND

methodsEighty-three patients who underwent microsurgical resection of brain AVMs involving motor-related areas were retrospectively reviewed. Four artificial intelligence-based indicators were calculated with artificial intelligence on TOF-MRA and DTI, including FN

resultsIn patients with and without postsurgical motor defects, the mean FN

conclusionsThe artificial intelligence-based indicator, FN

Indexed as

Intracranial Arteriovenous MalformationsRadiosurgeryArtificial IntelligenceBrainHumansPyramidal TractsRetrospective StudiesTreatment Outcome

Identifiers

PMID36549849

DOI10.3174/ajnr.A7735

PMCPMC9835926

OpenAlexW4312098437

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.