Evidence map›Paper›PMID 41809437›Full record

ArticleBrain communications2026

Automated quantification of the Alberta Stroke Programme Early CT Score (ASPECTS) and infarct core on diffusion-weighted imaging in acute ischaemic stroke: multi-centre validation and severity stratification.

Lai Wei, Ting Xiao, Hao Wang, Lei Shi, Qian Xi, Ming Liu, Huali Xu, Kangwei Zhang, Xiang Zhou, Yu Luo and 1 more

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Article in Brain communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

11 authors.

Lai WeiDepartment of Radiology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Ting XiaoSchool of Information Science and Engineering, East China University of Science and Technology, Shanghai 200235, China.
Hao WangSchool of Information Science and Engineering, East China University of Science and Technology, Shanghai 200235, China.
Lei ShiSchool of Information Science and Engineering, East China University of Science and Technology, Shanghai 200235, China.
Qian XiDepartment of Radiology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai 200120, China.
Ming LiuDepartment of Radiology, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China.
Huali XuDepartment of Radiology, Putuo Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai 200062, China.
Kangwei ZhangDepartment of Medical Imaging, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China.
Xiang ZhouDepartment of Medical Imaging, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China.ORCID https://orcid.org/0000-0002-5394-3841
Yu LuoDepartment of Radiology, Shanghai Fourth People's Hospital, School of Medicine, Tongji University, Shanghai 200434, China.
Peijun WangDepartment of Medical Imaging, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to develop and validate a deep learning framework for simultaneous automated quantification of diffusion-weighted imaging-the Alberta Stroke Programme early CT score (DWI-ASPECTS) and infarct core volume in middle cerebral artery acute ischaemic stroke (MCA-AIS) and to evaluate its clinical utility for severity stratification in multi-centre settings. A cohort of 738 patients diagnosed with MCA-AIS from four centres was divided into a train set (

Indexed as

acute ischaemic stroke (AIS)corevolumedeep learning (DL)diffusion-weighted imaging (DWI)the Alberta Stroke Programme Early CT Score (ASPECTS)

Identifiers

PMID41809437
PMCPMC12971011

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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.