Evidence map›Paper›PMID 41561950›Full record

ArticleFrontiers in medicine2025

Habitat imaging radiomics of chest CT identifies noninfectious acute exacerbations in chronic obstructive pulmonary disease.

Zhenxing Feng, Shuo Liang, Minghui Hua, Yafang Zheng, Jiwei Sun, Li Zhou, Yimeng Zhang, Boxin Li, Yi Li, Baozhen Ge and 2 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

12 authors.

Zhenxing FengDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Shuo LiangDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Minghui HuaDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Yafang ZhengDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Jiwei SunDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Li ZhouDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Yimeng ZhangDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Boxin LiDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Yi LiDepartment of Respiratory and Critical Care Medicine, Tianjin Chest Hospital, Tianjin, China.
Baozhen GeSchool of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, China.
Hong ZhangDepartment of Radiology, Tianjin Chest Hospital, Tianjin, China.
Daqiang SunDepartment of Thoracic Surgery, Tianjin Chest Hospital, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Noninfectious acute exacerbations of chronic obstructive pulmonary disease (AECOPD) pose significant diagnostic challenges due to the lack of reliable biomarkers. This study aims to develop and validate a CT-based habitat imaging radiomic model for precise identification of noninfectious AECOPD. Methods: This retrospective study included 352 eligible chronic obstructive pulmonary disease (COPD) patients who received treatment at Tianjin Chest Hospital from January 2019 to December 2023. Among these patients (181 with noninfectious AECOPD, 171 with stable COPD), stratified randomization allocated cohorts to training ( Results: The CT-based whole lung was segmented into three habitat subregions: habitat subregion 1 (emphysema/bullae-associated), habitat subregion 2 (bronchovascular bundle), and habitat subregion 3 (lung parenchyma). The habitat Conclusion: In conclusion, this study segmented whole-lung CT scans of noninfectious AECOPD patients into habitat subregions, developing a radiomics model that demonstrated strong diagnostic efficacy. This approach provides an objective imaging biomarker and a potential tool for quantifying COPD heterogeneity.

Indexed as

acute exacerbationchronic obstructive pulmonary diseaseCThabitatradiomics

Identifiers

PMID41561950
PMCPMC12812631

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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.