Evidence map›Paper›PMID 40352142›Full record

ArticleFrontiers in physiology2025

Longitudinal study of COPD phenotypes using integrated SPECT and qCT imaging.

Frank Li, Xuan Zhang, Alejandro P Comellas, Eric A Hoffman, Michael M Graham, Ching-Long Lin

Abstract read
In one paragraph

Article in Frontiers in physiology, 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

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

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

6 authors.

Frank LiRoy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States.
Xuan ZhangIIHR-Hydroscience and Engineering, University of Iowa, Iowa City, IA, United States.
Alejandro P ComellasDepartment of Internal Medicine, University of Iowa, Iowa City, IA, United States.
Eric A HoffmanRoy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States.
Michael M GrahamDepartment of Radiology, University of Iowa, Iowa City, IA, United States.
Ching-Long LinRoy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA, United States.

Funding

Pulmonary Toxicology Facility CoreP30ES005605 · NIEHS · UNIVERSITY OF IOWA · PI Jong Sung Kim · 1990 to 2026
$40.5M
Multi-center Structural & Functional Quantitative CT Pulmonary PhenotypingR01HL112986 · NHLBI · UNIVERSITY OF IOWA · PI HOFFMAN, ERIC ALFRED · 2012 to 2016
$4.6M
An integrative statistics-guided image-based multi-scale lung modelU01HL114494 · NHLBI · UNIVERSITY OF IOWA · PI LIN, CHING-LONG · 2013 to 2017
$3.1M
Deep Learning and Subtyping of Post-COVID-19 Lung Progression PhenotypesR01HL168116 · NHLBI · UNIVERSITY OF IOWA · PI CHING-LONG LIN · 2023 to 2026
$2.9M
Iowa Lung Imaging Training ProgramT32HL144461 · NHLBI · UNIVERSITY OF IOWA · PI HOFFMAN, ERIC ALFRED, REINHARDT, JOSEPH M · 2019 to 2023
$1.6M
Large-Scale Computing and Visualization for Cardiopulmonary ImagingS10RR022421 · NCRR · UNIVERSITY OF IOWA · PI LIN, CHING-LONG · 2008 to 2008
$474k
NCRR NIH HHS S10 RR022421NHLBI NIH HHS R01 HL112986NHLBI NIH HHS R01 HL168116NHLBI NIH HHS T32 HL144461NHLBI NIH HHS U01 HL114494NIEHS NIH HHS P30 ES005605
6 · The paper itself

Abstract

Introduction: The aim of this research is to elucidate chronic obstructive pulmonary disease (COPD) progression by quantifying lung ventilation heterogeneities using single-photon emission computed tomography (SPECT) images and establishing correlations with quantitative computed tomography (qCT) imaging-based metrics. This approach seeks to enhance our understanding of how structural and functional changes influence ventilation heterogeneity in COPD. Methods: Eight COPD subjects completed a longitudinal study with three visits, spaced about a year apart. CT scans were performed at each visit and qCT-based variables were derived to measure the structural and functional characteristics of the lungs, while the SPECT-based variables were used to quantify lung ventilation heterogeneity. The correlations between key qCT-based variables and SPECT-based variables were examined. Results: The SPECT-based ventilation heterogeneity (CV Discussion: In conclusion, this study found strong positive cross-sectional correlations between CV

Indexed as

COPDCTsmall airway diseaseSPECTventilation

Identifiers

PMID40352142
PMCPMC12061679

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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.