Observational studyChest2019
CT Imaging-Based Low-Attenuation Super Clusters in Three Dimensions and the Progression of Emphysema.
Observational study in Chest, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Chest CT in the evaluation of chronic obstructive pulmonary disease: recommendations of Asian Society of Thoracic Radiology.The British journal of radiology · 2026Guideline
- Effects of exercise intensity on nutritional status, body composition, and energy balance in patients with COPD: a randomized controlled trial.BMC pulmonary medicine · 2025Trial
- Cooperation, Defection, and Collapse: A Multiscale Game Theory Framework for Emphysema Progression.Cells · 2026Review
- Machine learning models using dual-phase CT radiomics for early detection of PRISm.Scientific reports · 2025Article
- Mechanically Affected Lung and Progression of Emphysema.American journal of respiratory and critical care medicine · 2025Article
- Preoperative and postoperative imaging features in thoracic surgery: insights from a single-center study.Journal of medicine and life · 2025Article
- Resistive breathing aggravates cigarette smoke-induced pulmonary inflammation.ERJ open research · 2025Article
- AutoCOPD-A novel and practical machine learning model for COPD detection using whole-lung inspiratory quantitative CT measurements: a retrospective, multicenter study.EClinicalMedicine · 2025Article
- Using machine learning for early detection of chronic obstructive pulmonary disease: a narrative review.Respiratory research · 2024Review
- A scale-free model of acute and ventilator-induced lung injury: a network theory approach inspired by seismology.Frontiers in network physiology · 2024Article
- Quantifying the spatial clustering characteristics of radiographic emphysema explains variability in pulmonary function.Scientific reports · 2023Article
- Spatiotemporal distribution of cellular injury and leukocytes during the progression of ventilator-induced lung injury.American journal of physiology. Lung cellular and molecular physiology · 2022Article
- A Personalized Spring Network Representation of Emphysematous Lungs From CT Images.Frontiers in network physiology · 2022Article
- Three-Dimensional CT for Quantification of Longitudinal Lung and Pneumonia Variations in COVID-19 Patients.Frontiers in medicine · 2021Article
- Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease.Frontiers in physiology · 2020Review
- Spontaneous Breathing Through Increased Airway Resistance Augments Elastase-Induced Pulmonary Emphysema.International journal of chronic obstructive pulmonary disease · 2020Article
- Quantitative CT analysis in patients with pulmonary emphysema: is lung function influenced by concomitant unspecific pulmonary fibrosis?International journal of chronic obstructive pulmonary disease · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundDistributions of low-attenuation areas in two-dimensional (2-D) CT lung slices are used to quantify parenchymal destruction in patients with COPD. However, these segmental approaches are limited and may not reflect the true three-dimensional (3-D) tissue processes that drive emphysematous changes in the lung. The goal of this study was to instead evaluate distributions of 3-D low-attenuation volumes, which we hypothesized would follow a power law distribution and provide a more complete assessment of the mechanisms underlying disease progression.
methodsCT scans and pulmonary function test results were acquired from an observational database for N = 12 patients with COPD and N = 12 control patients. The data set included baseline and two annual follow-up evaluations in patients with COPD. Three-dimensional representations of the lungs were reconstructed from 2-D axial CT slices, with low-attenuation volumes identified as contiguous voxels < -960 Hounsfield units.
resultsLow-attenuation sizes generally followed a power law distribution, with the exception of large, individual outliers termed "super clusters," which deviated from the expected distribution. Super cluster volume was correlated with disease severity (% total low attenuation, ρ = 0.950) and clinical measures of lung function including FEV
conclusionsLow-attenuation super clusters are defining, quantitative features of parenchymal destruction that dominate disease progression, particularly in advanced COPD.
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What OpenQuestion holds
Registered trials
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.