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Record W2747239266 · doi:10.1159/000478865

A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography

2017· article· en· W2747239266 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRespiration · 2017
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsMcGill University Health CentreUniversity of British ColumbiaSt. Paul's Hospital
Fundersnot available
KeywordsMedicineExpirationPopulationCOPDAirwayInternal medicineNuclear medicineCardiologyRespiratory systemSurgery

Abstract

fetched live from OpenAlex

<b><i>Background:</i></b> Disease accumulates in the small airways without being detected by conventional measurements. <b><i>Objectives:</i></b> To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. <b><i>Methods:</i></b> Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). <b><i>Results:</i></b> The participants included never-smokers (<i>n</i> = 135), at risk (<i>n</i> = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (<i>n</i> = 140), and GOLD II chronic obstructive pulmonary disease (<i>n</i> = 96). PRM<sub>GasTrap</sub> and DPM<sub>GasTrap</sub> measurements were significantly elevated in GOLD II compared to never-smokers (<i>p</i> < 0.01) and at risk (<i>p</i> < 0.01), and for GOLD I compared to at risk (<i>p</i> < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (<i>p</i> < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (<i>p</i> < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPM<sub>GasTrap</sub> but PRM<sub>Normal</sub> (PRM<sub>Normal</sub>- DPM<sub>GasTrap</sub> = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRM<sub>Normal</sub>-DPM<sub>Normal</sub> = -722 ± 89 HU; <i>p</i> < 0.0001). DPM and PRM<sub>GasTrap</sub> measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV<sub>1</sub>) (<i>p</i> < 0.01), FEV<sub>1</sub>/forced vital capacity (<i>p</i> < 0.0001), residual volume/total lung capacity (<i>p</i> < 0.0001), bronchodilator response (<i>p</i> < 0.0001), and dyspnea (<i>p</i> < 0.05). <b><i>Conclusion:</i></b> CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score0.942

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.072
GPT teacher head0.368
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it