ArticleThe British journal of radiology2023
Histogram-based analysis in progressive pulmonary fibrosis: relationships between pulmonary functional tests and HRCT indexes.
Article in The British journal of radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 5 citations in OpenAlex.
- Assessment of fibrosing interstitial lung disease progression: CT visual score on radiological progressive pulmonary fibrosis criteria versus 3D-CT volume-histogram analysis.Japanese journal of radiology · 2026Article
- Changes in the Quantitative Computed Tomography Values in Drug-associated Interstitial Lung Disease Caused by Non-anticancer Drugs.Internal medicine (Tokyo, Japan) · 2026Article
- Structural determinants of pulmonary diffusing capacity identified by network analysis and machine learning on quantitative CT.Scientific reports · 2026Article
- Quantitative comparative analysis of different CT modalities in systemic sclerosis-associated interstitial lung disease: correlations with lung function, serological biomarkers, and disease stratification.Journal of thoracic disease · 2026Article
- Semi-Automated Lung Segmentation Based on Region-Growing Methods in Interstitial Lung Disease.Journal of clinical medicine · 2026Article
- Quantitative Assessment of High-resolution Computer Tomography Imaging in a Super-responder to Nintedanib Therapy in a Patient with Idiopathic Pulmonary Fibrosis.Internal medicine (Tokyo, Japan) · 2025Article
- The density histograms-derived computerized integrated index (CII) predicts mortality in idiopathic pulmonary fibrosis.Scientific reports · 2024Article
- Artificial intelligence-based quantification of pulmonary HRCT (AIqpHRCT) for the evaluation of interstitial lung disease in patients with inflammatory rheumatic diseases.Rheumatology international · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo investigate relationships between histogram-based high-resolution CT (HRCT) indexes and pulmonary function tests (PFTs) in interstitial lung diseases.
methodsForty-nine patients having baseline and 1-year HRCT examinations and PFTs were investigated. Histogram-based HRCT indexes were calculated; strength of associations with PFTs was investigated using Pearson correlation. Patients were divided into progressive and non-progressive groups. HRCT indexes were compared between the two groups using the
resultsAt baseline, moderate correlations were observed considering kurtosis and diffusion capacity of the lungs for carbon monoxide (DLCO) (
conclusionAt one year, moderate correlations suggest that progression could be assessed through HRCT quantification. ADVANCES IN KNOWLEDGE: This study promotes histogram-based HRCT indexes in the assessment of progressive pulmonary fibrosis.
Indexed as
Identifiers
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.