ReviewBreathe (Sheffield, England)2024
Spatial lung imaging in clinical and translational settings.
Review in Breathe (Sheffield, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Insights into interstitial lung disease pathogenesis.Breathe (Sheffield, England) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
For many severe lung diseases, non-invasive biomarkers from imaging could improve early detection of lung injury or disease onset, establish a diagnosis, or help follow-up disease progression and treatment strategies. Imaging of the thorax and lung is challenging due to its size, respiration movement, transferred cardiac pulsation, vast density range and gravitation sensitivity. However, there is extensive ongoing research in this fast-evolving field. Recent improvements in spatial imaging have allowed us to study the three-dimensional structure of the lung, providing both spatial architecture and transcriptomic information at single-cell resolution. This fast progression, however, comes with several challenges, including significant image file storage and network capacity issues, increased costs, data processing and analysis, the role of artificial intelligence and machine learning, and mechanisms to combine several modalities. In this review, we provide an overview of advances and current issues in the field of spatial lung imaging.
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.