Evidence map›Paper›PMID 32494778›Full record

ArticleImage analysis for moving organ, breast, and thoracic images : third International Workshop, RAMBO 2018, fourth International Workshop, BIA 2018, and first International Workshop, TIA 2018, held in conjunction with MICCAI 2018, Granada,...2018

A CT Scan Harmonization Technique to Detect Emphysema and Small Airway Diseases.

Gonzalo Vegas-Sánchez-Ferrero, Raúl San Estépar José

Open access · greenAbstract read
In one paragraph

Article in Image analysis for moving organ, breast, and thoracic images : third International Workshop, RAMBO 2018, fourth International Workshop, BIA 2018, and first International Workshop, TIA 2018, held in conjunction with MICCAI 2018, Granada,..., 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.2field-weighted citation impact, top 16% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Gonzalo Vegas-Sánchez-FerreroApplied Chest Imaging Laboratory (ACIL), Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Raúl San Estépar JoséApplied Chest Imaging Laboratory (ACIL), Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Brigham and Women's Hospital · US

Funding

The clinical impact of pulmonary vascular remodeling in smokersR01HL116473 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SAN JOSE ESTEPAR, RAUL, WASHKO, GEORGE R · 2013 to 2021
$5.0M
Airway Inspector: a chest imaging biomarker software platform for COPDR01HL116931 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SAN JOSE ESTEPAR, RAUL · 2013 to 2017
$2.2M
CT-based Predictors of ILA Progression in COPDGeneR21HL140422 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SAN JOSE ESTEPAR, RAUL · 2017 to 2018
$264k
NHLBI NIH HHS R01 HL116473NHLBI NIH HHS R01 HL116931NHLBI NIH HHS R21 HL140422
6 · The paper itself

Abstract

Recent studies have suggested the central role of small airway destruction in the pathogenesis of COPD leading to further parenchymal destruction. This evidence has sparked the interest in in-vivo assessment of small airway disease overall at the early onset of the disease. The parametric response mapping (PRM) technique has been proposed to distinguish gas trapping due to small airway disease from low attenuation areas due to emphysema. Despite its success, the PRM technique shows some limitations that are precluding the interpretation of its results. The density value used to assess gas trapping highly depends on acquisition parameters, such as dose and reconstruction kernel, and changes in body size, that introduce inhomogeneous photon absorption patterns. In particular, many studies using PRM employ inspiratory and expiratory images that are obtained at different dose levels. Emphysema impact in early disease may be confounded with the gas trapping due to the noise introduced by differences in the acquisition during the PRM. In this work, we propose a CT harmonization technique to remove the nuisance factors to distinguish between small airway disease and emphysema. Our results show that the measurements based on CT harmonization provide an increase in the detection of both emphysema and airway disease, resulting in a statistically significant impact of both components and a better association with lung function measures.

Indexed as

CT scansEmphysemaLung diseaseStatistical characterization

Identifiers

PMID32494778
PMCPMC7269187
OpenAlexW2892001242

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.