Evidence map›Paper›PMID 39014011›Full record

ArticleScientific reports2024

Lung quantitative ultrasound to stage and monitor interstitial lung diseases.

Azadeh Dashti, Roshan Roshankhah, Theresa Lye, John Blackwell, Stephanie Montgomery, Thomas Egan, Jonathan Mamou, Marie Muller

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Azadeh Dashti *Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA.
Roshan Roshankhah *Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA.
Theresa LyeTopcon Advanced Biomedical Imaging Laboratory, Topcon Healthcare, Oakland, NJ, 07436, USA.
John BlackwellDepartment of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
Stephanie MontgomeryAKC Canine Health Foundation, Raleigh, NC, 27617, USA.
Thomas EganDepartment of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. thomas_egan@med.unc.edu.
Jonathan MamouDepartment of Radiology, Weill Cornell Medicine, New York, NY, 10022, USA. jom4032@med.cornell.edu.
Marie MullerDepartment of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC, 27695, USA. mmuller2@ncsu.edu.

Funding

Novel Ultrasonic Methods for the Assessment of Pulmonary EdemaR21HL154156 · NHLBI · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI EGAN, THOMAS M., MULLER, MARIE · 2020 to 2021
$419k
NHLBI NIH HHS R21 HL154156NHLBI NIH HHS R21HL154156U.S. Department of Defense W81XWH1810101
6 · The paper itself

Abstract

Chronic interstitial lung diseases (ILDs) require frequent point-of-care monitoring. X-ray-based methods lack resolution and are ionizing. Chest computerized tomographic (CT) scans are expensive and provide more radiation. Conventional ultrasound can detect severe lung damage via vertical artifacts (B-lines). However, this information is not quantitative, and the appearance of B-lines is operator- and system-dependent. Here we demonstrate novel ultrasound-based biomarkers to assess severity of ILDs. Lung alveoli scatter ultrasound waves, leading to a complex acoustic signature, which is affected by changes in alveolar density due to ILDs. We exploit ultrasound scattering in the lung and combine quantitative ultrasound (QUS) parameters, to develop ultrasound-based biomarkers that significantly correlate (p = 1e

Indexed as

LungLung Diseases, InterstitialUltrasonographyAnimalsBiomarkersHumansMaleMicePulmonary AlveoliPulmonary FibrosisRatsSeverity of Illness IndexBiomarkers

Identifiers

PMID39014011
PMCPMC11252144

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Registered trials

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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.