Evidence map›Paper›PMID 35918439›Full record

ArticleScientific reports2022

Simultaneous assessment of lung morphology and respiratory motion in retrospectively gated in-vivo microCT of free breathing anesthetized mice.

Christian Dullin, Angelika Svetlove, Jana Zschüntzsch, Frauke Alves

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
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

4 authors.

Christian DullinInstitute for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany. christian.dullin@protonmail.com.
Angelika SvetloveMax-Plank-Institute for Multidisciplinary Sciences, Translational Molecular Imaging, Goettingen, Germany.
Jana ZschüntzschClinic for Neurology, University Medical Center Goettingen, Göettingen, Germany.
Frauke AlvesInstitute for Diagnostic and Interventional Radiology, University Medical Center Goettingen, Goettingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Retrospective gating (RG) is a well established technique in preclinical computed tomography (CT) to assess 3D morphology of the lung. In RG additional angular projections are recorded typically by performing multiple rotations. Consequently, the projections are sorted according to the expansion state of the chest and those sets are then reconstructed separately. Thus, the breathing motion artefacts are suppressed at a cost of strongly elevated X-ray dose levels. Here we propose to use the entire raw data to assess respiratory motion in addition to retrospectively gated 3D reconstruction that visualize anatomical structures of the lung. Using this RG based X-ray respiratory motion measurement approach, which will be referred to as RG based X-ray lung function measurement (rgXLF) on the example of the mdx mouse model of Duchenne muscle dystrophy (mdx) we accurately obtained both the 3D anatomical morphology of the lung and the thoracic bones as well as functional temporal parameters of the lung. Thus, rgXLF will remove the necessity for separate acquisition procedures by being able to reproduce comparable results to the previously established planar X-ray based lung function measurement approach in a single low dose CT scan.

Indexed as

LungRespirationAnimalsMiceMice, Inbred mdxRetrospective StudiesX-Ray Microtomography

Identifiers

PMID35918439
PMCPMC9345384

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.