Evidence map›Paper›PMID 41254122›Full record

ArticleScientific reports2025

Motion compensated magnetic resonance imaging of an active sun beetle using an in situ treadmill.

Ajmal Chenakkara, Mazin Jouda, Ulrike Wallrabe, Jan G Korvink

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
–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

0 citing papers in PubMed.

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

4 authors.

Ajmal ChenakkaraInstitute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Karlsruhe, Germany.
Mazin JoudaInstitute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Karlsruhe, Germany.
Ulrike WallrabeInstitute of Microsystem Technology (IMTEK), University of Freiburg, Freiburg, Germany.
Jan G KorvinkInstitute of Microstructure Technology (IMT), Karlsruhe Institute of Technology, Karlsruhe, Germany. jan.korvink@kit.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magnetic resonance imaging is inherently non-invasive, and thus an ideal technique for probing living biological matter. The low sensitivity and prolonged data acquisition time, coupled with stringent magnetic field homogeneity requirements and spatial constraints inside the magnet, make the technique under-utilised for the study of live and freely moving model organisms. We introduce a new method for performing MRI of a live insect that is moving on a treadmill. The tethered insect, positioned on a treadmill inside an RF volume coil, provides a controlled environment for studying the organism, and maintains the spatial consistency for an MRI excitation slice, thereby limiting any residual motion artifacts within the slice or MRI field-of-view, and thus making the problem manageable with motion correction techniques available in clinical MRI research. We address the particular case of semi-periodic abdominal motion of the insect, and its effect on MRI reconstruction. An MR compatible optical imaging system has been integrated with the high-field magnet, in conjunction with a computer vision algorithm for extracting the real-time motion information, with the added advantage of phenotypic characterisation of the behaving organism. The motion information, with a prospective triggering system, has been used for the acquisition of spatially consistent k-space lines, thereby reducing artifacts due to the gross body motion of the walking insect.

Indexed as

ColeopteraMagnetic Resonance ImagingAlgorithmsAnimalsImage Processing, Computer-AssistedMotion

Identifiers

PMID41254122
PMCPMC12627492

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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.