Evidence map›Paper›PMID 38796545›Full record

ArticleScientific data2024

The SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA) for video-rate functional imaging of the skin.

Leonardo Ayala, Diana Mindroc-Filimon, Maike Rees, Marco Hübner, Jan Sellner, Silvia Seidlitz, Minu Tizabi, Sebastian Wirkert, Alexander Seitel, Lena Maier-Hein

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

10 authors.

Leonardo AyalaGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany. l.menjivar@dkfz.de.ORCID 0000-0002-3574-2085
Diana Mindroc-FilimonGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Maike ReesGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Marco HübnerGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Jan SellnerGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.ORCID 0000-0003-4469-8343
Silvia SeidlitzGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.ORCID 0000-0002-1122-4793
Minu TizabiGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Sebastian WirkertGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Alexander SeitelGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.
Lena Maier-HeinGerman Cancer Research Center (DKFZ), Division of Intelligent Medical Systems, Heidelberg, Germany.ORCID 0000-0003-4910-9368

Funding

EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) 101002198European Research Council
6 · The paper itself

Abstract

Spectral imaging has the potential to become a key technique in interventional medicine as it unveils much richer optical information compared to conventional RBG (red, green, and blue)-based imaging. Thus allowing for high-resolution functional tissue analysis in real time. Its higher information density particularly shows promise for the development of powerful perfusion monitoring methods for clinical use. However, even though in vivo validation of such methods is crucial for their clinical translation, the biomedical field suffers from a lack of publicly available datasets for this purpose. Closing this gap, we generated the SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA). It comprises ten spectral videos (∼20 Hz, approx. 20,000 frames each) systematically recorded of the hands of ten healthy human participants in different functional states. We paired each spectral video with concisely tracked regions of interest, and corresponding diffuse reflectance measurements recorded with a spectrometer. Providing the first openly accessible in human spectral video dataset for perfusion monitoring, our work facilitates the development and validation of new functional imaging methods.

Indexed as

SkinArmHandHumansVideo Recording

Identifiers

PMID38796545
PMCPMC11127995

What OpenQuestion holds

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LicenceCC BY
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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.