Evidence map›Paper›PMID 30868426›Full record

ArticleMolecular imaging and biology2019

Data Curation for Preclinical and Clinical Multimodal Imaging Studies.

Grace Gyamfuah Yamoah, Liji Cao, Chao Wu Wu, Freek J Beekman, Bert Vandeghinste, Julia G Mannheim, Stefanie Rosenhain, Kevin Leonardic, Fabian Kiessling, Felix Gremse

Abstract read
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In one paragraph

Article in Molecular imaging and biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. MedShift: Automated Identification of Shift Data for Medical Image Dataset Curation.IEEE journal of biomedical and health informatics · 2023
    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.

Grace Gyamfuah YamoahInstitute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany.
Liji CaoInviscan SAS, Strasbourg, France.
Chao Wu WuMILabs B.V. Utrecht, Utrecht, The Netherlands.
Freek J BeekmanMILabs B.V. Utrecht, Utrecht, The Netherlands.
Bert VandeghinsteMolecubes NV, Ghent, Belgium.
Julia G MannheimDepartment of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, Eberhard Karls University Tuebingen, Tuebingen, Germany.
Stefanie RosenhainInstitute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany.
Kevin LeonardicInstitute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany.
Fabian KiesslingInstitute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany.
Felix GremseInstitute for Experimental Molecular Imaging, Helmholtz Institute for Biomedical Engineering, RWTH Aachen University Clinic, Forckenbeckstraße 55, 52074, Aachen, Germany. fgremse@ukaachen.de.ORCID http://orcid.org/0000-0002-6522-9004

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn biomedical research, imaging modalities help discover pathological mechanisms to develop and evaluate novel diagnostic and theranostic approaches. However, while standards for data storage in the clinical medical imaging field exist, data curation standards for biomedical research are yet to be established. This work aimed at developing a free secure file format for multimodal imaging studies, supporting common in vivo imaging modalities up to five dimensions as a step towards establishing data curation standards for biomedical research. PROCEDURES: Images are compressed using lossless compression algorithm. Cryptographic hashes are computed on the compressed image slices. The hashes and compressions are computed in parallel, speeding up computations depending on the number of available cores. Then, the hashed images with digitally signed timestamps are cryptographically written to file. Fields in the structure, compressed slices, hashes, and timestamps are serialized for writing and reading from files. The C++ implementation is tested on multimodal data from six imaging sites, well-documented, and integrated into a preclinical image analysis software.

resultsThe format has been tested with several imaging modalities including fluorescence molecular tomography/x-ray computed tomography (CT), positron emission tomography (PET)/CT, single-photon emission computed tomography/CT, and PET/magnetic resonance imaging. To assess performance, we measured the compression rate, ratio, and time spent in compression. Additionally, the time and rate of writing and reading on a network drive were measured. Our findings demonstrate that we achieve close to 50 % reduction in storage space for μCT data. The parallelization speeds up the hash computations by a factor of 4. We achieve a compression rate of 137 MB/s for file of size 354 MB.

conclusionsThe development of this file format is a step to abstract and curate common processes involved in preclinical and clinical multimodal imaging studies in a standardized way. This work also defines better interface between multimodal imaging modalities and analysis software.

Indexed as

Data CurationMultimodal ImagingAlgorithmsAnimalsData CompressionImage Processing, Computer-AssistedCompressionCredibilityCryptographic hashingData curationFile formatMetadataMultimodal imagingReproducibilitySerializationTimestamp

Identifiers

PMID30868426

What OpenQuestion holds

Textmetadata
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.