001     1027017
005     20250204113900.0
024 7 _ |a 10.1186/s13244-024-01704-w
|2 doi
024 7 _ |a 10.34734/FZJ-2024-03583
|2 datacite_doi
024 7 _ |a 38825600
|2 pmid
024 7 _ |a WOS:001237654800002
|2 WOS
037 _ _ |a FZJ-2024-03583
082 _ _ |a 610
100 1 _ |a Floca, Ralf
|0 P:(DE-HGF)0
|b 0
|e Corresponding author
245 _ _ |a Radiomics workflow definition & challenges - German priority program 2177 consensus statement on clinically applied radiomics
260 _ _ |a Heidelberg
|c 2024
|b Springer
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1718116151_30832
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a Funded by the DFG 428090865, 428149221, 428210203, 428212052, 428212161, 428215948, 428216905, 428218324, 428219815, 428222922, 428223038, 428223139, 428223917, 428224258, 428224476 / SPP 2177 • Partially funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Projektnummer 442326535 /
520 _ _ |a Objectives: Achieving a consensus on a definition for different aspects of radiomics workflows to support their translation into clinical usage. Furthermore, to assess the perspective of experts on important challenges for a successful clinical workflow implementation.Materials and methods: The consensus was achieved by a multi-stage process. Stage 1 comprised a definition screening, a retrospective analysis with semantic mapping of terms found in 22 workflow definitions, and the compilation of an initial baseline definition. Stages 2 and 3 consisted of a Delphi process with over 45 experts hailing from sites participating in the German Research Foundation (DFG) Priority Program 2177. Stage 2 aimed to achieve a broad consensus for a definition proposal, while stage 3 identified the importance of translational challenges.Results: Workflow definitions from 22 publications (published 2012-2020) were analyzed. Sixty-nine definition terms were extracted, mapped, and semantic ambiguities (e.g., homonymous and synonymous terms) were identified and resolved. The consensus definition was developed via a Delphi process. The final definition comprising seven phases and 37 aspects reached a high overall consensus (> 89% of experts "agree" or "strongly agree"). Two aspects reached no strong consensus. In addition, the Delphi process identified and characterized from the participating experts' perspective the ten most important challenges in radiomics workflows.Conclusion: To overcome semantic inconsistencies between existing definitions and offer a well-defined, broad, referenceable terminology, a consensus workflow definition for radiomics-based setups and a terms mapping to existing literature was compiled. Moreover, the most relevant challenges towards clinical application were characterized.Critical relevance statement: Lack of standardization represents one major obstacle to successful clinical translation of radiomics. Here, we report a consensus workflow definition on different aspects of radiomics studies and highlight important challenges to advance the clinical adoption of radiomics.Key points: Published radiomics workflow terminologies are inconsistent, hindering standardization and translation. A consensus radiomics workflow definition proposal with high agreement was developed. Publicly available result resources for further exploitation by the scientific community.Keywords: Computer-assisted; Consensus development conference; Image processing; Terminology; Workflow.
536 _ _ |a 5252 - Brain Dysfunction and Plasticity (POF4-525)
|0 G:(DE-HGF)POF4-5252
|c POF4-525
|f POF IV
|x 0
536 _ _ |a DFG project 428090865 - Radiomics basierend auf MRT und Aminosäure PET in der Neuroonkologie (428090865)
|0 G:(GEPRIS)428090865
|c 428090865
|x 1
536 _ _ |a DFG project 428149221 - Prädiktion von Therapieansprechen und Outcome beim lokal fortgeschrittenen Rektum-Karzinom mittels Radiomics und Deep Learning: eine beispielhafte Anwendung für eine allgemein verwendbare, Deep Learning basierte Prozessierungs-Pipeline für die Bild-Klassifikation. (428149221)
|0 G:(GEPRIS)428149221
|c 428149221
|x 2
536 _ _ |a DFG project 428210203 - Bildmorphologische Biomarker der menschlichen Skelettmuskulatur (Muskelmasse, morphologische und Textureigenschaften von Muskelgruppen des Körperstamms und Oberschenkels) bei Sarkopenie und kardiometabolischen Erkrankungen (428210203)
|0 G:(GEPRIS)428210203
|c 428210203
|x 3
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Bohn, Jonas
|0 P:(DE-HGF)0
|b 1
700 1 _ |a Haux, Christian
|0 P:(DE-HGF)0
|b 2
700 1 _ |a Wiestler, Benedikt
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Zöllner, Frank G.
|0 P:(DE-HGF)0
|b 4
700 1 _ |a Reinke, Annika
|0 P:(DE-HGF)0
|b 5
700 1 _ |a Weiß, Jakob
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Nolden, Marco
|0 P:(DE-HGF)0
|b 7
700 1 _ |a Albert, Steffen
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Persigehl, Thorsten
|0 P:(DE-HGF)0
|b 9
700 1 _ |a Norajitra, Tobias
|0 P:(DE-HGF)0
|b 10
700 1 _ |a Baeßler, Bettina
|0 P:(DE-HGF)0
|b 11
700 1 _ |a Dewey, Marc
|0 P:(DE-HGF)0
|b 12
700 1 _ |a Braren, Rickmer
|0 P:(DE-HGF)0
|b 13
700 1 _ |a Büchert, Martin
|0 P:(DE-HGF)0
|b 14
700 1 _ |a Fallenberg, Eva Maria
|0 P:(DE-HGF)0
|b 15
700 1 _ |a Galldiks, Norbert
|0 P:(DE-Juel1)143792
|b 16
|u fzj
700 1 _ |a Gerken, Annika
|0 P:(DE-HGF)0
|b 17
700 1 _ |a Götz, Michael
|0 P:(DE-HGF)0
|b 18
700 1 _ |a Hahn, Horst K.
|0 P:(DE-HGF)0
|b 19
700 1 _ |a Haubold, Johannes
|0 P:(DE-HGF)0
|b 20
700 1 _ |a Haueise, Tobias
|0 P:(DE-HGF)0
|b 21
700 1 _ |a Große Hokamp, Nils
|0 P:(DE-HGF)0
|b 22
700 1 _ |a Ingrisch, Michael
|0 P:(DE-HGF)0
|b 23
700 1 _ |a Iuga, Andra-Iza
|0 P:(DE-HGF)0
|b 24
700 1 _ |a Janoschke, Marco
|0 P:(DE-HGF)0
|b 25
700 1 _ |a Jung, Matthias
|0 P:(DE-HGF)0
|b 26
700 1 _ |a Kiefer, Lena Sophie
|0 P:(DE-HGF)0
|b 27
700 1 _ |a Lohmann, Philipp
|0 P:(DE-Juel1)145110
|b 28
|u fzj
700 1 _ |a Machann, Jürgen
|0 P:(DE-HGF)0
|b 29
700 1 _ |a Moltz, Jan Hendrik
|0 P:(DE-HGF)0
|b 30
700 1 _ |a Nattenmüller, Johanna
|0 P:(DE-HGF)0
|b 31
700 1 _ |a Nonnenmacher, Tobias
|0 P:(DE-HGF)0
|b 32
700 1 _ |a Oerther, Benedict
|0 P:(DE-HGF)0
|b 33
700 1 _ |a Othman, Ahmed E.
|0 P:(DE-HGF)0
|b 34
700 1 _ |a Peisen, Felix
|0 P:(DE-HGF)0
|b 35
700 1 _ |a Schick, Fritz
|0 P:(DE-HGF)0
|b 36
700 1 _ |a Umutlu, Lale
|0 P:(DE-HGF)0
|b 37
700 1 _ |a Wichtmann, Barbara D.
|0 P:(DE-HGF)0
|b 38
700 1 _ |a Zhao, Wenzhao
|0 P:(DE-HGF)0
|b 39
700 1 _ |a Caspers, Svenja
|0 P:(DE-Juel1)131675
|b 40
|u fzj
700 1 _ |a Schlemmer, Heinz-Peter
|0 P:(DE-HGF)0
|b 41
700 1 _ |a Schlett, Christopher L.
|0 P:(DE-HGF)0
|b 42
700 1 _ |a Maier-Hein, Klaus
|0 P:(DE-HGF)0
|b 43
700 1 _ |a Bamberg, Fabian
|0 P:(DE-HGF)0
|b 44
773 _ _ |a 10.1186/s13244-024-01704-w
|g Vol. 15, no. 1, p. 124
|0 PERI:(DE-600)2543323-4
|n 1
|p 124
|t Insights into imaging
|v 15
|y 2024
|x 1869-4101
856 4 _ |u https://juser.fz-juelich.de/record/1027017/files/PDF.pdf
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/1027017/files/PDF.gif?subformat=icon
|x icon
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/1027017/files/PDF.jpg?subformat=icon-1440
|x icon-1440
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/1027017/files/PDF.jpg?subformat=icon-180
|x icon-180
|y OpenAccess
856 4 _ |u https://juser.fz-juelich.de/record/1027017/files/PDF.jpg?subformat=icon-640
|x icon-640
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1027017
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 16
|6 P:(DE-Juel1)143792
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 28
|6 P:(DE-Juel1)145110
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 40
|6 P:(DE-Juel1)131675
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5252
|x 0
914 1 _ |y 2024
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-08-22
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-08-22
915 _ _ |a Fees
|0 StatID:(DE-HGF)0700
|2 StatID
|d 2023-08-22
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Article Processing Charges
|0 StatID:(DE-HGF)0561
|2 StatID
|d 2023-08-22
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b INSIGHTS IMAGING : 2022
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
|d 2024-04-10T15:40:08Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
|d 2024-04-10T15:40:08Z
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b DOAJ : Double anonymous peer review
|d 2024-04-10T15:40:08Z
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2025-01-01
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2025-01-01
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2025-01-01
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2025-01-01
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)INM-3-20090406
|k INM-3
|l Kognitive Neurowissenschaften
|x 0
920 1 _ |0 I:(DE-Juel1)INM-4-20090406
|k INM-4
|l Physik der Medizinischen Bildgebung
|x 1
920 1 _ |0 I:(DE-Juel1)INM-1-20090406
|k INM-1
|l Strukturelle und funktionelle Organisation des Gehirns
|x 2
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)INM-3-20090406
980 _ _ |a I:(DE-Juel1)INM-4-20090406
980 _ _ |a I:(DE-Juel1)INM-1-20090406
980 _ _ |a UNRESTRICTED
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21