Jansen, Robin W.
Roohollahi, Khashayar
Uner, Ogul E.
de Jong, Yvonne
de Bloeme, Christiaan M.
Göricke, Sophia
Sirin, Selma
Maeder, Philippe
Galluzzi, Paolo
Brisse, Hervé J.
Cardoen, Liesbeth
Castelijns, Jonas A.
van der Valk, Paul
Moll, Annette C.
Grossniklaus, Hans
Hubbard, G. Baker
de Jong, Marcus C.
Dorsman, Josephine
de Graaf, Pim
,
Funding for this research was provided by:
KIKA (342)
Hanarth Foundation (MRI-based Deep Learning Segmentation, Quantitative Radiomics in Retinoblastoma)
KWF Kankerbestrijding (10832)
Article History
Received: 2 January 2023
Revised: 30 April 2023
Accepted: 22 June 2023
First Online: 24 August 2023
Declarations
:
: Pim de Graaf had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
: The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
: Two of the authors, K. Roohollahi and M. de Jong, have significant statistical expertise.
: Written informed consent was waived by the Institutional Review Board.
: Institutional Review Board approval was obtained.
: Seventeen patients were previously reported in a study on genetic markers for high-risk retinoblastoma without imaging [], while the current study reports on associations between MRI features and gene expression profiles.16 Hudson LE, Mendoza P, Hudson WH et al (2018) Distinct gene expression profiles define anaplastic grade in retinoblastoma. The American Journal of Pathology 188:2328–2338.Some study subjects or cohorts have not been previously reported.
: