Correlation of gene expression with magnetic resonance imaging features of retinoblastoma: a multi-center radiogenomics validation study.
Gene expression
MRI
Radiogenomics
Retinoblastoma
Validation
Journal
European radiology
ISSN: 1432-1084
Titre abrégé: Eur Radiol
Pays: Germany
ID NLM: 9114774
Informations de publication
Date de publication:
24 Aug 2023
24 Aug 2023
Historique:
received:
02
01
2023
accepted:
22
06
2023
revised:
30
04
2023
medline:
24
8
2023
pubmed:
24
8
2023
entrez:
24
8
2023
Statut:
aheadofprint
Résumé
To validate associations between MRI features and gene expression profiles in retinoblastoma, thereby evaluating the repeatability of radiogenomics in retinoblastoma. In this retrospective multicenter cohort study, retinoblastoma patients with gene expression data and MRI were included. MRI features (scored blinded for clinical data) and matched genome-wide gene expression data were used to perform radiogenomic analysis. Expression data from each center were first separately processed and analyzed. The end product normalized expression values from different sites were subsequently merged by their Z-score to permit cross-sites validation analysis. The MRI features were non-parametrically correlated with expression of photoreceptorness (radiogenomic analysis), a gene expression signature informing on disease progression. Outcomes were compared to outcomes in a previous described cohort. Thirty-six retinoblastoma patients were included, 15 were female (42%), and mean age was 24 (SD 18) months. Similar to the prior evaluation, this validation study showed that low photoreceptorness gene expression was associated with advanced stage imaging features. Validated imaging features associated with low photoreceptorness were multifocality, a tumor encompassing the entire retina or entire globe, and a diffuse growth pattern (all p < 0.05). There were a number of radiogenomic associations that were also not validated. A part of the radiogenomic associations could not be validated, underlining the importance of validation studies. Nevertheless, cross-center validation of imaging features associated with photoreceptorness gene expression highlighted the capability radiogenomics to non-invasively inform on molecular subtypes in retinoblastoma. Radiogenomics may serve as a surrogate for molecular subtyping based on histopathology material in an era of eye-sparing retinoblastoma treatment strategies. • Since retinoblastoma is increasingly treated using eye-sparing methods, MRI features informing on molecular subtypes that do not rely on histopathology material are important. • A part of the associations between retinoblastoma MRI features and gene expression profiles (radiogenomics) were validated. • Radiogenomics could be a non-invasive technique providing information on the molecular make-up of retinoblastoma.
Identifiants
pubmed: 37615761
doi: 10.1007/s00330-023-10054-y
pii: 10.1007/s00330-023-10054-y
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : KIKA
ID : 342
Organisme : Hanarth Foundation
ID : MRI-based Deep Learning Segmentation
Organisme : Hanarth Foundation
ID : Quantitative Radiomics in Retinoblastoma
Organisme : KWF Kankerbestrijding
ID : 10832
Informations de copyright
© 2023. The Author(s).
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