Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Radiology ; 307(5): e222264, 2023 06.
Artigo em Inglês | MEDLINE | ID: mdl-37191489

RESUMO

Background MYCN-amplified RB1 wild-type (MYCNARB1+/+) retinoblastoma is a rare but clinically important subtype of retinoblastoma due to its aggressive character and relative resistance to typical therapeutic approaches. Because biopsy is not indicated in retinoblastoma, specific MRI features might be valuable to identify children with this genetic subtype. Purpose To define the MRI phenotype of MYCNARB1+/+ retinoblastoma and evaluate the ability of qualitative MRI features to help identify this specific genetic subtype. Materials and Methods In this retrospective, multicenter, case-control study, MRI scans in children with MYCNARB1+/+ retinoblastoma and age-matched children with RB1-/- subtype retinoblastoma were included (case-control ratio, 1:4; scans acquired from June 2001 to February 2021; scans collected from May 2018 to October 2021). Patients with histopathologically confirmed unilateral retinoblastoma, genetic testing (RB1/MYCN status), and MRI scans were included. Associations between radiologist-scored imaging features and diagnosis were assessed with the Fisher exact test or Fisher-Freeman-Halton test, and Bonferroni-corrected P values were calculated. Results A total of 110 patients from 10 retinoblastoma referral centers were included: 22 children with MYCNARB1+/+ retinoblastoma and 88 control children with RB1-/- retinoblastoma. Children in the MYCNARB1+/+ group had a median age of 7.0 months (IQR, 5.0-9.0 months) (13 boys), while children in the RB1-/- group had a median age of 9.0 months (IQR, 4.6-13.4 months) (46 boys). MYCNARB1+/+ retinoblastomas were typically peripherally located (in 10 of 17 children; specificity, 97%; P < .001) and exhibited plaque or pleomorphic shape (in 20 of 22 children; specificity, 51%; P = .011) with irregular margins (in 16 of 22 children; specificity, 70%; P = .008) and extensive retina folding with vitreous enclosure (specificity, 94%; P < .001). MYCNARB1+/+ retinoblastomas showed peritumoral hemorrhage (in 17 of 21 children; specificity, 88%; P < .001), subretinal hemorrhage with a fluid-fluid level (in eight of 22 children; specificity, 95%; P = .005), and strong anterior chamber enhancement (in 13 of 21 children; specificity, 80%; P = .008). Conclusion MYCNARB1+/+ retinoblastomas show distinct MRI features that could enable early identification of these tumors. This may improve patient selection for tailored treatment in the future. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rollins in this issue.


Assuntos
Neoplasias da Retina , Retinoblastoma , Humanos , Retinoblastoma/diagnóstico por imagem , Retinoblastoma/genética , Proteína Proto-Oncogênica N-Myc/genética , Estudos Retrospectivos , Estudos de Casos e Controles , Neoplasias da Retina/diagnóstico por imagem , Neoplasias da Retina/genética , Ubiquitina-Proteína Ligases/genética , Proteínas de Ligação a Retinoblastoma/genética
2.
Sci Rep ; 14(1): 25103, 2024 10 23.
Artigo em Inglês | MEDLINE | ID: mdl-39443629

RESUMO

MYCN-amplified RB1 wild-type (MYCNampRB1+/+) retinoblastoma is a rare and aggressive subtype, often resistant to standard therapies. Identifying unique MRI features is crucial for diagnosing this subtype, as biopsy is not recommended. This study aimed to differentiate MYCNampRB1+/+ from the most prevalent RB1-/- retinoblastoma using pretreatment MRI and radiomics. Ninety-eight unilateral retinoblastoma patients (19 MYCN cases and 79 matched controls) were included. Tumors on T2-weighted MR images were manually delineated and validated by experienced radiologists. Radiomics analysis extracted 120 features per tumor. Several combinations of feature selection methods, oversampling techniques and machine learning (ML) classifiers were evaluated in a repeated fivefold cross-validation machine learning pipeline to yield the best-performing prediction model for MYCN. The best model used univariate feature selection, data oversampling (duplicating MYCN cases), and logistic regression classifier, achieving a mean AUC of 0.78 (SD 0.12). SHAP analysis highlighted lower sphericity, higher flatness, and greater gray-level heterogeneity as predictive for MYCNampRB1+/+ status, yielding an AUC of 0.81 (SD 0.11). This study shows the potential of MRI-based radiomics to distinguish MYCNampRB1+/+ and RB1-/- retinoblastoma subtypes.


Assuntos
Imageamento por Ressonância Magnética , Proteína Proto-Oncogênica N-Myc , Proteínas de Ligação a Retinoblastoma , Retinoblastoma , Ubiquitina-Proteína Ligases , Humanos , Retinoblastoma/genética , Retinoblastoma/diagnóstico por imagem , Retinoblastoma/patologia , Proteína Proto-Oncogênica N-Myc/genética , Feminino , Imageamento por Ressonância Magnética/métodos , Estudos de Casos e Controles , Masculino , Estudos Retrospectivos , Proteínas de Ligação a Retinoblastoma/genética , Ubiquitina-Proteína Ligases/genética , Pré-Escolar , Lactente , Neoplasias da Retina/genética , Neoplasias da Retina/diagnóstico por imagem , Neoplasias da Retina/patologia , Aprendizado de Máquina , Mutação , Diagnóstico Diferencial , Criança , Radiômica
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA