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Radiomics risk score may be a potential imaging biomarker for predicting survival in isocitrate dehydrogenase wild-type lower-grade gliomas.
Park, Chae Jung; Han, Kyunghwa; Kim, Hwiyoung; Ahn, Sung Soo; Choi, Yoon Seong; Park, Yae Won; Chang, Jong Hee; Kim, Se Hoon; Jain, Rajan; Lee, Seung-Koo.
Afiliação
  • Park CJ; Department of Radiology, Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.
  • Han K; Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea.
  • Kim H; Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Yonsei University College of Medicine, Seoul, South Korea.
  • Ahn SS; Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea. SUNGSOO@yuhs.ac.
  • Choi YS; Department of Radiology, Center for Clinical Imaging Data Science, Research Institute of Radiological Sciences, Yonsei University College of Medicine, Seoul, South Korea. SUNGSOO@yuhs.ac.
  • Park YW; Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea.
  • Chang JH; Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea.
  • Kim SH; Department of Neurosurgery, Yonsei University College of Medicine, Seoul, South Korea.
  • Jain R; Department of Pathology, Yonsei University College of Medicine, Seoul, South Korea.
  • Lee SK; Department of Radiology, Langone Medical Center, New York University School of Medicine, New York, NY, USA.
Eur Radiol ; 30(12): 6464-6474, 2020 Dec.
Article em En | MEDLINE | ID: mdl-32740813
ABSTRACT

OBJECTIVES:

Isocitrate dehydrogenase wild-type (IDHwt) lower-grade gliomas of histologic grades II and III follow heterogeneous clinical outcomes, which necessitates risk stratification. We aimed to evaluate whether radiomics from MRI would allow prediction of overall survival in patients with IDHwt lower-grade gliomas and to investigate the added prognostic value of radiomics over clinical features.

METHODS:

Preoperative MRIs of 117 patients with IDHwt lower-grade gliomas from January 2007 to February 2018 were retrospectively analyzed. The external validation cohort consisted of 33 patients from The Cancer Genome Atlas. A total of 182 radiomic features were extracted. Radiomics risk scores (RRSs) for overall survival were derived from the least absolute shrinkage and selection operator (LASSO) and elastic net. Multivariable Cox regression analyses, including clinical features and RRSs, were performed. The integrated areas under the receiver operating characteristic curves (iAUCs) from models with and without RRSs were calculated for comparisons. The prognostic value of RRS was assessed in the validation cohort.

RESULTS:

The RRS derived from LASSO and elastic net independently predicted survival with hazard ratios of 9.479 (95% confidence interval [CI], 3.220-27.847) and 6.148 (95% CI, 3.009-12.563), respectively. Those RRSs enhanced model performance for predicting overall survival (iAUC increased to 0.780-0.797 from 0.726), which was externally validated. The RRSs stratified IDHwt lower-grade gliomas in the validation cohort with significantly different survival.

CONCLUSION:

Radiomics has the potential for noninvasive risk stratification and can improve prediction of overall survival in patients with IDHwt lower-grade gliomas when integrated with clinical features. KEY POINTS • Isocitrate dehydrogenase wild-type lower-grade gliomas with histologic grades II and III follow heterogeneous clinical outcomes, which necessitates further risk stratification. • Radiomics risk scores derived from MRI independently predict survival even after incorporating strong clinical prognostic features (hazard ratios 6.148-9.479). • Radiomics risk scores derived from MRI have the potential to improve survival prediction when added to clinical features (integrated areas under the receiver operating characteristic curves increased from 0.726 to 0.780-0.797).
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Imageamento por Ressonância Magnética / Glioma Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Encefálicas / Imageamento por Ressonância Magnética / Glioma Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article