ArticleEuropean radiology2018
Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma.
Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.
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Who cites it
44 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Conventional MRI features of adult diffuse glioma molecular subtypes: a systematic review.Neuroradiology · 2021Pooled it
- Imaging biomarkers for detecting IDH mutations and monitoring response to novel targeted therapies: Current insights and future perspectives.Neuro-oncology · 2026Review
- Predicting IDH Mutation in Glioma Patients Using Deep Learning Algorithms with Conformal Prediction.Journal of imaging informatics in medicine · 2026Article
- Advanced MRI, Radiomics and Radiogenomics in Unravelling Incidental Glioma Grading and Genetic Status: Where Are We?Medicina (Kaunas, Lithuania) · 2025Review
- Radiomics and AI-Based Prediction of MGMT Methylation Status in Glioblastoma Using Multiparametric MRI: A Hybrid Feature Weighting Approach.Diagnostics (Basel, Switzerland) · 2025Article
- Structured reporting of gliomas based on VASARI criteria to improve report content and consistency.BMC medical imaging · 2025Article
- Impact of Sex Hormones on Glioblastoma: Sex-Related Differences and Neuroradiological Insights.Life (Basel, Switzerland) · 2024Review
- Preoperative prediction of MGMT promoter methylation in glioblastoma based on multiregional and multi-sequence MRI radiomics analysis.Scientific reports · 2024Article
- Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.BMC medical imaging · 2024Article
- Artificial intelligence-based MRI radiomics and radiogenomics in glioma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- The Convergence of Radiology and Genomics: Advancing Breast Cancer Diagnosis with Radiogenomics.Cancers · 2024Review
- Current Status of Cancer Genomics and Imaging Phenotypes: What Radiologists Need to Know.Radiology. Imaging cancer · 2023Review
- Article
- Magnetic Resonance Imaging of Primary Adult Brain Tumors: State of the Art and Future Perspectives.Biomedicines · 2023Review
- Challenges and opportunities for advanced neuroimaging of glioblastoma.The British journal of radiology · 2023Review
- Beyond Imaging and Genetic Signature in Glioblastoma: Radiogenomic Holistic Approach in Neuro-Oncology.Biomedicines · 2022Review
- Noninvasive Determination of the IDH Status of Gliomas Using MRI and MRI-Based Radiomics: Impact on Diagnosis and Prognosis.Current oncology (Toronto, Ont.) · 2022Review
- Gamma distribution model of diffusion MRI for evaluating the isocitrate dehydrogenase mutation status of glioblastomas.The British journal of radiology · 2022Article
- Radiogenomic Predictors of Recurrence in Glioblastoma-A Systematic Review.Journal of personalized medicine · 2022Review
- Article
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15 authors.
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Abstract
objectivesTo assess the association between MR imaging features and major genomic profiles in glioblastoma.
methodsQualitative and quantitative imaging features such as volumetrics and histogram analysis from normalised CBV (nCBV) and ADC (nADC) were evaluated based on both T2WI and CET1WI. The imaging parameters of different genetic profile groups were compared and regression analyses were used for identifying imaging-molecular associations. Progression-free survival (PFS) was analysed by a Kaplan-Meier test and Cox proportional hazards model.
resultsAn IDH mutation was observed in 18/176 patients, and ATRX loss was positive in 17/158 of the IDH-wt cases. The IDH-mut group showed a larger volume on T2WI and a higher volume ratio between T2WI and CET1WI than the IDH-wt group (p < 0.05). In the IDH-mut group, higher mean nADC values were observed compared with the IDH-wt tumours (p < 0.05). Among the IDH-wt tumours, IDH-wt, ATRX-loss tumours revealed higher 5th percentile nADC values than the IDH-wt, ATRX-noloss tumours (p = 0.03). PFS was the longest in the IDH-mut group, followed by the IDH-wt, ATRX-loss groups and the IDH-wt, ATRX-noloss groups, consecutively (p < 0.05). We found significant associations of PFS with the genetic profiles and imaging parameters.
conclusionMajor genetic profiles of glioblastoma showed a significant association with MR imaging features, along with some genetic profiles, which are independent prognostic parameters for GBM. KEY POINTS: • Significant correlation exists between radiological parameters such as volumetric and ADC values and major genomic profiles such as IDH mutation and ATRX loss status • Radiological parameters such as the ADC value were feasible predictors of glioblastoma patients' prognosis • Imaging features can predict major genomic profiles of the tumours and the prognosis of glioblastoma patients.
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