ReviewBritish journal of cancer2021
Radiomics and radiogenomics in gliomas: a contemporary update.
Review in British journal of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 121 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
121 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Role of radiomics as a predictor of disease recurrence in ovarian cancer: a systematic review.Abdominal radiology (New York) · 2024Pooled it
- Predicting IDH and ATRX mutations in gliomas from radiomic features with machine learning: a systematic review and meta-analysis.Frontiers in radiology · 2024Pooled it
- Visualising spatial heterogeneity in glioblastoma using imaging habitats.Frontiers in oncology · 2022Pooled it
- Malignant transformation of lower-grade glioma: contrast enhancement, extent of resection, and the natural history under interval-censored analysis.Journal of neuro-oncology · 2026Article
- Circulating miRNAs for glioblastoma monitoring: from biofluid to clinical decision.Molecular therapy. Oncology · 2026Review
- Glioblastoma MRI Dataset with Standardized Preprocessing, Expert-Validated Segmentation, and MGMT Profiling.Scientific data · 2026Article
- Integrating Molecular Pathology, Tumor Microenvironment, and Novel Therapies to Overcome Resistance in Glioblastoma.Journal of molecular neuroscience : MN · 2026Review
- Precision reirradiation in recurrent CNS tumors integrating biology techniques and multimodal care.Discover oncology · 2026Review
- Evolving Landscape of Glioblastoma Research: Integrating Therapeutic Advances and Diagnostic Frontiers.Brain sciences · 2026Review
- Development and validation of a deep learning radiomics model based on ultrasound and clinical features to predict prognosis in elderly patients with advanced pancreatic cancer after HIFU therapy.BMC gastroenterology · 2026Article
- Radiomics of T2-weighted MRI for pretreatment prediction of prognosis and temozolomide chemosensitivity in glioma.BMC cancer · 2026Article
- Bridging modalities with AI: a review of AI advances in multimodal biomedical imaging.Communications engineering · 2026Review
- MRI-based clinical radiomics nomogram for the prognostic prediction of adult diffuse low-grade gliomas.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Review
- Multi-institutional MRI-based radiomic pilot study to measure the variations between scanner vendors and imaging sessions.Frontiers in oncology · 2026Article
- Integration of MRI radiomics with immune profiling to predict response to CDK6 inhibitors in high-grade glioma.Frontiers in immunology · 2026Observational
- Glioblastoma-A Contemporary Overview of Epidemiology, Classification, Pathogenesis, Diagnosis, and Treatment: A Review Article.International journal of molecular sciences · 2025Review
- Opportunities and challenges in application of VASARI features in neuro-oncology.Neuro-oncology practice · 2025Review
- GlioSurv: interpretable transformer for multimodal, individualized survival prediction in diffuse glioma.NPJ digital medicine · 2025Article
- Radiomics and radiogenomics in ovarian cancer: a review with a focus on ultrasound applications.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Review
61 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The natural history and treatment landscape of primary brain tumours are complicated by the varied tumour behaviour of primary or secondary gliomas (high-grade transformation of low-grade lesions), as well as the dilemmas with identification of radiation necrosis, tumour progression, and pseudoprogression on MRI. Radiomics and radiogenomics promise to offer precise diagnosis, predict prognosis, and assess tumour response to modern chemotherapy/immunotherapy and radiation therapy. This is achieved by a triumvirate of morphological, textural, and functional signatures, derived from a high-throughput extraction of quantitative voxel-level MR image metrics. However, the lack of standardisation of acquisition parameters and inconsistent methodology between working groups have made validations unreliable, hence multi-centre studies involving heterogenous study populations are warranted. We elucidate novel radiomic and radiogenomic workflow concepts and state-of-the-art descriptors in sub-visual MR image processing, with relevant literature on applications of such machine learning techniques in glioma management.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.