ReviewFrontiers in oncology2021
Current Advances and Challenges in Radiomics of Brain Tumors.
Review in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 50 citations in OpenAlex.
- Objective characterization of displacement of the frontal aslant tract in low-grade glioma: a quantitative tractography study.Neuroradiology · 2026Article
- A Novel Nomogram for Predicting Meningioma Grade Based on Radiomics Features and Clinical Characteristics.Current medical science · 2026Article
- Current applications of radiomics in neurotrauma.Neurosurgical review · 2026Review
- CT radiomics of adenocarcinoma of the esophagogastric junction: machine learning-based prediction of perineural invasion status.World journal of surgical oncology · 2026Article
- DARE-FUSE: domain aligned evidence guided learning for joint brain tumor MRI segmentation and classification.NPJ digital medicine · 2026Article
- Advanced Neuroimaging and Emerging Systemic Therapies in Glioblastoma: Current Evidence and Future Directions.Biomedicines · 2025Review
- Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma.Scientific reports · 2025Article
- Radiomics based on brain-to-tumor interface enables prediction of metastatic tumor type of brain metastasis: a proof-of-concept study.La Radiologia medica · 2025Article
- Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomas.Neuro-oncology · 2025Article
- Development, validation, and visualization of a novel nomogram for predicting clinical outcomes of radiotherapy combined with chemotherapy in locally advanced cervical cancer.Frontiers in oncology · 2025Article
- Preoperative prediction of CNS WHO grade and tumour aggressiveness in intracranial meningioma based on radiomics and structured semantics.Scientific reports · 2024Article
- Reirradiation for diffuse intrinsic pontine glioma: prognostic radiomic factors at progression.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2024Article
- Revolutionizing Brain Tumor Care: Emerging Technologies and Strategies.Biomedicines · 2024Review
- MRI- and DWI-Based Radiomics Features for Preoperatively Predicting Meningioma Sinus Invasion.Journal of imaging informatics in medicine · 2024Article
- Predicting meningioma grades and pathologic marker expression via deep learning.European radiology · 2024Article
- Radiomic features of the hippocampal based on magnetic resonance imaging in the menopausal mouse model linked to neuronal damage and cognitive deficits.Brain imaging and behavior · 2024Article
- Comparison of MRI Sequences to PredictBiomedicines · 2024Article
- Artificial intelligence-based MRI radiomics and radiogenomics in glioma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- MRI-based intratumoral and peritumoral radiomics for preoperative prediction of glioma grade: a multicenter study.Frontiers in oncology · 2024Article
- Artificial Intelligence in Andrology: From Semen Analysis to Image Diagnostics.The world journal of men's health · 2024Review
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Imaging diagnosis is crucial for early detection and monitoring of brain tumors. Radiomics enable the extraction of a large mass of quantitative features from complex clinical imaging arrays, and then transform them into high-dimensional data which can subsequently be mined to find their relevance with the tumor's histological features, which reflect underlying genetic mutations and malignancy, along with grade, progression, therapeutic effect, or even overall survival (OS). Compared to traditional brain imaging, radiomics provides quantitative information linked to meaningful biologic characteristics and application of deep learning which sheds light on the full automation of imaging diagnosis. Recent studies have shown that radiomics' application is broad in identifying primary tumor, differential diagnosis, grading, evaluation of mutation status and aggression, prediction of treatment response and recurrence in pituitary tumors, gliomas, and brain metastases. In this descriptive review, besides establishing a general understanding among protocols, results, and clinical significance of these studies, we further discuss the current limitations along with future development of radiomics.
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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.