ReviewAnnual review of biomedical engineering2020
Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.
Review in Annual review of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed.
- Supervoxel-based multimodal MRI biomarkers reveal tumor heterogeneity in high-grade glioma for prognostic stratification and therapy response prediction.NPJ precision oncology · 2026Article
- Radiomics machine learning model based on multi-sequence MRI for predicting Ki-67 expression level in glioblastoma.Frontiers in molecular biosciences · 2026Article
- Deep manifold learning reveals hidden developmental dynamics of a human embryo model.Science advances · 2025Article
- Individualizing glioma radiotherapy planning by optimization of a data and physics-informed discrete loss.Nature communications · 2025Article
- Predictive Digital Twins with Quantified Uncertainty for Patient-Specific Decision Making in Oncology.ArXiv · 2025Article
- Identifiability and model selection frameworks for models of high-grade glioma response to chemoradiation.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Article
- Validating the predictions of mathematical models describing tumor growth and treatment response.ArXiv · 2025Article
- Editorial: Spatiotemporal & AI trends in neuroscience, neuroimaging, and neurooncology.Frontiers in neuroimaging · 2025Article
- Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancements.The Lancet. Oncology · 2024Review
- Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practice.The Lancet. Oncology · 2024Review
- Fast model calibration for predicting the response of breast cancer to chemotherapy using proper orthogonal decomposition.Journal of computational science · 2024Article
- Linel2D-Net: A deep learning approach to solving 2D linear elastic boundary value problems on image domains.iScience · 2024Article
- A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data.Engineering with computers · 2024Article
- Imaging with spatio-temporal modelling to characterize the dynamics of plant-pathogen lesions.PLoS computational biology · 2023Article
- FDM data driven U-Net as a 2D Laplace PINN solver.Scientific reports · 2023Article
- Ensemble Inversion for Brain Tumor Growth Models With Mass Effect.IEEE transactions on medical imaging · 2023Article
- Patient-specific forecasting of postradiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapse.iScience · 2022Article
- CLAIRE-Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging Applications.Journal of imaging · 2022Article
- Fibre tract segmentation for intraoperative diffusion MRI in neurosurgical patients using tract-specific orientation atlas and tumour deformation modelling.International journal of computer assisted radiology and surgery · 2022Article
- Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy.Advanced drug delivery reviews · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Central nervous system (CNS) tumors come with vastly heterogeneous histologic, molecular, and radiographic landscapes, rendering their precise characterization challenging. The rapidly growing fields of biophysical modeling and radiomics have shown promise in better characterizing the molecular, spatial, and temporal heterogeneity of tumors. Integrative analysis of CNS tumors, including clinically acquired multi-parametric magnetic resonance imaging (mpMRI) and the inverse problem of calibrating biophysical models to mpMRI data, assists in identifying macroscopic quantifiable tumor patterns of invasion and proliferation, potentially leading to improved (
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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.