ArticleNeuroImage. Clinical2018
Towards patient-specific modeling of brain tumor growth and formation of secondary nodes guided by DTI-MRI.
Article in NeuroImage. Clinical, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03458455 (Improved Therapy Response Assessment in Metastatic Brain Tumors), which is not on this map. Cited by 23 papers, 1 of them a synthesis 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.
Improved Therapy Response Assessment in Metastatic Brain Tumors
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.
- Digital Twins in Neuro-Oncology: A Systematic Review of Current Implementations, Technical Strategies, and Clinical Applications.Radiology. Imaging cancer · 2026Pooled it
- Mapping radiosensitivity in glioblastoma using MR elastography and biomechanical modeling.Scientific reports · 2026Article
- A multiphysics computational model of focused ultrasound-enhanced drug delivery using temperature-sensitive liposomes.Biomechanics and modeling in mechanobiology · 2026Article
- A predictive multiphysics framework for optimizing focused ultrasound-assisted immune checkpoint blockade.Frontiers in immunology · 2026Article
- From images to physics-based computational models to digital twins: a framework for personalized cancer therapies.Frontiers in radiology · 2026Article
- Optimizing therapeutic outcomes with Mechanotherapy and Ultrasound Sonopermeation in solid tumors.PLoS computational biology · 2025Article
- Novel radiotherapy target definition using AI-driven predictions of glioblastoma recurrence from metabolic and diffusion MRI.NPJ digital medicine · 2025Article
- Biomarkers of mRNA vaccine efficacy derived from mechanistic modeling of tumor-immune interactions.PLoS computational biology · 2025Article
- Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.Nature reviews. Cancer · 2025Review
- Heterogeneous Mechanical Stress and Interstitial Fluid Flow Predictions Derived from DCE-MRI for Rat U251N Orthotopic Gliomas.Annals of biomedical engineering · 2024Article
- Applications of generative adversarial networks in neuroimaging and clinical neuroscience.NeuroImage · 2023Review
- Data-driven spatio-temporal modelling of glioblastoma.Royal Society open science · 2023Review
- Coupling solid and fluid stresses with brain tumour growth and white matter tract deformations in a neuroimaging-informed model.Biomechanics and modeling in mechanobiology · 2022Article
- Feasibility and clinical usefulness of modelling glioblastoma migration in adjuvant radiotherapy.Zeitschrift fur medizinische Physik · 2022Article
- Network analysis shows decreased ipsilesional structural connectivity in glioma patients.Communications biology · 2022Article
- Article
- A computational model of glioma reveals opposing, stiffness-sensitive effects of leaky vasculature and tumor growth on tissue mechanical stress and porosity.Biomechanics and modeling in mechanobiology · 2021Article
- Imaging acute effects of bevacizumab on tumor vascular kinetics in a preclinical orthotopic model of U251 glioma.NMR in biomedicine · 2021Article
- In Silico Mathematical Modelling for Glioblastoma: A Critical Review and a Patient-Specific Case.Journal of clinical medicine · 2021Review
- Retrospective analysis of hemispheric structural network change as a function of location and size of glioma.Brain communications · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Previous studies to simulate brain tumor progression, often investigate either temporal changes in cancer cell density or the overall tissue-level growth of the tumor mass. Here, we developed a computational model to bridge these two approaches. The model incorporates the tumor biomechanical response at the tissue level and accounts for cellular events by modeling cancer cell proliferation, infiltration to surrounding tissues, and invasion to distant locations. Moreover, acquisition of high resolution human data from anatomical magnetic resonance imaging, diffusion tensor imaging and perfusion imaging was employed within the simulations towards a realistic and patient specific model. The model predicted the intratumoral mechanical stresses to range from 20 to 34 kPa, which caused an up to 4.5 mm displacement to the adjacent healthy tissue. Furthermore, the model predicted plausible cancer cell invasion patterns within the brain along the white matter fiber tracts. Finally, by varying the tumor vascular density and its invasive outer ring thickness, our model showed the potential of these parameters for guiding the timing (83-90 days) of cancer cell distant invasion as well as the number (0-2 sites) and location (temportal and/or parietal lobe) of the invasion sites.
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What OpenQuestion holds
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.