ArticleScientific reports2021
Multiscale computational modeling of cancer growth using features derived from microCT images.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed, 30 citations in OpenAlex.
- 3D multi-omics tumour atlases: from technology to biology and clinical translation.Nature reviews. Cancer · 2026Review
- Leveraging experimental vasculature data for high-resolution brain tumor simulations.Biophysical journal · 2026Article
- ViVo: A Temporal Modeling Framework That Boosts Statistical Power and Minimizes Animal Usage.Journal of medicinal chemistry · 2026Article
- A Roadmap for the Future of Systems Biology in Cancer Research.Cancer research · 2025Review
- Highly multiplexed 3D profiling of cell states and immune niches in human tumors.Nature methods · 2025Article
- Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025Article
- Molecular Crowding by Computational Approaches.Sub-cellular biochemistry · 2025Review
- AMBER: A Modular Model for Tumor Growth, Vasculature and Radiation Response.Bulletin of mathematical biology · 2024Article
- AI driven analysis of MRI to measure health and disease progression in FSHD.Scientific reports · 2024Article
- A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.NPJ systems biology and applications · 2024Review
- Vascular phenotyping of the invasive front in breast cancer using a 3D angiogenesis atlas.Microvascular research · 2023Article
- Novel computational biology modeling system can accurately forecast response to neoadjuvant therapy in early breast cancer.Breast cancer research : BCR · 2023Article
- Immune modulations of the tumor microenvironment in response to phototherapy.Journal of innovative optical health sciences · 2023Article
- Functional biomaterials for biomimetic 3D in vitro tumor microenvironment modeling.In vitro models · 2023Review
- Tumor heterogeneity: preclinical models, emerging technologies, and future applications.Frontiers in oncology · 2023Review
- Inhibition of Ehrlich ascites carcinoma growth by melatonin: Studies with micro-CT.Oncology research · 2023Article
- Nanoconstructs for theranostic application in cancer: Challenges and strategies to enhance the delivery.Frontiers in pharmacology · 2023Review
- Multiscale modeling in the framework of biological systems and its potential for spaceflight biology studies.iScience · 2022Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Advances in medical imaging technologies now allow noninvasive image acquisition from individual patients at high spatiotemporal resolutions. A relatively new effort of predictive oncology is to develop a paradigm for forecasting the future status of an individual tumor given initial conditions and an appropriate mathematical model. The objective of this study was to introduce a comprehensive multiscale computational method to predict cancer and microvascular network growth patterns. A rectangular lattice-based model was designed so different evolutionary scenarios could be simulated and for predicting the impact of diffusible factors on tumor morphology and size. Further, the model allows prediction-based simulation of cell and microvascular behavior. Like a single cell, each agent is fully realized within the model and interactions are governed in part by machine learning methods. This multiscale computational model was developed and incorporated input information from in vivo microscale computed tomography (microCT) images acquired from breast cancer-bearing mice. It was found that as the difference between expansion of the cancer cell population and microvascular network increases, cells undergo proliferation and migration with a greater probability compared to other phenotypes. Overall, multiscale computational model agreed with both theoretical expectations and experimental findings (microCT images) not used during model training.
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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.