ArticleIEEE transactions on medical imaging2017
Pancreatic Tumor Growth Prediction With Elastic-Growth Decomposition, Image-Derived Motion, and FDM-FEM Coupling.
Article in IEEE transactions on medical imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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.
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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
23 citing papers in PubMed, 53 citations in OpenAlex.
- Validating the predictions of mathematical models describing tumor growth and treatment response.ArXiv · 2025Article
- A Pilot Study on Patient-specific Computational Forecasting of Prostate Cancer Growth during Active Surveillance Using an Imaging-informed Biomechanistic Model.Cancer research communications · 2024Article
- Designing clinical trials for patients who are not average.iScience · 2024Review
- 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
- Prediction of Lung Nodule Progression with an Uncertainty-Aware Hierarchical Probabilistic Network.Diagnostics (Basel, Switzerland) · 2022Article
- Demonstrating the benefits of corrective intraoperative feedback in improving the quality of duodenal hydrogel spacer placement.Medical physics · 2022Article
- Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology.Biophysics reviews · 2022Review
- Modeling of Glioma Growth With Mass Effect by Longitudinal Magnetic Resonance Imaging.IEEE transactions on bio-medical engineering · 2021Article
- Quantitative magnetic resonance imaging and tumor forecasting of breast cancer patients in the community setting.Nature protocols · 2021Review
- Deformation driven Seq2Seq longitudinal tumor and organs-at-risk prediction for radiotherapy.Medical physics · 2021Article
- Integrating Quantitative Assays with Biologically Based Mathematical Modeling for Predictive Oncology.iScience · 2020Review
- Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology.Annual review of biomedical engineering · 2020Review
- Optimal Control Theory for Personalized Therapeutic Regimens in Oncology: Background, History, Challenges, and Opportunities.Journal of clinical medicine · 2020Review
- Spatio-Temporal Convolutional LSTMs for Tumor Growth Prediction by Learning 4D Longitudinal Patient Data.IEEE transactions on medical imaging · 2020Article
- WHERE DID THE TUMOR START? AN INVERSE SOLVER WITH SPARSE LOCALIZATION FOR TUMOR GROWTH MODELS.Inverse problems · 2020Article
- IMAGE-DRIVEN BIOPHYSICAL TUMOR GROWTH MODEL CALIBRATION.SIAM journal on scientific computing : a publication of the Society for Industrial and Applied Mathematics · 2020Article
- An adjoint-based method for a linear mechanically-coupled tumor model: Application to estimate the spatial variation of murine glioma growth based on diffusion weighted magnetic resonance imaging.Computational mechanics · 2019Article
- Mechanism-Based Modeling of Tumor Growth and Treatment Response Constrained by Multiparametric Imaging Data.JCO clinical cancer informatics · 2019Review
- Mathematical models of tumor cell proliferation: A review of the literature.Expert review of anticancer therapy · 2018Review
- Incorporating drug delivery into an imaging-driven, mechanics-coupled reaction diffusion model for predicting the response of breast cancer to neoadjuvant chemotherapy: theory and preliminary clinical results.Physics in medicine and biology · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Pancreatic neuroendocrine tumors are abnormal growths of hormone-producing cells in the pancreas. Unlike the brain which is protected by the skull, the pancreas can be significantly deformed by its surrounding organs. Consequently, the tumor shape differences observable from images at different time points arise from both tumor growth and pancreatic motion, and tumor growth model personalization may be compromised if such motion is ignored. Therefore, we incorporate pancreatic motion information derived from deformable image registration in model personalization. For more accurate mechanical interactions between tumor growth and pancreatic motion, elastic-growth decomposition is used with a hyperelastic constitutive law to model the mass effect, which allows growth modeling while conserving the mechanical properties. Furthermore, a way of coupling the finite difference method and the finite element method is proposed to greatly reduce the computation time. With both 2-[
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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.