Related Experiment Video
Updated: Jul 20, 2026
Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging
Published on: June 7, 2020
Mathematical modeling of brain metastases growth and response to therapies: A review
Beatriz Ocaña-Tienda1, Víctor M Pérez-García1
1Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Avda. Camilo José Cela s/n, 13071, Ciudad Real, Spain.
Abstract:
Brain metastases (BMs) are the most common intracranial tumor type and a significant health concern, affecting approximately 10% to 30% of all oncological patients. Although significant progress is being made, many aspects of the metastatic process to the brain and the growth of the resulting lesions are still not well understood. There is a need for an improved understanding of the growth dynamics and the response to treatment of these tumors. Mathematical models have been proven valuable for drawing inferences and making predictions in different fields of cancer research, but few mathematical works have considered BMs. This comprehensive review aims to establish a unified platform and contribute to fostering emerging efforts dedicated to enhancing our mathematical understanding of this intricate and challenging disease. We focus on the progress made in the initial stages of mathematical modeling research regarding BMs and the significant insights gained from such studies. We also explore the vital role of mathematical modeling in predicting treatment outcomes and enhancing the quality of clinical decision-making for patients facing BMs.
Insights
Mathematical modeling offers new insights into brain metastases (BMs), the most common brain tumors. This review synthesizes current research to improve understanding of BMs growth and treatment response.
Area of Science:
- Oncology
- Mathematical Biology
- Biophysics
Background:
- Brain metastases (BMs) represent a significant oncological challenge, impacting 10-30% of cancer patients.
- The metastatic process and lesion growth in the brain remain incompletely understood.
- Existing mathematical models for cancer research have not extensively addressed BMs.
Purpose of the Study:
- To review and consolidate mathematical modeling approaches for brain metastases.
- To foster a unified platform for research on BMs.
- To enhance the understanding of BMs growth dynamics and treatment response.
Main Methods:
- Comprehensive literature review of mathematical modeling studies on BMs.
- Analysis of insights gained from existing mathematical models.
- Exploration of the role of modeling in predicting treatment outcomes.
Main Results:
- Mathematical models provide valuable inferences and predictions for cancer research.
- Early-stage mathematical modeling of BMs has yielded significant insights.
- Modeling aids in understanding tumor growth and response to therapy.
Conclusions:
- Mathematical modeling is crucial for advancing the understanding of brain metastases.
- This review establishes a foundation for future mathematical research on BMs.
- Modeling can improve clinical decision-making for patients with BMs.
Related Concept Videos
01:27Pharmacodynamic Models: Overview
01:29Pharmacodynamic Models: Direct Effect Model and Indirect Response Model