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脑转移瘤生长和治疗反应的数学建模:综述。

Mathematical modeling of brain metastases growth and response to therapies: A review.

机构信息

Mathematical Oncology Laboratory (MOLAB), University of Castilla-La Mancha, Avda. Camilo José Cela s/n, 13071, Ciudad Real, Spain.

出版信息

Math Biosci. 2024 Jul;373:109207. doi: 10.1016/j.mbs.2024.109207. Epub 2024 May 15.

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.

摘要

脑转移瘤(BMs)是最常见的颅内肿瘤类型,也是一个重大的健康问题,约影响 10%至 30%的所有肿瘤患者。尽管取得了重大进展,但脑转移过程和由此产生的病变生长的许多方面仍未得到很好的理解。需要更好地了解这些肿瘤的生长动态和对治疗的反应。数学模型已被证明在癌症研究的不同领域具有推断和预测的价值,但很少有数学作品考虑到脑转移瘤。本综述旨在建立一个统一的平台,并有助于促进新兴的努力,致力于提高我们对这种复杂和具有挑战性的疾病的数学理解。我们专注于脑转移瘤数学建模研究初始阶段的进展以及这些研究获得的重要见解。我们还探讨了数学建模在预测治疗结果和提高面临脑转移瘤的患者的临床决策质量方面的重要作用。

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