Falco Jacopo, Agosti Abramo, Vetrano Ignazio G, Bizzi Alberto, Restelli Francesco, Broggi Morgan, Schiariti Marco, DiMeco Francesco, Ferroli Paolo, Ciarletta Pasquale, Acerbi Francesco
Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy.
MOX, Department of Mathematics, Politecnico di Milano, 20133 Milan, Italy.
J Clin Med. 2021 May 17;10(10):2169. doi: 10.3390/jcm10102169.
Glioblastoma extensively infiltrates the brain; despite surgery and aggressive therapies, the prognosis is poor. A multidisciplinary approach combining mathematical, clinical and radiological data has the potential to foster our understanding of glioblastoma evolution in every single patient, with the aim of tailoring therapeutic weapons. In particular, the ultimate goal of biomathematics for cancer is the identification of the most suitable theoretical models and simulation tools, both to describe the biological complexity of carcinogenesis and to predict tumor evolution. In this report, we describe the results of a critical review about different mathematical models in neuro-oncology with their clinical implications. A comprehensive literature search and review for English-language articles concerning mathematical modelling in glioblastoma has been conducted. The review explored the different proposed models, classifying them and indicating the significative advances of each one. Furthermore, we present a specific case of a glioblastoma patient in which our recently proposed innovative mechanical model has been applied. The results of the mathematical models have the potential to provide a relevant benefit for clinicians and, more importantly, they might drive progress towards improving tumor control and patient's prognosis. Further prospective comparative trials, however, are still necessary to prove the impact of mathematical neuro-oncology in clinical practice.
胶质母细胞瘤会广泛浸润大脑；尽管进行了手术和积极治疗，但其预后仍然很差。将数学、临床和放射学数据相结合的多学科方法有潜力促进我们对每位胶质母细胞瘤患者病情发展的理解，以便量身定制治疗手段。特别是，癌症生物数学的最终目标是识别最合适的理论模型和模拟工具，既能描述致癌过程的生物学复杂性，又能预测肿瘤的发展。在本报告中，我们描述了对神经肿瘤学中不同数学模型及其临床意义进行批判性综述的结果。我们对有关胶质母细胞瘤数学建模的英文文章进行了全面的文献检索和综述。该综述探讨了不同的模型提议，对它们进行分类并指出每个模型的重要进展。此外，我们展示了一位胶质母细胞瘤患者的具体病例，其中应用了我们最近提出的创新力学模型。数学模型的结果有可能为临床医生带来切实的益处，更重要的是，它们可能推动在改善肿瘤控制和患者预后方面取得进展。然而，仍需要进一步的前瞻性对比试验来证明数学神经肿瘤学在临床实践中的影响。
