Badoual M, Gerin C, Deroulers C, Grammaticos B, Llitjos J-F, Oppenheim C, Varlet P, Pallud J
Laboratoire IMNC, UMR 8165, CNRS, Univ. Paris-Sud, 91405, Orsay, France; Univ Paris Diderot, 75013, Paris, France.
Cell Prolif. 2014 Aug;47(4):369-80. doi: 10.1111/cpr.12114. Epub 2014 Jun 19.
Diffuse low-grade gliomas are characterized by slow growth. Despite appropriate treatment, they change inexorably into more aggressive forms, jeopardizing the patient's life. Optimizing treatments, for example with the use of mathematical modelling, could help to prevent tumour regrowth and anaplastic transformation. Here, we present a model of the effect of radiotherapy on such tumours. Our objective is to explain observed delay of tumour regrowth following radiotherapy and to predict its duration.
We have used a migration-proliferation model complemented by an equation describing appearance and draining of oedema. The model has been applied to clinical data of tumour radius over time, for a population of 28 patients.
We were able to show that draining of oedema accounts for regrowth delay after radiotherapy and have been able to fit the clinical data in a robust way. The model predicts strong correlation between high proliferation coefficient and low progression-free gain of lifetime, due to radiotherapy among the patients, in agreement with clinical studies. We argue that, with reasonable assumptions, it is possible to predict (precision ~20%) regrowth delay after radiotherapy and the gain of lifetime due to radiotherapy.
Our oedema-based model provides an early estimation of individual duration of tumour response to radiotherapy and thus, opens the door to the possibility of personalized medicine.
弥漫性低级别胶质瘤的特点是生长缓慢。尽管进行了适当治疗,但它们仍会不可避免地转变为更具侵袭性的形式,危及患者生命。优化治疗方法,例如使用数学建模,可能有助于防止肿瘤复发和间变转化。在此,我们提出一种放疗对这类肿瘤影响的模型。我们的目标是解释放疗后观察到的肿瘤复发延迟现象,并预测其持续时间。
我们使用了一个迁移 - 增殖模型,并辅以一个描述水肿出现和消退的方程。该模型已应用于28名患者群体的肿瘤半径随时间变化的临床数据。
我们能够证明水肿消退是放疗后肿瘤复发延迟的原因,并且能够以稳健的方式拟合临床数据。该模型预测,在患者中,由于放疗,高增殖系数与低无进展生存期获益之间存在强相关性,这与临床研究结果一致。我们认为,在合理假设的情况下,可以预测(精度约为20%)放疗后的肿瘤复发延迟以及放疗带来的生存期获益。
我们基于水肿的模型提供了对放疗后肿瘤个体反应持续时间的早期估计,从而为个性化医疗开辟了可能性。