IEEE Trans Biomed Eng. 2021 Sep;68(9):2718-2729. doi: 10.1109/TBME.2021.3052345. Epub 2021 Aug 19.
Purposes of this work were i) to develop an in silico model of tumor response to radiotherapy, ii) to perform an exhaustive sensitivity analysis in order to iii) propose a simplified version and iv) to predict biochemical recurrence with both the comprehensive and the reduced model.
A multiscale computational model of tumor response to radiotherapy was developed. It integrated the following radiobiological mechanisms: oxygenation, including hypoxic death; division of tumor cells; VEGF diffusion driving angiogenesis; division of healthy cells and oxygen-dependent response to irradiation, considering, cycle arrest and mitotic catastrophe. A thorough sensitivity analysis using the Morris screening method was performed on 21 prostate computational tissues. Tumor control probability (TCP) curves of the comprehensive model and 15 reduced versions were compared. Logistic regression was performed to predict biochemical recurrence after radiotherapy on 76 localized prostate cancer patients using an output of the comprehensive and the reduced models.
No significant difference was found between the TCP curves of the comprehensive and a simplified version which only considered oxygenation, division of tumor cells and their response to irradiation. Biochemical recurrence predictions using the comprehensive and the reduced models improved those made from pre-treatment imaging parameters (AUC = 0.81 ± 0.02 and 0.82 ± 0.02 vs. 0.75 ± 0.03, respectively).
A reduced model of tumor response to radiotherapy able to predict biochemical recurrence in prostate cancer was obtained.
This reduced model may be used in the future to optimize personalized fractionation schedules.
本研究旨在 i) 开发一种用于预测肿瘤对放射治疗反应的计算模型，ii) 进行全面的敏感性分析，以 iii) 提出简化版本，并 iv) 利用综合模型和简化模型预测生化复发。
开发了一种用于肿瘤对放射治疗反应的多尺度计算模型。它整合了以下放射生物学机制：包括缺氧死亡在内的氧合作用；肿瘤细胞分裂；VEGF 扩散驱动血管生成；健康细胞分裂以及对辐射的氧依赖性反应，同时考虑细胞周期阻滞和有丝分裂灾难。使用 Morris 筛选法对 21 个前列腺计算组织进行了全面的敏感性分析。比较了综合模型和 15 个简化版本的肿瘤控制概率（TCP）曲线。对 76 例局部前列腺癌患者，利用综合模型和简化模型的输出，进行逻辑回归以预测放射治疗后的生化复发。
综合模型和仅考虑氧合作用、肿瘤细胞分裂及其对辐射反应的简化版本的 TCP 曲线没有显著差异。综合模型和简化模型的生化复发预测结果均优于基于治疗前影像学参数的预测结果（AUC=0.81±0.02 和 0.82±0.02 比 0.75±0.03）。
获得了一种能够预测前列腺癌生化复发的简化肿瘤对放射治疗反应模型。
这种简化模型未来可能用于优化个体化分割方案。
