Department of Oncology, Medical Physics Unit, Montreal, QC, Canada.
Phys Med Biol. 2012 Jun 7;57(11):R75-97. doi: 10.1088/0031-9155/57/11/R75. Epub 2012 May 9.
Radiobiological models are essential components of modern radiotherapy. They are increasingly applied to optimize and evaluate the quality of different treatment planning modalities. They are frequently used in designing new radiotherapy clinical trials by estimating the expected therapeutic ratio of new protocols. In radiobiology, the therapeutic ratio is estimated from the expected gain in tumour control probability (TCP) to the risk of normal tissue complication probability (NTCP). However, estimates of TCP/NTCP are currently based on the deterministic and simplistic linear-quadratic formalism with limited prediction power when applied prospectively. Given the complex and stochastic nature of the physical, chemical and biological interactions associated with spatial and temporal radiation induced effects in living tissues, it is conjectured that methods based on Monte Carlo (MC) analysis may provide better estimates of TCP/NTCP for radiotherapy treatment planning and trial design. Indeed, over the past few decades, methods based on MC have demonstrated superior performance for accurate simulation of radiation transport, tumour growth and particle track structures; however, successful application of modelling radiobiological response and outcomes in radiotherapy is still hampered with several challenges. In this review, we provide an overview of some of the main techniques used in radiobiological modelling for radiotherapy, with focus on the MC role as a promising computational vehicle. We highlight the current challenges, issues and future potentials of the MC approach towards a comprehensive systems-based framework in radiobiological modelling for radiotherapy.
放射生物学模型是现代放射治疗的重要组成部分。它们越来越多地被应用于优化和评估不同治疗计划方式的质量。它们经常被用于设计新的放射治疗临床试验，通过估计新方案的预期治疗比来评估其效果。在放射生物学中，治疗比是通过估计肿瘤控制概率（TCP）的预期增益和正常组织并发症概率（NTCP）的风险来估计的。然而，目前 TCP/NTCP 的估计值是基于确定性和简单的线性二次公式，当应用于前瞻性研究时，预测能力有限。鉴于与活组织中时空辐射诱导效应相关的物理、化学和生物相互作用的复杂和随机性质，人们推测基于蒙特卡罗（MC）分析的方法可能会为放射治疗计划和试验设计提供更好的 TCP/NTCP 估计值。事实上，在过去几十年中，基于 MC 的方法已经证明了在准确模拟辐射输运、肿瘤生长和粒子轨迹结构方面的优越性能；然而，在放射生物学反应和结果的建模方面，成功应用建模方法仍然存在几个挑战。在这篇综述中，我们提供了放射生物学模型在放射治疗中的一些主要技术的概述，重点介绍了 MC 作为一种有前途的计算工具的作用。我们强调了 MC 方法在放射生物学模型中的当前挑战、问题和未来潜力，旨在建立一个全面的基于系统的框架。
