Applying an astrophysics modelling tool to improve the diagnosis and treatment of cancers

光的使用是诊断和治疗中各种医学进步的基础。例如，我们可以使用手持设备来检测新生儿中升高的胆红素水平，使用激光对手术组织进行切除，在手术过程中部署相机对癌症组织成像，以及使用光动力疗法摧毁癌细胞。在未来，我们可能能够使用光学加热纳米颗粒治疗肿瘤，或者在不需要活检的情况下诊断乳腺癌。所有这些技术都依赖于对光学辐射和组织之间复杂相互作用的深刻理解。当光在体内传播时，它可以被散射和吸收，它可以跨越不同组织之间的边界，在那里它可以被反射和折射，它的频率可以通过非弹性散射或荧光来改变。此外，光通过的材料可能是高度不均匀和各向异性的，并在各种尺度上显示出复杂的解剖结构。如果我们能够开发出足够复杂的数值模型，我们就可以构建相关组织的数字模型，并在Silico中进行数值实验。我们可以制作模型设备，用大范围的强度和波长照射组织，并研究不同的模型参数如何影响组织的加热、光动力疗法的剂量或荧光光子的检测。此外，这些实验可以快速、廉价和安全地进行。尽管在规模上存在巨大差异，但科学家在模拟人体辐射传递(RT)时面临的物理和数值挑战本质上与计算恒星和星系的RT模型时所面临的挑战相同。这两种体制都包含高散射介质，在大范围内具有复杂的形貌，其中必须考虑多色辐射，并且吸收和散射系数随环境而变化。最重要的是，蒙特卡罗(MC)建模技术(通过大量的光子“包”对光进行建模)的使用已经成为这两个领域的黄金标准。因此，尝试和利用天体物理MC代码中的算法和计算机科学进步并将其应用于生物医学物理是很自然的，这也是这一提议的本质。埃克塞特大学拥有环面蒙特卡罗代码，该代码已被用于模拟各种天体物理现象，从盘状行星的形成到星系中21厘米的辐射。哈里斯和他的团队已经开发了超过15年的圆环。2016年，我们从惠康信托获得资金，以改造Torus来解决生物医学问题。随后，我们获得了为期4年的Carlotta Palmer博士学位，以研究光动力疗法(PDT)在非黑色素瘤皮肤癌治疗中的优化，并获得了为期3.5年的EPSRC DTP研究生学位，以模拟乳房组织中的拉曼散射，以帮助癌症诊断。我们希望聘请一名STFC创新研究员加入我们新成立的生物医学建模团队。这位研究员将与物理学家、数学家、生物学家和临床医生合作，将我们的建模工具应用于乳腺癌和皮肤癌等疾病的诊断和治疗。他们还将与我们的技术转让办公室密切合作，通过与公司和其他非学术组织接触，调查我们代码的商业潜力。在整个奖学金期间，我们将提供所需的培训和指导，以加快研究员的职业生涯，使他们能够成功地申请独立资助。

The use of light is fundamental to a diverse range of medical advances in diagnostics and therapy. For example we can use a handheld devices to detect elevated bilirubin levels in neonates, apply lasers to surgically resect tissue, deploy cameras to image cancerous tissue during surgery, and destroy cancer cells using photodynamic therapy. In the future we may be able to treat tumours using optically heated nanoparticles, or diagnose breast cancer without the necessity for a biopsy. All these technologies rely on a deep understanding of the complex interplay between optical radiation and tissue. As light propagates through the body it can be scattered and absorbed, it can cross boundaries between different tissues where it can be reflected and refracted, and its frequency can be changed by inelastic scattering or fluorescence. Furthermore the material through which the light travels may be highly heterogeneous and anisotropic, and display intricate anatomical structures on a wide variety of scales.If we can develop a numerical model of sufficient complexity we may construct a digital phantom of the relevant tissue, and conduct numerical experiments in silico. We can fabricate model devices, illuminate tissue with a wide range of intensities and wavelengths, and investigate how varying the model parameters affects the heating of the tissue, the dosage for photodynamic therapy, or the detection of fluorescent photons. Furthermore these experiments can be conducted rapidly, cheaply, and safely.Despite the vast differences in scale, the physical and numerical challenges that scientists face when modelling radiative transfer (RT) in the human body are in essence the same as those faced when computing RT models of stars and galaxies. Both regimes contain highly scattering media with complex morphologies on a large range of scales, where polychromatic radiation must be considered and where the absorption and scattering coefficients change with environment. Critically the use of Monte Carlo (MC) modelling techniques (in which light is modelled via a large number of photon 'packets') has become the gold standard in both fields. It is therefore natural to try and exploit the algorithmic and computer science advances that have been made in astrophysical MC codes and apply them to biomedical physics, and this is the essence of this proposal.The University of Exeter is home to the TORUS Monte Carlo code that has been used to model a wide variety of astrophysical phenomena, from planet formation in discs to 21-cm radiation in galaxies. Harries and his team have developed TORUS for over 15 years. In 2016 we obtained funding from the Wellcome Trust to adapt TORUS to tackle biomedical problems. Subsequently we have been awarded a 4-year Carlotta Palmer PhD studentship to investigate the optimisation of photodynamic therapy (PDT) in the treatment of non-melanoma skin cancer, and a 3.5-year EPSRC DTP studentship to model Raman scattering in breast tissue as an aid to cancer diagnosis. We wish to hire an STFC Innovation Fellow to join our nascent biomedical modelling team. The Fellow will work alongside physicists, mathematicians, biologists and clinicians in applying our modelling tool to the diagnosis and treatment of diseases such as breast and skin cancer. They will also work closely with our technology transfer office in investigating the commercial potential of our code by engaging with companies and other non-academic organisations. Throughout the fellowship we will provide the training and mentoring needed to accelerate the Fellow's career to the point at which they can successfully apply for independent funding.