An integrated MRI tool to map brain microvascular and metabolic function: improving imaging diagnostics for human brain disease

肿瘤、头部损伤、癫痫、多发性硬化症和痴呆症等脑部疾病给患者及其照顾者带来了相当大的个人、社会和经济代价。虽然磁共振成像(MRI)在过去40年里彻底改变了许多大脑疾病的管理，但仍需要更好的工具来量化大脑的能量供应(从血流和血管功能的角度)，并从代谢功能的角度来量化能量的使用。例如，就最常见的脑瘤--胶质瘤而言，我们缺乏关于组织功能异质性的详细信息，无法帮助指导更好的治疗，如更有针对性和个性化的联合放射治疗和药物计划。对肿瘤微环境的更多了解也将促进更有效的治疗方法的发展。对于高级别胶质瘤，特别是胶质母细胞瘤，预后仍然很差，这突显了临床的迫切需求。最近，我们加的夫大学脑研究成像中心(Cubric)和其他人开发了基于MRI的工具(称为双校准fMRI)来绘制整个人脑的地图，空间分辨率为几毫米，大脑消耗的氧气量(称为CMRO2)以及血液供应效率的测量。CMRO2反映神经活动，并可随着肿瘤等疾病的变化而改变，肿瘤是指细胞增殖和能量代谢改变的疾病。了解脑血管的功能特性和脑组织的氧气状况对于了解血液供应是否充足或血管系统是否异常非常重要，因为血管增殖的肿瘤经常会出现这种情况。我们新开发的方法在揭示多发性硬化症和癫痫患者脑组织能量消耗的异常方面显示出了希望。在癫痫患者中，通过识别大脑中代谢异常低的区域，他们可能会提供一种替代使用基于辐射的PET扫描来评估脑外科患者的方法。但是，为了产生更广泛的临床影响，有必要进一步推进MRI和数据分析，以便它们能够在最初的临床试验中用于商业开发和常规临床使用。拟议项目的三分之二将解决工程和物理科学方面的挑战，以(I)通过优化MRI数据采集和分析，将数据采集速度加快到约10分钟，这是临床上可行的时间；(Ii)通过收集额外的MRI信息和组织特性的详细生物物理模型，扩大我们可以可靠测量的组织病理范围；以及(Iii)实施基于高效人工智能(神经网络)的数据分析，可以将图像快速提供给MRI扫描仪的临床医生。其余三分之一的项目将展示该方法的可行性及其在脑瘤(胶质瘤)中的应用价值。我们的目标是展示我们可以绘制出肿瘤组织的异质性地图，这些地图可以揭示肿瘤的类型，肿瘤在哪里活跃生长，哪里对治疗有反应和没有反应，以及放射治疗可能损害健康组织，所有这些都有助于指导治疗决策，以实现最大的疗效。我们与工业界和NHS的合作伙伴关系是我们提案成功的核心。西门子将为开发核磁共振技术贡献其在Cubric的现场科学家的专业知识。维尔德雷癌症中心，南威尔士的主要肿瘤学中心，将合作进行临床试点研究，并帮助评估成像，以利于未来患者的利益。我们的合作伙伴将帮助我们将这些方法带到该项目的关键时刻，如果成功，将用于医疗保健的商业开发和更大规模的临床试验，以演示如何将这些方法用于临床实践中的诊断、治疗计划和监测。

Brain diseases such as tumours, head injury, epilepsy, multiple sclerosis and dementias have considerable personal, social and economic costs for the sufferers and their carers. While magnetic resonance imaging (MRI) has revolutionised the management of many brain conditions in the last 40 years, there is a need for better tools for quantifying the brain's supply of energy in terms of blood flow and vascular function and it use of energy in terms of metabolic function. For example, in the case of the most common forms of brain tumour, glioma, we lack detailed information about the heterogeneity of tissue function that could help guide better treatments such as more targeted and individualised combined radiotherapy and drug programmes. Understanding more about the tumour microenvironment will also promote the development of more effective treatments. For high-grade gliomas, particularly glioblastoma, the prognosis remains poor, highlighting an urgent clinical need.Recently, we at Cardiff University Brain Research Imaging Centre (CUBRIC), and others, have developed MRI-based tools (termed dual calibrated fMRI) to map across the human brain, with a spatial resolution of a few millimetres, the amount of oxygen that the brain is consuming (known as CMRO2) along with measures of the efficiency of blood supply. CMRO2 reflects neural activity and can be altered with disease such as tumour where there is cell proliferation and energy metabolism is changed. Knowing also the functional properties of brain blood vessels and the oxygen status of brain tissue is important for understanding whether blood supply is sufficient or the vasculature is abnormal as is often seen in tumours where vessels proliferate. Our newly developed methods have shown promise in revealing abnormalities of brain tissue energy consumption in multiple sclerosis and epilepsy. In epilepsy they may offer an alternative to the use of radiation-based PET scans in the evaluation of patients for brain surgery by identifying areas in the brain with abnormally low metabolism.However, to produce a wider clinical impact it is necessary to advance the MRI and data analysis further, such that they could then be taken forward for commercial development and routine clinical use, initially within clinical trials. Two-thirds of the proposed project will address engineering and physical science challenges to (i) speed up data acquisition to about 10 mins, a clinically feasible time, by optimising the MRI data acquisition and analysis, (ii) widen the range of tissue pathology that we can reliably measure through collection of additional MRI information and detailed biophysical modelling of tissue properties and (iii) implement efficient artificial intelligence (neural network) based data analysis that can rapidly feed the images to the clinician at the MRI scanner. The remaining one-third of the project will demonstrate the feasibility of the method and its value in application to brain tumour (glioma). We aim to show that we can map the heterogeneity of tumour tissue that can reveal the type of tumour, where it is actively growing, where it is and is not responding to treatment and where radiotherapy may be damaging healthy tissue, all helping to guide treatment decisions for maximum efficacy.Central to the success of our proposal are our partnerships with industry and the NHS. Siemens will contribute the expertise of its onsite scientist at CUBRIC for the development of the MRI technology. The Velindre Cancer Centre, South Wales' principal centre for oncology, will partner on the clinical pilot studies and help to evaluate imaging for future patient benefit. Our partners will help us to bring the methods to the point within this project, if successful, of commercial development for healthcare benefit and larger scale clinical trials to demonstrate how the methods may be used in clinical practice for diagnosis, treatment planning and monitoring.