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

诸如肿瘤、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护理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年中已经彻底改变了许多脑部疾病的管理，但仍需要更好的工具来量化大脑在血流和血管功能方面的能量供应以及在代谢功能方面的能量使用。例如，在最常见的脑肿瘤胶质瘤的情况下，我们缺乏有关组织功能异质性的详细信息，这些信息可以帮助指导更好的治疗，例如更具针对性和个性化的联合放疗和药物计划。更多地了解肿瘤微环境也将促进更有效治疗方法的开发。对于高级别胶质瘤，特别是胶质母细胞瘤，预后仍然很差，突出了迫切的临床需求。最近，我们在卡迪夫大学脑研究成像中心（CUBRIC）和其他人，已经开发了基于MRI的工具（称为双校准功能磁共振成像）映射整个人类大脑，空间分辨率为几毫米，大脑消耗的氧气量（称为CMRO 2）沿着血液供应效率的测量。CMRO2反映了神经活动，并且可以随着疾病而改变，例如肿瘤，其中存在细胞增殖和能量代谢改变。了解脑血管的功能特性和脑组织的氧状态对于了解血液供应是否充足或血管系统是否异常也很重要，这在血管增生的肿瘤中经常看到。我们新开发的方法在揭示多发性硬化症和癫痫的脑组织能量消耗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，它们可以为使用基于辐射的PET扫描评估患者的脑部手术提供替代方案。然而，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，以便将其用于商业开发和常规临床使用，最初是在临床试验中。拟议项目的三分之二将解决工程和物理科学挑战，以（i）通过优化MRI数据采集和分析，将数据采集加快到约10分钟，这是临床可行的时间，（ii）通过收集额外的MRI信息和组织特性的详细生物物理建模，扩大我们可以可靠测量的组织病理学范围，以及（iii）实现基于高效人工智能（神经网络）的数据分析，可以在MRI扫描仪处将图像快速馈送给临床医生。其余三分之一的项目将证明该方法的可行性及其在脑肿瘤（神经胶质瘤）应用中的价值。我们的目标是表明，我们可以绘制肿瘤组织的异质性，可以揭示肿瘤的类型，它在哪里活跃地生长，在哪里对治疗有反应，在哪里放射治疗可能会损害健康组织，所有这些都有助于指导治疗决策，以获得最大的疗效。我们的建议成功的核心是我们与行业和NHS的合作伙伴关系。西门子将贡献其在CUBRIC的现场科学家的专业知识，以开发MRI技术。南威尔士的主要肿瘤学中心Velindre癌症中心将与临床试点研究合作，并帮助评估成像对未来患者的益处。我们的合作伙伴将帮助我们将这些方法带到这个项目中，如果成功的话，商业开发的医疗保健效益和更大规模的临床试验，以证明这些方法如何在临床实践中用于诊断，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.