Transforming Clinical Brain Imaging to Protect the Neonatal Brain

转变临床脑成像以保护新生儿大脑

• 批准号: 2877280
• 金额: --
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2877280
• 关键词: Transforming; Clinical; Brain; Imaging; Protect

1) Brief description of the context of the research including potential impactThe first 2 years of life are critical for the development of the neural connections and functions responsible for normal motor and cognitive functioning in humans. Perinatal injury to the developing brain often refers to as birth asphyxia, continues to remain a significant cause of neurodevelopmental disability.We need objective, non-invasive, hospital and outpatient clinic friendly, easy to operate brain imaging tools to inform early detection of newborn brain injury; to support neurobehavioural interventions in young infants and toddlers, ultimately leading to the best possible brain development.To answer this need, this PhD will build upon technological advancements in brain imaging and computational techniques; these include (i) magnetic resonance spectroscopy (or MRS) that can quantify bioproducts of metabolism; (ii) optical imaging, with broadband near-infrared spectroscopy (or bNIRS) and diffuse correlation spectroscopy (or DCS); a non-invasive brain imaging instrument that can map cortical oxygenation, haemodynamics, blood flow and metabolic changes from birth; and (iii) machine learning approaches for classification and prediction of newborn brain injury.The ambition of this project is to innovate neuroimaging and redefine what can be investigated in the developing brain of infants at risk of neurodevelopmental disability.2) Aims and Objectives- Optimise a multimodal neuroimaging platform for neuronal functional assessment from the neonatal intensive care unit to the outpatient clinic.- Translate and enable the use of this platform to map localized cortical responses, in infants from birth up to 5 years old, correlating with a range of abnormalities including seizures and cerebral palsy.- Implement computational techniques such as machine learning methods for feature extractions and image analytics for classification of brain functional activity (oxygenation/flow and metabolism) and neurodevelopmental outcomes, towards biomarkers of brain health.3) Novelty of Research MethodologyThe project uses a novel combination of imaging modalities (bNIRS, DCS and MRS) combined with machine learning approaches to advance what can be investigated in the brains of neonates with brain injury in terms of real-time brain health as well as neurodevelopmental outcomes. The imaging platform will provide monitoring of blood flow, saturation and metabolism over extended time scales and will use portable equipment that can be brought to the neonatal's bedside rather than requiring moving of the patient (e.g. for an MRI).4) Alignment to EPSRC's strategies and research areasThis project aligns with and falls under the EPSRC's research themes of "Healthcare technologies" and "Medical imaging"5) Any companies or collaborators involvedN/A

1)研究背景的简要描述，包括潜在影响生命的前2年对于负责人类正常运动和认知功能的神经连接和功能的发展至关重要。围产期脑损伤常被称为出生窒息，一直是神经发育障碍的一个重要原因，我们需要客观、无创、医院和门诊友好、易于操作的脑成像工具来早期发现新生儿脑损伤;支持对婴幼儿进行神经行为干预，最终实现最佳的大脑发育。为了满足这一需求，该博士学位将建立在脑成像和计算技术的技术进步的基础上;这些技术包括（i）磁共振光谱（或MRS），可以量化代谢的生物产物;（ii）光学成像，宽带近红外光谱（或bNIRS）和扩散相关光谱（或DCS）;一种非侵入性的脑成像仪器，可以绘制从出生开始的皮质氧合、血液动力学、血流和代谢变化;以及（iii）新生儿脑损伤分类和预测的机器学习方法。该项目的目标是创新神经成像，并重新定义在有神经发育障碍风险的婴儿大脑发育中可以研究的内容。2）目的和目标-优化多模式神经成像平台，用于从新生儿重症监护病房到门诊的神经元功能评估。翻译并使用该平台来映射从出生到5岁的婴儿的局部皮质反应，与包括癫痫发作和脑瘫在内的一系列异常相关。实施计算技术，例如用于特征提取的机器学习方法和用于大脑功能活动分类的图像分析（氧合/流量和代谢）和神经发育结果，对大脑健康的生物标志物。3）研究方法的新奇该项目使用了一种新的成像模式组合（bNIRS，DCS和MRS）结合机器学习方法，以推进在实时脑健康和神经发育结果方面可以在脑损伤新生儿大脑中进行的研究。成像平台将提供血流监测，并将使用便携式设备，可以带到新生儿的床边，而不需要移动病人（例如MRI）。4）与EPSRC的战略和研究领域保持一致本项目与EPSRC的“医疗保健技术”和“医学成像“研究主题保持一致并属于该主题的福尔斯5）任何公司或合作者参与N/A