Multiparametric Magnetic Resonance Imaging of Pancreas Disease

胰腺疾病的多参数磁共振成像

• 批准号: 2280970
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2280970
• 关键词: Multiparametric; Magnetic; Resonance; Imaging; Pancreas

This project falls within the EPSRC Healthcare Technologies (Medical Imaging) research areaCollaboration and SupervisionThis project will be carried out in collaboration with Perspectum Diagnostics Ltd. The project will be supervised by Prof. Daniel Bulte at the University of Oxford and Prof. Sir Michael Brady and Dr. Ged Ridgway at Perspectum Diagnostics Ltd.Project DetailsMuch like chronic liver disease, chronic pancreas disease is on the rise together with the increasing prevalence of obesity and its associated conditions, such as the metabolic syndrome, cardiovascular disease and cancer. Obesity causes ectopic fat accumulation in organs such as the liver, heart or pancreas, and triggers a set of inflammatory responses that ultimately lead to fibrosis and increased risk of primary cancer. Fatty infiltration of organs such as the liver or the pancreas is initially asymptomatic and is usually reported incidentally as part of an abdominal imaging routine. Quantitative imaging becomes essential to the early detection and diagnosis of these conditions in order to monitor these subjects more closely. MRI provides safe, accurate and precise tools compared to other imaging techniques such as Computed Tomography (CT) or ultrasound.Perspectum Diagnostics Ltd have developed a set of non-contrast, quantitative MRI protocols for the assessment of liver disease. Multiparametric imaging of the liver allows for the reliable quantification of fat, iron and fibro-inflammation in parenchymal tissue; these parameters predict clinical outcomes in patients with NAFLD, hemochromatosis, steatohepatitis or autoimmune hepatitis, to name a few, as well as alcohol-related liver disease. While these MRI protocols are not readily applicable to pancreas disease, they constitute excellent first candidates. We believe this for two main reasons, (1) the fact that the pancreas shows similar disease progression to the liver when exposed to fatty infiltration -the analogous term Non-Alcoholic Fatty Pancreas Disease (NAFPD) has been coined- and (2) similar conditions have been described in the pancreas, including pancreatic steatosis, iron overload, pancreatic fibrosis, chronic pancreatitis, pancreatic cancer, pancreatic cysts or pancreatic duct obstruction. More adventurous research has attempted to establish a link between certain pancreas conditions such as NAFPD and beta-cell dysfunction and the onset of type II diabetes mellitus (T2DM), with inconclusive results. In pancreatic transplantation, steatosis is currently assessed subjectively through visual inspection upon organ retrieval and is a frequent cause of organ discard.The first year of this research project will focus on the technical MRI acquisition challenges and the validation of the Proton Density Fat Fraction (PDFF) metric for fat quantification in the pancreas. For this problem, certain modelling assumptions in liver fat assessment do not hold; also, the variable geometry and location of the pancreas make it a challenging organ to image without artefacts, compromising fat quantification. The second year of the DPhil will aim to investigate protocols for the segmentation of the pancreas in order to assess the spatial heterogeneity of pancreatic steatosis. Segmentation will help towards the assessment of pancreatic volume and surface irregularity, which have been linked to certain conditions such as T1DM and may themselves constitute useful imaging biomarkers tied with pancreas health state. The third year of the project is planned for the development of relaxometry protocols for the quantification of fibro-inflammation and its association with the risk of developing pancreatic cancer. Nearly 20,000 UK Biobank volunteer acquisitions have become available to us, each with multiple pancreas MRI protocols. We are also aiming to acquire patient data within the course of the project through research collaborations.

该项目属于EPSRC医疗技术（医学成像）研究领域，合作与监督。该项目将与Perspectum Diagnostics有限公司合作进行。该项目将由牛津大学的Daniel Bulte教授和Perspectum Diagnostics有限公司的Michael Brady教授和Ged Ridgway博士监督。项目详细信息与慢性肝病一样，慢性胰腺疾病随着肥胖及其相关疾病（如代谢综合征、心血管疾病和癌症）的日益流行而呈上升趋势。肥胖会导致肝脏、心脏或胰腺等器官的异位脂肪堆积，并引发一系列炎症反应，最终导致纤维化，增加患原发性癌症的风险。肝脏或胰腺等器官的脂肪浸润最初是无症状的，通常作为腹部影像学常规的一部分偶然报告。定量成像对于这些疾病的早期发现和诊断至关重要，以便更密切地监测这些受试者。与计算机断层扫描（CT）或超声波等其他成像技术相比，核磁共振成像提供了安全、准确和精密的工具。Perspectum诊断有限公司开发了一套非对比的定量MRI方案，用于评估肝脏疾病。肝脏的多参数成像可以可靠地量化实质组织中的脂肪、铁和纤维炎症；这些参数预测NAFLD、血色素沉着症、脂肪性肝炎或自身免疫性肝炎以及酒精相关肝病患者的临床结果。虽然这些MRI方案不容易适用于胰腺疾病，但它们是极好的首选方案。我们认为这主要有两个原因，(1)当暴露于脂肪浸润时，胰腺表现出与肝脏相似的疾病进展——类似的术语非酒精性脂肪性胰腺疾病（NAFPD）已经被创造出来——(2)在胰腺中描述了类似的疾病，包括胰腺脂肪变性、铁过载、胰腺纤维化、慢性胰腺炎、胰腺癌、胰腺囊肿或胰管阻塞。更大胆的研究试图建立某些胰腺疾病（如NAFPD和β细胞功能障碍）与II型糖尿病（T2DM）发病之间的联系，但结果尚无定论。在胰腺移植中，脂肪变性目前是通过器官取出后的目视检查来主观评估的，并且是器官丢弃的常见原因。该研究项目的第一年将重点关注技术MRI采集挑战和用于胰腺脂肪量化的质子密度脂肪分数（PDFF）度量的验证。对于这个问题，肝脏脂肪评估中的某些建模假设不成立；此外，胰腺的可变几何形状和位置使其成为一个具有挑战性的器官，无法在没有伪影的情况下成像，从而影响脂肪量化。博士学位的第二年将致力于研究胰腺分割的方案，以评估胰腺脂肪变性的空间异质性。分割将有助于评估胰腺体积和表面不规则性，这与某些疾病（如T1DM）有关，并且本身可能构成与胰腺健康状态相关的有用成像生物标志物。该项目的第三年计划开发用于量化纤维炎症及其与患胰腺癌风险的关联的松弛测量方案。我们已经获得了近20,000名英国生物银行志愿者，每个人都有多个胰腺MRI协议。我们还打算通过研究合作在项目过程中获取患者数据。

项目成果

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation

• DOI: 10.1016/j.mri.2023.01.002
• 发表时间: 2023-01-11
• 期刊: MAGNETIC RESONANCE IMAGING
• 影响因子: 2.5
• 作者: Bagur，Alexandre Triay;McClymont，Darryl;Bulte，Daniel P.
• 通讯作者: Bulte，Daniel P.

Pancreas MRI Segmentation Into Head, Body, and Tail Enables Regional Quantitative Analysis of Heterogeneous Disease.

• DOI: 10.1002/jmri.28098
• 发表时间: 2022-10
• 期刊: JOURNAL OF MAGNETIC RESONANCE IMAGING
• 影响因子: 4.4
• 作者: Triay Bagur, Alexandre;Aljabar, Paul;Ridgway, Gerard R.;Brady, Michael;Bulte, Daniel P.
• 通讯作者: Bulte, Daniel P.

Augmented mapping and analysis of pancreatic fat by quantitative MRI

通过定量 MRI 增强胰腺脂肪绘图和分析

• DOI: 10.5287/ora-nyvjrgxnn
• 发表时间: 2022
• 作者: Triay Bagur A

Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12-14, 2021, Proceedings

医学图像理解与分析 - 第 25 届年会，MIUA 2021，英国牛津，2021 年 7 月 12-14 日，会议记录

• DOI: 10.1007/978-3-030-80432-9_17
• 发表时间: 2021
• 作者: Bagur A