Fully Automated High-Throughput Quantitative MRI of the Liver

肝脏全自动高通量定量 MRI

• 批准号: 10605255
• 负责人: Diego Hernando
• 金额: $ 62.75万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-08 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10605255
• 关键词: Abdomen; Affect; American; Anatomy; Anemia; Artificial Intelligence; Biological Markers; Biopsy; Blood Transfusion; Breathing; Chemical Engineering; Chemicals; Child; Cirrhosis; Clinical; Cost Analysis; Data; Development; Diagnostic tests; Diffuse; Engineering; Ensure; FDA approved; Fatty Liver; Fatty acid glycerol esters; Goals; Health; Hepatic; Hepatocyte; Hereditary hemochromatosis; Image; Image Analysis; Intervention; Iron; Iron Overload; Length; Liver; Liver Failure; Liver diseases; MRI Scans; Magnetic Resonance Imaging; Manuals; Maps; Measurement; Methods; Modeling; Monitor; Morphologic artifacts; Motion; NIH Program Announcements; National Institute of Biomedical Imaging and Bioengineering; Non-Invasive Detection; Patients; Persons; Populations at Risk; Prevention; Preventive treatment; Primary carcinoma of the liver cells; Protocols documentation; Protons; Quantitative Evaluations; Reporting; Reproducibility; Research Personnel; Scanning; Schedule; Sensitivity and Specificity; Series; Source; Staging; Surveys; Testing; Time; Training; Transfusion; Translations; Triglycerides; Validation; Vendor; Work; automated analysis; chronic liver disease; clinical examination; clinical implementation; clinical translation; comorbidity; cost; density; design; diagnostic value; fatty liver disease; improved; innovation; non-alcoholic fatty liver disease; nonalcoholic steatohepatitis; novel; quantitative imaging; respiratory; tool

PROJECT SUMMARY: The overall goal of this application is to develop, implement and test a “single button push”, integrated combination of innovative MRI solutions to enable widespread and generalizable implementation of quantitative evaluation of chronic liver disease in < 5 minutes. We aim to design a reliable, efficient, low variability, and fully automated, MRI exam. This goal will be enabled by artificial intelligence (AI), reengineered chemical shift encoded (CSE)-MRI to provide “error-free” free-breathing measurement of liver fat and iron, an innovative MRI suite design, and automated analysis. In this way, we aim to achieve high-throughput, low-cost evaluation of liver disease with high accuracy, precision and reproducibility. Abnormal accumulation of triglycerides in hepatocytes, or steatosis, is the earliest feature of non-alcoholic fatty liver disease (NAFLD), affecting ~100 million people in the US. Liver iron overload is common in patients with hereditary hemochromatosis and those receiving repeated blood transfusions. Early, affordable, and accessible non-invasive detection and quantitative staging of liver fat and iron would impact the health of millions of people at risk for NAFLD and its comorbidities, as well as those with liver iron overload. Confounder-corrected CSE-MRI provides simultaneous estimation of liver proton density fat fraction (PDFF) and R2*, which are accurate, precise and reproducible biomarkers of liver fat and iron. A primary determinant of the cost of MRI is scheduled MRI suite time. Minimum slot times to accommodate the majority of patients are driven by variability in exam duration and MRI suite turnaround time. As MRI scan times are shortened, the largest contributor to exam duration is the time needed for i) manual image prescription, ii) repeated scans (rework), and iii) room turnaround time. Many patients, including children, are unable to hold their breath for the duration of CSE-MRI (~20 seconds) leading to ghosting artifacts that corrupt PDFF / R2* maps, necessitating repeated CSE-MRI acquisitions and exacerbating exam time variability. We will address these challenges by developing fully automated AI-based image prescription based on multi-center, multi-vendor data at 1.5T and 3T, in parallel with a novel “error-proof” high SNR “snapshot” CSE-MRI method that is insensitive to breathing motion. This will be performed using a novel MR “Smart Suite” design, capable of patient turnaround in less than 2 minutes, followed by automated quantitative analysis and reporting. We will implement and test a fully automated, single button push CSE-MRI exam by aiming to: 1). Develop and optimize motion insensitive, high SNR, free-breathing CSE-MRI for accurate and precise measurement of PDFF and R2*, 2). Confirm the accuracy, repeatability, and reproducibility of the proposed CSE-MRI method in patients with liver fat and iron overload, and 3). Implement and validate a fully automated CSE-MRI protocol in less than 5 minutes of MR room time. If successful, this work will provide a high-throughput, high value solution for liver fat/iron quantification. The innovations proposed in this application will also have broad applicability beyond CSE-MRI, and ultimately reduce cost and increase access, through improvements in MRI scanner utilization.

项目总结： 该应用程序的总体目标是开发、实现和测试“单键按下”、集成 结合创新的MRI解决方案，以实现广泛和普遍的量化实施 在&lt；5分钟内评估慢性肝病。我们的目标是设计一个可靠、高效、低变化性和完全 自动核磁共振检查。这一目标将通过人工智能(AI)、重新设计的化学变化来实现 编码(CSE)-核磁共振提供无误差的自由呼吸测量肝脏脂肪和铁，这是一种创新的核磁共振 套件设计和自动化分析。通过这种方式，我们的目标是实现高吞吐量、低成本的评估 具有较高的准确度、精密度和重复性。甘油三酯在人体内的异常积聚 肝细胞或脂肪变性是非酒精性脂肪性肝病(NAFLD)的最早特征，影响~100 美国有一百万人。遗传性血色素沉着症患者的肝脏铁超载是常见的 反复输血。早期、经济实惠且可获得的非侵入性检测和定量 肝脏脂肪和铁的分期将影响数百万有NAFLD及其合并症风险的人的健康， 以及那些肝脏铁超载的人。混杂校正的CSE-MRI可同时估计 肝脏质子密度脂肪分数(PDFF)和R2*是准确、精确和可重复性的肝脏生物标志物 脂肪和铁。磁共振成像成本的一个主要决定因素是预定的磁共振成像套件时间。最短时隙时间 适应大多数患者是由检查持续时间和MRI套件周转时间的变化驱动的。 随着MRI扫描时间的缩短，对检查持续时间影响最大的是i)手动成像所需的时间 处方，ii)重复扫描(返工)，以及iii)房间周转时间。许多患者，包括儿童，都是 无法屏住呼吸持续CSE-MRI(~20秒)，导致损坏的重影伪影 PDFF/R2*映射，需要重复CSE-MRI采集，并加剧检查时间变异性。我们会 通过开发基于多中心的全自动基于AI的图像处方来应对这些挑战， 1.5T和3T的多供应商数据，同时采用一种新的“防错”高信噪比“快照”CSE-MRI方法 对呼吸运动不敏感。这将使用一个新颖的MR“Smart Suite”设计，能够 在不到2分钟的时间内实现患者转机，然后进行自动定量分析和报告。我们 将实施和测试全自动、单键CSE-MRI考试，目的是：1)开发和开发 优化运动不敏感、高信噪比、自由呼吸的CSE-MRI，以准确和精确地测量PDFF 和R2*，2)。确认所建议的CSE-MRI方法在患者中的准确性、重复性和重复性 肝脏脂肪和铁超载；3)实施和验证全自动化CSE-MRI协议所需时间不到 5分钟的先生房间时间。如果成功，这项工作将为肝脏提供高通量、高价值的解决方案 脂肪/铁的量化。本申请中提出的创新也将具有广泛的适用性 CSE-MRI，并通过提高MRI扫描仪的利用率，最终降低成本并增加访问。