Motion-Resolved, Comprehensive Quantitative Tissue Characterization Using MR Multitasking

使用 MR 多任务处理进行运动解析、全面的定量组织表征

• 批准号: 10376180
• 负责人: Anthony G Christodoulou
• 金额: $ 62.86万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10376180
• 关键词: Address; Aging; Algorithms; Arrhythmia; Artificial Intelligence; Blood flow; Breathing; Cancer Patient; Cardiac; Cardiovascular Diseases; Cardiovascular system; Clinical; Collection; Consumption; Data; Development; Diagnosis; Diffuse; Diffusion; Dimensions; Disease; Early Diagnosis; Edema; Electrocardiogram; Fibrosis; Hemorrhage; Image; Iron; Joints; Lead; Lipids; Liver; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Magnetism; Malignant neoplasm of prostate; Maps; Measurement; Measures; Methods; Modeling; Monitor; Morphologic artifacts; Motion; Nature; Neurologic; Organ; Patients; Physiological; Positioning Attribute; Predisposition; Process; Property; Recovery; Reproducibility; Research; Research Personnel; Respiration; Risk Assessment; Scanning; Series; Signal Transduction; Source; Staging; System; Technology; Testing; Time; Tissue imaging; Tissues; Validation; body system; deep learning; heart motion; image reconstruction; magnetic field; magnetohydrodynamic; mathematical model; multitask; new technology; prospective; quantitative imaging; reconstruction; respiratory; time use; tissue biomarkers; tool

PROJECT SUMMARY Quantitative magnetic resonance imaging (MRI) measures tissue parameters such as T1, T2, T2*, and diffusion to detect subtle differences in tissue states (such as microstructure, diffuse fibrosis, edema, hemorrhage, and iron content) from neurological, oncological, and cardiovascular diseases. Because each parameter offers complementary tissue information, multiparameter mapping is very promising for risk assessment, early detection, accurate staging, and treatment monitoring of disease. However, quantitative MRI is typically very time consuming and difficult to perform. Each parameter is typically measured from its own series of images, so measuring multiple parameters leads to long, inefficient scanning sessions. Furthermore, cardiac and breathing motion creates misalignment between images, causing additional problems. The standard approach to motion is to either remove it (e.g., ask the patient to hold their breath) or to synchronize image acquisition with it (e.g., using electrocardiography (ECG) to monitor cardiac motion). This approach makes scan times even longer, limits imaging to patients who can repeatedly perform long breath holds (which is difficult for aging or weak patients) and who have predictable cardiac motion (which is not true of patients with cardiac arrhythmias). Furthermore, these methods are often unreliable and difficult to perform. This project is to develop and validate a new technology, MR Multitasking, to perform multiple simultaneous measurements in a single, push-button scan that is both comfortable for patients and simple for technologists to perform. MR Multitasking redesigns quantitative MRI around the concept of images as functions of many time dimensions, each corresponding to a different dynamic process (e.g., motion, T1, T2, T2*, and diffusion), and then uses mathematical models called low-rank tensors to perform fast, multidimensional imaging. This allows continuous acquisition of imaging data even while the subject is moving, providing motion-resolved parameter maps without breath holding or motion synchronization. We will scan healthy subjects, liver patients, prostate cancer patients, and cardiovascular patients to develop and validate this technology and use artificial intelligence to quickly reconstruct images from the collected data. The resulting tool will be applicable to any organ system, offering clinicians and investigators a valuable tool to answer a wide range of biomedical questions.

项目摘要 定量磁共振成像（MRI）测量组织参数，例如T1，T2，T2*和 扩散以检测组织态的细微差异（例如微结构，弥漫性纤维化，水肿， 神经，肿瘤和心血管疾病的出血和铁含量）。因为每个 参数提供互补的组织信息，多参数映射非常有前途的风险 评估，早期检测，准确分期和疾病的治疗监测。但是，定量MRI 通常非常耗时且难以执行。每个参数通常是根据自己的 一系列图像，因此测量多个参数会导致长时间，效率低下的扫描会话。此外， 心脏和呼吸运动在图像之间造成不对准，从而导致其他问题。 标准运动方法是将其删除（例如，要求患者屏住呼吸）或 与IT同步图像采集（例如，使用心电图（ECG）监测心脏运动）。这 方法可以使扫描时间更长，将成像限制给可以反复呼吸的患者 持有（对于衰老或弱患者来说很难）并且具有可预测的心脏运动（这是不正确的 心律不齐的患者）。此外，这些方法通常不可靠且难以执行。 该项目是为了开发和验证一项新技术，多任务先生，以执行多个 同时进行单个按钮扫描中的测量 要执行的技术人员。 MR多任务重新设计图像概念的定量MRI作为 许多时间维度的函数，每个功能对应于不同的动态过程（例如运动，T1，T2， T2*和扩散），然后使用称为低级张量的数学模型来快速执行， 多维成像。即使受试者移动，这也可以连续获取成像数据， 提供运动分辨的参数图，而无需呼吸或运动同步。我们将扫描 健康受试者，肝脏患者，前列腺癌患者和心血管患者发展和验证 这项技术并使用人工智能快速从收集的数据中重建图像。这 最终的工具将适用于任何器官系统，为临床医生和调查人员提供一个有价值的工具 回答各种生物医学问题。

项目成果

Multitasking dynamic contrast enhanced magnetic resonance imaging can accurately differentiate chronic pancreatitis from pancreatic ductal adenocarcinoma.

• DOI: 10.3389/fonc.2022.1007134
• 发表时间: 2022
• 期刊: FRONTIERS IN ONCOLOGY
• 影响因子: 4.7
• 作者: Wang, Nan;Gaddam, Srinivas;Xie, Yibin;Christodoulou, Anthony G.;Wu, Chaowei;Ma, Sen;Fan, Zhaoyang;Wang, Lixia;Lo, Simon;Hendifar, Andrew E.;Pandol, Stephen J.;Li, Debiao
• 通讯作者: Li, Debiao

Three-dimensional whole-brain simultaneous T1, T2, and T1ρ quantification using MR Multitasking: Method and initial clinical experience in tissue characterization of multiple sclerosis.

• DOI: 10.1002/mrm.28553
• 发表时间: 2021-04
• 期刊: Magnetic resonance in medicine
• 影响因子: 3.3
• 作者: Ma S;Wang N;Fan Z;Kaisey M;Sicotte NL;Christodoulou AG;Li D
• 通讯作者: Li D

Motion-robust quantitative multiparametric brain MRI with motion-resolved MR multitasking.

• DOI: 10.1002/mrm.28959
• 发表时间: 2022-01
• 期刊: Magnetic resonance in medicine
• 影响因子: 3.3
• 作者: Ma S;Wang N;Xie Y;Fan Z;Li D;Christodoulou AG
• 通讯作者: Christodoulou AG

Data-Consistent non-Cartesian deep subspace learning for efficient dynamic MR image reconstruction.

• DOI: 10.1109/isbi52829.2022.9761497
• 发表时间: 2022-03
• 期刊: Proceedings. IEEE International Symposium on Biomedical Imaging
• 作者: Chen, Zihao;Chen, Yuhua;Xie, Yibin;Li, Debiao;Christodoulou, Anthony G.
• 通讯作者: Christodoulou, Anthony G.

MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation.

• DOI: 10.1002/mrm.29522
• 发表时间: 2023-04
• 期刊: MAGNETIC RESONANCE IN MEDICINE
• 影响因子: 3.3
• 作者: Hu, Zhehao;Xiao, Jiayu;Mao, Xianglun;Xie, Yibin;Kwan, Alan C.;Song, Shlee S.;Fong, Michael W.;Wilcox, Alison G.;Li, Debiao;Christodoulou, Anthony G.;Fan, Zhaoyang
• 通讯作者: Fan, Zhaoyang