Rapid Motion-Robust and Easy-to-Use Dynamic Contrast-Enhanced MRI for Liver Perfusion Quantification

用于肝脏灌注定量的快速运动稳健且易于使用的动态对比增强 MRI

• 批准号: 10430267
• 负责人: Li Feng
• 金额: $ 45.25万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10430267
• 关键词: 3-Dimensional; Address; Aftercare; Biopsy; Breathing; Cancer Etiology; Clinical; Clinical Research; Consumption; Contrast Media; Development; Diagnosis; Disease; Gadolinium; Hepatic; Histologic; Image; Image Analysis; Imaging Techniques; Incidence; Kinetics; Lead; Learning; Lesion; Liver; Liver Dysfunction; Liver diseases; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Methods; Modeling; Morphologic artifacts; Motion; Operative Surgical Procedures; Pathologic; Patient-Focused Outcomes; Patients; Pattern; Performance; Perfusion; Phase; Prediction of Response to Therapy; Primary carcinoma of the liver cells; Prognosis; Radial; Recovery; Resolution; Sampling; Signal Transduction; Speed; Systemic Therapy; Techniques; Time; Translating; Treatment Efficacy; Tumor Angiogenesis; Tumor Burden; United States; Venous; Visual; analysis pipeline; base; cancer type; care costs; clinical implementation; clinical translation; contrast enhanced; curative treatments; data acquisition; deep learning; deep learning model; feasibility testing; flexibility; image reconstruction; imaging biomarker; improved; individualized medicine; ineffective therapies; insight; interest; liver imaging; mortality; motion sensitivity; novel; prevent; rapid technique; reconstruction; response; routine imaging; side effect; spatiotemporal; tool; treatment strategy; tumor; tumor microenvironment

Project Summary The broad objective of this application is to develop a rapid motion-robust and easy-to-use dynamic contrast- enhanced magnetic resonance imaging (DCE-MRI) framework for liver perfusion quantification and to evaluate its performance in quantitative assessment of hepatocellular carcinoma (HCC), the most prevalent primary malignancy in the liver. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using gadolinium-based contrast agents is currently a cornerstone for identifying and characterizing hepatic lesions, including HCC. However, the current clinical use of liver DCE-MRI is limited to visual assessment of the pattern of perfusion in 3-4 multiphasic images (arterial, venous and delayed phases), and these images are routinely acquired during multiple breath holds. DCE-MRI also has the potential for quantitative assessment of perfusion kinetics, which can provide a deeper insight into the tumor microenvironment for non-invasive characterization of different histological features of the tumor, such as tumor angiogenesis and aggressiveness. This is particularly relevant for HCC, which is typically diagnosed based on imaging without pathological confirmation from invasive biopsy. Unfortunately, conventional liver perfusion MRI techniques suffer from a number of important limitations that restrict its clinical implementation, including (1) slow imaging speed, (2) limited spatiotemporal resolution, (3) sensitivity to motion artifacts, and (4) time-consuming quantitative perfusion analysis. Meanwhile, the need for pre-contrast T1 mapping to convert MR signal to gadolinium concentration further complicates the already-cumbersome imaging workflow. These challenges and underlying complexity have all led to non-reproducible performance of liver perfusion MRI and have significantly diminished its ultimate clinical utility. In this project, we propose to develop new rapid MRI techniques combining novel motion-robust sampling strategies and advanced reconstruction models to address these challenges. The new imaging techniques will enable motion-robust 3D T1 mapping with whole-liver coverage for efficient estimation of contrast concentration and free-breathing DCE-MRI of the liver with high spatiotemporal resolution. We will also incorporate state-of-the-art methods in deep learning to further improve imaging performance, to reduce reconstruction time, and to substantially simplify perfusion quantification. These new technical developments will be integrated into a new liver perfusion MRI framework, which will be translated into the clinical setting for assessment of HCC in an exploratory clinical study. The overall hypothesis is that with the new imaging framework developed in the project, robust high spatiotemporal resolution perfusion MRI of the liver can be achieved under free breathing, and absolute quantification of liver perfusion can be performed without user- interaction. Given the rapidly rising incidence and substantial burden of HCC in the United States, successful completion of this project would enable significant progress towards improved characterization and management of HCC and other liver diseases with high clinical impact.

项目概要 该应用的主要目标是开发一种快速运动鲁棒且易于使用的动态对比度 用于肝脏灌注量化和评估的增强磁共振成像 (DCE-MRI) 框架 其在肝细胞癌 (HCC)（最常见的原发性肝癌）定量评估中的表现 肝脏恶性肿瘤。动态对比增强磁共振成像 (DCE-MRI) 使用 钆基造影剂目前是识别和表征肝脏病变的基石， 包括肝癌。然而，目前肝脏 DCE-MRI 的临床应用仅限于视觉评估模式 3-4 幅多相图像（动脉相、静脉相和延迟相）中的灌注情况，这些图像通常是 在多次屏气期间获得。 DCE-MRI 还具有定量评估灌注的潜力 动力学，可以更深入地了解肿瘤微环境，以进行非侵入性表征 肿瘤的不同组织学特征，例如肿瘤血管生成和侵袭性。这是 与 HCC 特别相关，通常根据影像学诊断而无需病理证实 来自侵入性活检。不幸的是，传统的肝脏灌注 MRI 技术存在许多问题： 限制其临床实施的重要局限性，包括（1）成像速度慢，（2）有限 时空分辨率，(3) 对运动伪影的敏感性，以及 (4) 耗时的定量灌注 分析。同时，需要预对比 T1 映射将 MR 信号转换为钆浓度 使本已繁琐的成像工作流程进一步复杂化。这些挑战和潜在的复杂性 所有这些都导致肝脏灌注 MRI 的不可重复性能，并显着降低了其性能 最终的临床实用性。在这个项目中，我们建议开发新的快速 MRI 技术，结合新颖的 运动鲁棒采样策略和先进的重建模型可以应对这些挑战。新的 成像技术将实现具有全肝脏覆盖的运动鲁棒性 3D T1 映射，以实现高效估计 具有高时空分辨率的肝脏对比剂浓度和自由呼吸 DCE-MRI。我们将 还结合深度学习中最先进的方法，进一步提高成像性能，减少 重建时间，并大大简化灌注量化。这些新技术的发展 将被整合到新的肝脏灌注 MRI 框架中，该框架将转化为临床环境 在一项探索性临床研究中评估 HCC。总体假设是，通过新的成像 该项目开发的框架，可以对肝脏进行强大的高时空分辨率灌注磁共振成像 在自由呼吸下实现，并且无需用户即可进行肝脏灌注的绝对定量 相互作用。鉴于美国 HCC 的发病率迅速上升且负担沉重，成功 该项目的完成将在改进特性描述和 管理 HCC 和其他具有高度临床影响的肝脏疾病。