Fully Quantitative Low-Dose, Motion-Resolved Dynamic Contrast-Enhanced MRI in Pancreatic Adenocarcinoma

胰腺癌的全定量低剂量运动分辨动态对比增强 MRI

• 批准号: 10646508
• 负责人: Anthony G Christodoulou
• 金额: $ 58.62万
• 依托单位: CEDARS-SINAI MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-15 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10646508
• 关键词: 3-Dimensional; Abdomen; Address; Arrhythmia; Blood Plasma Volume; Blood Vessels; Breathing; Cancer Etiology; Cardiovascular Diseases; Cessation of life; Contrast Media; Development; Diagnosis; Dimensions; Disease; Dose; Early Diagnosis; Electrocardiogram; Excision; Fibrosis; Gadolinium; Heart; Histology; Image; Image Enhancement; Inflammation; Injections; Ischemia; Kinetics; Longitudinal Studies; Machine Learning; Magnetic Resonance Imaging; Malignant Neoplasms; Maps; Measurement; Modeling; Monitor; Motion; Multicenter Studies; Nature; Necrosis; Neoadjuvant Therapy; Odds Ratio; Operative Surgical Procedures; Organ; Pancreas; Pancreatic Adenocarcinoma; Pancreatic Ductal Adenocarcinoma; Parameter Estimation; Pathologic; Patients; Perfusion; Prior Therapy; Process; Property; Recovery; Reproducibility; Research Personnel; Resectable; Resected; Risk Assessment; Safety; Series; Signal Transduction; Specimen; Staging; Techniques; Technology; Three-Dimensional Imaging; Time; Tissues; Validation; cancer imaging; contrast enhanced; deep learning; design; healthy volunteer; heart imaging; heart motion; histological image; image reconstruction; improved; learning network; multitask; nervous system disorder; network models; new technology; non-invasive imaging; novel; pancreas imaging; pharmacokinetic model; prevent; quantitative imaging; reconstruction; respiratory; temporal measurement; tool; tumor; tumor microenvironment

PROJECT SUMMARY Quantitative dynamic contrast enhancement (DCE) MRI metrics such as tissue perfusion rates, kinetic parameters, extravascular volume, and plasma volume allow characterization of subtle differences in tissue states related to ischemia, vascularity, inflammation, and fibrosis in neurological and cardiovascular diseases, and in cancers such as pancreatic adenocardinoma (PDAC). The reproducible nature of quantitative imaging makes it more suitable for multi-center or longitudinal studies than conventional “qualitative” imaging. Quantitative DCE metrics have been shown to be important for risk assessment, early detection, staging, characterization, and treatment monitoring of PDAC and other diseases. DCE MRI performs imaging before, during, and after injection of a gadolinium (Gd)-based contrast agent. There are several major challenges, especially in moving organs: i) cardiac motion must be dealt with for heart scans, generally by syncing acquisition with an ECG signal, leading to difficulty in arrhythmia patients as well as low imaging efficiency and challenges for whole-heart 3D imaging; ii) respiratory motion must be dealt with, typically by patient breath-holding; iii) safety questions surrounding Gd contrast agents lower the benefit-to-risk ratio in many situations. The objective of this project is to develop low-dose, motion-resolved, quantitative dynamic contrast enhanced (DCE) MRI for PDAC. This will be accomplished by developing and validating the MR multitasking framework for multi-dynamic, highly time-resolved T1 mapping, and correlating MRI measurements to histology in patients undergoing surgical resection. Multitasking designs DCE MRI around the concept of images as functions of multiple time dimensions, each corresponding to a different dynamic process (e.g., motion, T1, DCE). It integrates machine learning, low-rank tensor modeling, compressed sensing, and deep learning to extract reproducible, quantitative measurements from 6D DCE images, even under free-breathing conditions. The resulting technology would be a powerful tool for quantitative MRI tissue characterization in moving organs, and would be promising as a tool for monitoring neoadjuvant therapies prior to pancreatic resection.

项目摘要 定量动态对比度增强（DCE）MRI指标，例如组织灌注速率，动力学 参数，血管外体积和等离子体体积允许表征组织的细微差异 与缺血，血管性，炎症和纤维化有关的状态，神经和心血管疾病， 以及诸如胰腺腺癌（PDAC）等癌症中。定量成像的可再现性质 比常规的“定性”成像更适合多中心或纵向研究。 定量DCE指标已被证明对于风险评估，早期检测，分期， PDAC和其他疾病的表征和治疗监测。 DCE MRI在注射Gadolinium（GD）基于造影剂之前，期间和之后进行成像。 有一些主要的挑战，尤其是在移动器官方面：i）心脏运动必须为心脏处理 扫描，通常通过将采集与心电图信号同步，也导致心律不齐患者的困难 作为全心3D成像的低成像效率和挑战； ii）必须处理呼吸运动， 通常是通过呼吸呼吸的； iii）围绕GD对比代理的安全性问题降低了风险福利风险 在许多情况下的比率。 该项目的目的是开发低剂量，运动分辨，定量动态对比度 PDAC增强（DCE）MRI。这将通过开发和验证MR多任务来完成 多动力，高度分辨的T1映射的框架，并将MRI测量与组织学相关 在接受手术切除的患者中。多任务设计DCE MRI围绕图像的概念作为 多个时间维 DCE）。它将机器学习，低量张量建模，压缩感应和深度学习整合到 从6D DCE图像中提取可复制的定量测量，即使在自由呼吸条件下也是如此。 最终的技术将是用于移动的定量MRI组织表征的强大工具 器官，并且有望作为在胰腺切除之前监测新辅助疗法的工具。