Addressing biological barriers in in vivo human brain MRI acquisitions

解决人脑 MRI 采集中的生物障碍

• 批准号: 10224852
• 负责人: Lawrence L Wald
• 金额: $ 25.68万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10224852
• 关键词: Address; Anatomy; Architecture; Arteriogram; Biological; Biological Factors; Biology; Biomedical Engineering; Blood Vessels; Brain; Brain imaging; Breathing; Data; Development; Disease; Electrodes; Engineering; Face; Facial nerve structure; Functional Magnetic Resonance Imaging; Generations; Goals; Head; Health; Human; Image; Individual; Joints; Knowledge; Learning; Magnetic Resonance Imaging; Maps; Measures; Methods; Modeling; Modernization; Morphologic artifacts; Motion; Nerve; Noise; Nose; Ocular dominance columns; Patients; Pattern; Performance; Peripheral Nerve Stimulation; Physiologic pulse; Physiological; Play; Potassium Channel; Protons; Recording of previous events; Refractory; Resolution; Respiration; Retina; Series; Sodium Channel; Surface; T2 weighted imaging; Technology; Testing; Time; Training; anatomic imaging; area striata; base; convolutional neural network; data space; density; design; human imaging; image reconstruction; improved; in vivo; magnetic field; neurovascular; novel strategies; programs; reconstruction; respiratory; retinotopic; spatiotemporal; success; tool

TRD3 Addressing biological barriers in in vivo human brain MRI acquisitions Abstract In this project, we propose a program of bioengineering development to improve human functional and anatomical MRI at its acquisition stage. We aim to bridge the macro and micro scales of brain architecture by improving the spatio-temporal resolution of fMRI down to its biological limits. The barriers we face in acquisition encoding and then again in the ability of MRI to perform anatomical imaging at the meso scale (500 um or less) and finally the spatial fidelity of fMRI maps themselves are primarily biological. Firstly, we impact MRI encoding broadly by focusing on methods to address the Peripheral Nerve Stimulation (PNS) barrier in application of fast gradient coils. We will improve gradient coil technology through utilizing a detailed peripheral nerve stimulation model to predict nerve stimulation and optimize reduction strategies. In Aim 2 we address the confounds of respiratory and patient motion in anatomical imaging through motion robust image reconstruction of anatomical MR images using a data-consistency driven approach. We jointly estimate biological nuisance modulations from respiration and patient motion within the multi-channel kspace data. Successful joint estimate of the image and the nuisance variables within a comprehensive forward model effectively removes these confounds from the image yielding a motion and respiratory robust acquisition. Finally, in aim 3 we develop methods to address spatial resolution limits imposed on fMRI by large vasculature by predicting and removing them from the activation maps on the flattened cortical surface by models incorporating prior knowledge from high resolution vascular maps. Overall, our tools will broadly advance the study of human brain circuits at the mesoscopic scale while retaining the whole- brain and non-invasive features of MRI.

TRD3 解决体内人脑 MRI 采集中的生物障碍 抽象的 在这个项目中，我们提出了一个生物工程开发计划，以改善人类 处于采集阶段的功能和解剖 MRI。我们的目标是架起宏观和微观的桥梁 通过将功能磁共振成像的时空分辨率提高到其 生物学极限。我们在采集编码以及 MRI 能力方面面临的障碍 以细观尺度（500 微米或更小）执行解剖成像，最终实现空间保真度 功能磁共振成像图本身主要是生物学的。首先，我们通过以下方式广泛影响 MRI 编码： 重点关注解决周围神经刺激（PNS）应用障碍的方法 快速梯度线圈。我们将通过利用详细的外围设备来改进梯度线圈技术 神经刺激模型来预测神经刺激并优化减少策略。目标 2 我们通过以下方式解决解剖成像中呼吸和患者运动的混淆问题 使用数据一致性驱动的解剖 MR 图像的运动稳健图像重建 方法。我们共同估计呼吸和患者的生物干扰调节 多通道 kspace 数据内的运动。图像和图像的成功联合估计 综合前向模型中的干扰变量有效地消除了这些混淆 从图像中产生运动和呼吸鲁棒采集。最后，在目标 3 中，我们开发 通过预测解决大脉管系统对 fMRI 空间分辨率限制的方法 并通过模型将它们从扁平皮质表面的激活图中移除 结合高分辨率血管图的先验知识。总体而言，我们的工具将广泛 在介观尺度上推进人类大脑回路的研究，同时保留整体 MRI 的大脑和非侵入性特征。