Acquisition technology for in vivo functional and structural MR imaging at the mesoscopic scale.

介观尺度体内功能和结构 MR 成像的采集技术。

• 批准号: 10224851
• 负责人: Kawin Setsompop
• 金额: $ 25.64万
• 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/10224851
• 关键词: Acceleration; Algorithms; Animal Model; Animals; Architecture; Biological; Blood Vessels; Brain; Brain imaging; Cell Nucleus; Cells; Cerebrum; Clinical; Complement; Cortical Column; Data; Data Set; Development; Diffusion; Diffusion Magnetic Resonance Imaging; Frequencies; Functional Magnetic Resonance Imaging; Gold; Human; Image; Investigation; Joints; Machine Learning; Magnetic Resonance Imaging; Microscopic; Microscopy; Morphologic artifacts; Motion; Neurons; Optics; Performance; Peripheral Nerve Stimulation; Physiologic pulse; Play; Relaxation; Resolution; Role; SKI gene; Sampling; Scanning; Scheme; Sensitivity and Specificity; Slice; Space Models; Specificity; Speed; Structure; Surface; Techniques; Technology; Time; Variant; Veins; animal imaging; base; denoising; design; gray matter; human imaging; improved; in vivo; in vivo imaging; insight; instrumentation; machine learning algorithm; neural circuit; novel; novel strategies; performance tests; preservation; programs; reconstruction; spatiotemporal; technology development; temporal measurement; tool

Significant strides have been made in microscopic brain imaging of animal models and ex vivo samples, led by advances in optical microscopy and new tools for manipulation of neural circuitry and targeted stimulation; enabling us to gain new insights into neuronal cells and circuits functions at this fine scale. Concurrent to these developments, in vivo non-invasive human brain imaging, particularly through MRI, has also undergone significant advancement. This has allowed it to collect rich functional and structural information at the macroscale quickly, and also aid in its push towards higher spatial resolution, where imaging at the mesoscopic scale is starting to become feasible. Nonetheless, critical barriers remain in achieving adequate specificity and sensitivity at this scale. The ability to image more precisely at the mesoscale both structurally and functionally with MRI will play a critical role to bridge the gap and transfer our improved understanding at the microscale with animal and ex vivo studies to macroscale human imaging that are performed in large scale studies and in clinical settings. This project will create a program for MR technology development to overcome current “encoding limits” in MRI to achieve in vivo imaging at the mesoscopic scale: diffusion, functional, and structural imaging of the human brain at the 400–600 µm isotropic voxel size with high sensitivity and high spatial accuracy. This will push in vivo MRI from the macro-scale toward the meso-scale of cerebral cortical columns and layers and subcortical nuclei to transfer new insights from invasive animal and post mortem micro-scale imaging to non-invasive human imaging. Because fundamental modules of brain organization can be observed in the meso-scale architecture, this project will allow for in vivo investigation at relevant spatial scales with sufficient coverage. We will undertake a synergistic ‘from-the-ground-up’ development that combines novel encoding and reconstruction strategies with newly-available instrumentation to achieve high imaging fidelity and sensitivity at the target resolution. SNR-efficient volumetric and continuous acquisitions along with highly-accelerated spatio-temporal controlled-aliasing encoding will be developed. New approaches to image encoding will be created that utilize a recently-introduced combined RF and B0 shim-array technology, not only for its original intended purpose of reducing B0 inhomogeneity, but also to complement conventional encoding schemes to increase acceleration performance, improve robustness, and achieve large artifacts mitigation, particularly for multi-shot EPI. Synergistic reconstruction schemes will also be developed using emerging concepts in low-rank and multi-dimensional sub-space modeling combined with powerful Machine Learning (ML) algorithms. The proposed time-resolved reconstruction of both functional and structural data will provide a new, rich imaging dataset with hundreds of TEs and TIs from a single scan. With this approach, the detrimental image blurring from relaxation effects and distortion from B0 inhomogeneity, will also be removed to create sharp, high-fidelity datasets.

在动物模型和离体样本的显微脑成像方面取得了重大进展