An Enabling Technology for Preclinical X-Ray Imaging of Biomaterials In-Vivo

体内生物材料临床前 X 射线成像的支持技术

• 批准号: 9927852
• 负责人: Mark A Anastasio
• 金额: $ 53.91万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-09 至 2022-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9927852
• 关键词: 3-Dimensional; Address; Algorithm Design; Algorithms; Animal Model; Animals; Anodes; Biocompatible Materials; Biocompatible Materials Testing; Biomaterials Research; Cell Therapy; Clinical Research; Communities; Computer Simulation; Correlation Studies; Coupled; Data; Data Set; Development; Diagnostic radiologic examination; Drug Delivery Systems; Environment; Failure; Geometry; Image; Imaging Techniques; Implant; In Situ; Liquid substance; Measures; Metals; Methods; Monitor; Natural regeneration; Nature; Penetration; Phase; Property; Radiation Dose Unit; Refractive Indices; Research; Resolution; Resource Sharing; Roentgen Rays; Solid; Source; Speed; Structure; System; Techniques; Technology; Time; Tissue Engineering; Tissues; Translating; Translations; Tube; X-Ray Computed Tomography; absorption; animal imaging; base; biomaterial development; calcification; clinical application; contrast imaging; data acquisition; design; experimental study; falls; high resolution imaging; image reconstruction; imager; imaging modality; imaging potential; imaging system; improved; in vivo; in vivo Model; in vivo imaging; innovation; melting; novel; novel therapeutics; pre-clinical; public health relevance; reconstruction; response; soft tissue; tomography; tomosynthesis

 DESCRIPTION (provided by applicant): The objective of this R01 application is to develop and evaluate a high-resolution X-ray phase- contrast (XPC) imaging system and associated image reconstruction algorithms for in-vivo volumetric imaging of biomaterials in small animal models. The need for improved imaging methods for evaluating and monitoring biomaterials for tissue engineering/regeneration, drug delivery, and cell therapies applications is great. The ideal method would provide 3D quantitative information, possess high spatial resolution (<100 µm), allow deep tissue penetration (>5 cm), and provide contrast between tissue and material structures essential for evaluating tissue response and development. Currently available imaging methods fall short in one or more of these requirements and this is currently limiting the development of biomaterial-based therapies. Moreover, these limitations hinder a variety of other preclinical imaging applications. For high-resolution applications of XPC, a microfocus X-ray tube is required in combination with a magnification geometry. Although kW power tubes equipped with source gratings are being actively explored for XPC imaging using a Talbot-Lau interferometer, that implementation does not meet the resolution requirements needed for monitoring biomaterials in small animal models and many other preclinical applications. Despite significant effort devoted in recent years to the development of XPC computed tomography (CT) using tube-based sources, the technology is still plagued by long data-acquisition times and relatively high radiation doses. Accordingly, the technology is not yet suitable for routine live animal imaging. The dominant cause of the long acquisition times in high-resolution implementations of XPC CT is the brightness limitations of conventional microfocus tubes set by the melting point of the anode target material. Another important contributing factor is that the advantages of optimized tomosynthesis data-acquisition strategies coupled with advanced statistically principled image reconstruction methods have not been fully exploited. The proposed research directly addresses the current limitations of high-resolution XPC imaging and will permit its translation for in-vivo volumetric imaging of biomaterials in small animal models. Our approach involves a high degree of innovation regarding both the hardware implementation and image reconstruction methods. The specific aims of the project are as follows. Aim 1: Develop and characterize an XPC tomosynthesis imager based on a MetalJet source for 3D monitoring of biomaterials; Aim 2: Develop advanced image reconstruction algorithms to maximize image quality; Aim 3: Refine the imaging system via computer-simulations and imaging experiments; Aim 4: Validate XPC imaging for in-vivo volumetric imaging of biomaterials in pre-clinical animal models.

 描述（由申请人提供）：本R 01申请的目的是开发和评价高分辨率X射线相衬（XPC）成像系统和相关图像重建算法，用于小动物模型中生物材料的体内体积成像。对于用于评估和监测用于组织工程/再生、药物递送和细胞治疗应用的生物材料的改进的成像方法的需求是巨大的。理想 该方法将提供3D定量信息，具有高空间分辨率（<100 µm），允许深层组织穿透（>5 cm），并提供组织和材料结构之间的对比度，这对于评估组织反应和发育至关重要。目前可用的成像方法不符合这些要求中的一个或多个，这目前限制了基于生物材料的疗法的发展。此外，这些限制阻碍了各种其他临床前成像应用。 对于XPC的高分辨率应用，需要结合放大几何结构的微焦点X射线管。虽然千瓦功率管配备源光栅正在积极探索XPC成像使用Talbot-Lau干涉仪，该实施方案不满足监测小动物模型和许多其他临床前应用中的生物材料所需的分辨率要求。尽管近年来致力于开发使用基于管的源的XPC计算机断层扫描（CT）的显著努力，但是该技术仍然受到长的数据采集时间和相对高的辐射剂量的困扰。因此，该技术还不适合常规活体动物成像。XPC CT的高分辨率实现中的长采集时间的主要原因是由阳极靶材料的熔点设定的常规微聚焦管的亮度限制。另一个重要的影响因素是，优化的断层合成数据采集策略与先进的统计学原理图像重建方法的优势尚未得到充分利用。 拟议的研究直接解决了目前高分辨率XPC成像的局限性，并将允许其翻译为小动物模型中生物材料的体内体积成像。我们的方法涉及到高度的创新，无论是硬件实现和图像重建方法。该项目的具体目标如下。 目标1：开发和表征基于MetalJet源的XPC断层合成成像仪，用于生物材料的3D监测;目标2：开发先进的图像重建算法，以最大限度地提高图像质量;目标3：通过计算机模拟和成像实验优化成像系统;目标4：将XPC成像用于临床前动物模型中生物材料的体内体积成像。

项目成果

Gold nanorods enable noninvasive longitudinal monitoring of hydrogels in vivo with photoacoustic tomography.

• DOI: 10.1016/j.actbio.2020.09.048
• 发表时间: 2020-09
• 期刊: Acta biomaterialia
• 影响因子: 9.7
• 作者: B. Shrestha;Katerina Stojkova;Richard C. Yi;M. Anastasio;J. Ye;E. Brey

Recent advances in edge illumination x-ray phase-contrast tomography.

• DOI: 10.1117/1.jmi.4.4.040901
• 发表时间: 2017-10
• 期刊: Journal of medical imaging (Bellingham, Wash.)
• 作者: Zamir A;Hagen C;Diemoz PC;Endrizzi M;Vittoria F;Chen Y;Anastasio MA;Olivo A
• 通讯作者: Olivo A

Single-shot edge illumination x-ray phase-contrast tomography enabled by joint image reconstruction.

• DOI: 10.1364/ol.42.000619
• 发表时间: 2017-02-01
• 期刊: Optics letters
• 影响因子: 3.6
• 作者: Chen Y;Guan H;Hagen CK;Olivo A;Anastasio MA
• 通讯作者: Anastasio MA

A 3D human adipose tissue model within a microfluidic device.

• DOI: 10.1039/d0lc00981d
• 发表时间: 2021-01-21
• 期刊: Lab on a chip
• 影响因子: 6.1
• 作者: Yang F;Carmona A;Stojkova K;Garcia Huitron EI;Goddi A;Bhushan A;Cohen RN;Brey EM
• 通讯作者: Brey EM