A Computational Framework Enabling Virtual Imaging Trials of 3D Quantitative Optoacoustic Tomography Breast Imaging

支持 3D 定量光声断层扫描乳腺成像虚拟成像试验的计算框架

• 批准号: 10665540
• 负责人: Mark A Anastasio
• 金额: $ 62.95万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10665540
• 关键词: 3-Dimensional; Acceleration; Acoustics; Anatomy; Blood; Breast; Breast Magnetic Resonance Imaging; Clinic; Clinical; Clinical Trials; Communities; Computer Models; Computing Methodologies; Consumption; Coupled; Data; Detection; Development; Ethics; Future; Generations; Goals; Hemoglobin; Human; Hypoxia; Image; Ionizing radiation; Knowledge; Lesion; Light; Malignant Neoplasms; Mammary Gland Parenchyma; Mammary Ultrasonography; Mammography; Measurement; Measures; Metabolic; Metabolism; Methods; Modality; Modeling; Optics; Oxygen; Pathologic; Physics; Physiological; Play; Probability; Process; Property; Research; Research Personnel; Resolution; Roentgen Rays; Role; System; Techniques; Technology; Time; Tissue imaging; Tissues; Translating; Translations; X-Ray Computed Tomography; accurate diagnosis; angiogenesis; breast cancer diagnosis; breast imaging; cancer imaging; clinical development; clinical imaging; computer framework; computerized tools; cost; cost efficient; data acquisition; density; design; diffuse optical tomography; experimental study; image reconstruction; imager; imaging modality; imaging study; in silico; interest; malignant breast neoplasm; non-invasive imaging; novel; open source; optoacoustic tomography; public health relevance; quantitative imaging; reconstruction; simulation; tool; tumor; tumor growth; tumor progression; virtual imaging

ABSTRACT Optoacoustic tomography (OAT), also known as photoacoustic computed tomography, is a non-invasive imaging modality actively being developed for breast cancer imaging and other biomedical applications. A unique feature of OAT is the ability to produce an image based on the endogenous optical contrast associated with the concentration and oxygenation state of hemoglobin within tissue, without ionizing radiation and without the loss of spatial resolution typically associated with purely optical techniques such as optical diffusion tomography. Because aggressively growing malignant breast tumors tend to be under hypoxia and decreased blood oxygen saturation due to substantially increased metabolic activity in comparison to healthy tissue, an optimized and validated OAT system can be a powerful tool for the management of breast cancer by assessing density of the tumor microvasculature and its blood oxygenation. Currently, there is no validated OAT method that is sufficiently accurate for widespread clinical imaging of the breast; important issues such as optimal hardware and image reconstruction designs, the ability to resolve lesions at depth, and quantitative imaging remain unresolved. Due to the competing requirements of light delivery and acoustic detection, a variety of different system designs for breast OAT have been proposed; this is unlike in x-ray mammography, breast MRI and breast ultrasound, where very similar implementations are in use per modality. Considering the large number of parameters involved, it is infeasible to systematically optimize breast OAT through human trials due to time- and cost-constraints and ethical concerns. However, virtual imaging trials (VITs), where an imaging study is conducted in silico by use of representative numerical phantoms and imaging models, can offer a rapid and cost-efficient means of assessing and optimizing new imaging concepts and technologies such as OAT. The ability to conduct VITs for 3D OAT is currently lacking. The broad objective of this project is to develop, validate, and demonstrate computational tools for performing VITs that can inform the development of clinically viable and effective 3D breast OAT technologies. This will afford researchers an unprecedented level of control in modeling and validating quantitative OAT imaging of the tumor and tissue oxygen saturation distributions necessary for assessing breast cancer. The results will be the first of their kind evaluating the task-based merits and capabilities of OAT and the knowledge attainable in these studies is critical for translating this technology to the clinic. The Specific Aims of the project are: Aim 1. To develop multi-physics simulation tools for the in silico simulation of realistic measurement data in 3D breast OAT; Aim 2. To systematically develop and refine quantitative OAT image reconstruction methods; Aim 3. To conduct physical experiments that will be used to validate the computational models; Aim 4. To conduct VITs to explore quantitative OAT system optimization.

抽象的 光声断层扫描（OAT），也称为光声计算机断层扫描，是一种无创的 成像模态正在积极开发用于乳腺癌成像和其他生物医学应用。一个 燕麦的独特特征是能够基于内源性对比度产生图像的能力 组织内血红蛋白的浓度和氧合状态，而无需电离辐射，没有 空间分辨率的丢失通常与纯粹的光学技术相关，例如光学扩散 断层扫描。因为积极生长的恶性乳腺肿瘤往往在缺氧下且减少 与健康组织相比，由于代谢活性大大增加而引起的血氧饱和度 优化和经过验证的燕麦系统可以通过评估来管理乳腺癌的强大工具 肿瘤微举行的密度及其血液氧合。 当前，尚无经过验证的燕麦法，足以准确地用于广泛的临床成像 乳房；重要问题，例如最佳硬件和图像重建设计，解决能力 深度的病变和定量成像仍未解决。由于光的竞争要求 递送和声学检测，已经提出了各种不同的乳腺燕麦系统设计。这 与X射线乳房X线摄影，乳房MRI和乳房超声不同，在此实现非常相似 使用每个模态。考虑到涉及的大量参数，它是系统的 由于时间和成本约束和道德问题，通过人类试验来优化乳房燕麦。然而， 虚拟成像试验（VIT），其中通过使用代表性数值在计算机中进行成像研究 幻影和成像模型可以提供快速且经济高效的方法来评估和优化新的 成像概念和技术，例如燕麦。目前缺乏为3D燕麦进行VIT的能力。 该项目的广泛目的是开发，验证和演示用于的计算工具 进行VIT，可以告知临床可行和有效的3D乳腺燕麦技术的发展。 这将为研究人员提供建模和验证定量燕麦的前所未有的控制水平 评估乳腺癌所需的肿瘤和组织氧饱和分布的成像。这 结果将是评估燕麦的基于任务的优点和能力的第一个同类产品和知识 在这些研究中可获得的研究对于将这项技术转化为诊所至关重要。 该项目的具体目的是：目标1。为In Silico开发多物理模拟工具 模拟3D乳腺燕麦中现实的测量数据；目标2。系统地发展和完善 定量燕麦图像重建方法；目标3。进行实验实验 验证计算模型；目标4。进行VIT以探索定量燕麦系统优化。