TR&D Project 2: Virtual Scanners

基本信息

批准号：
10372910
负责人：
Ehsan Samei
金额：
$ 29.42万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10372910
关键词：
3-Dimensional Algorithms Anatomy Artificial Intelligence Biological Models Cardiac Clinical Code Communities Computed Tomography Scanners Computer software Computing Methodologies Data Data Set Dose Evaluation Generations Geometry Goals Image Imaging technology Knowledge Manufacturer Name Medical Imaging Methods Modeling Monte Carlo Method Motion Patients Performance Perfusion Phase Process Protocols documentation Radiation Dose Unit Radiation Scattering Reader Research Roentgen Rays Scheme Signal Transduction Specific qualifier value Specificity Speed System Technology Training Tube Validation Variant Work X-Ray Computed Tomography base clinical imaging design detector flexibility high resolution imaging human subject imaging modality in silico multiple datasets new technology photon-counting detector programs prototype radiation absorbed dose radiomics reconstruction respiratory simulation system architecture tool usability user-friendly virtual virtual imaging virtual patient virtual platform

项目摘要

ABSTRACT – TRD2: Virtual Scanners Virtual Imaging Trials (VITs) offer a powerful alternative to conducting studies of computed tomography (CT) technologies with human subjects. With the trial taking place in silico, virtual trials require a fast and realistic CT simulator. However, current CT simulators are inadequate to meet this need due to limited representation of the actual CT acquisition processes and slow speed. Simulators using Monte Carlo methods are optimal in accurately modeling the image acquisition process but too slow for simulating high resolution images. Alternative ray-tracing methods are faster but unable to provide realistic estimates of absorbed radiation dose, a factor of high importance in CT imaging. Most simulators are further limited in their ability to model specific CT makes and models, which would be essential to represent an actual clinical CT imaging scenario. This project develops and provides a new CT simulation platform to meet the desired throughput and realism of virtual imaging trials. The platform combines the benefits of high spatio/temporal details (provided by ray- tracing), precise radiation dose and scatter estimates (provided by Monte Carlo), speed (provided by GPU computing and proficient programing), and specificity (modeling CT subcomponents based on precise system specifications from CT manufacturers). Already prototyped for one CT scanner, this project will expand the prototype into a comprehensive CT simulator platform for multiple CT systems. The Specific Aims of the project are (1) to model CT acquisition subcomponents in detail; (2) to model CT acquisition schemes for estimating primary signal, scatter, and radiation dose; (3) to implement processes for integration, image formation, and validation; and (4) to build a modular interface to enable effective use of the simulator. The simulation will include manufacturer-specific, user-defined, and generic (i.e., manufacturer- neutral) CT systems and reconstruction algorithms, detector geometry and models (including photon-counting detectors), full user-control over acquisition specifications (i.e., virtual patient input from TRD1, CT scanner, protocol, kV, mA, recon, etc.), and a user-friendly modular interface with both GUI and script-based utility. This work will provide a first-of-its-kind rapid and accurate CT simulator with scanner-specific, user- customizable, and generic 3D and 4D modeling capabilities, which can simulate both reconstructed images and absorbed radiation dose. Users will be able to utilize the simulator to study a variety of CT technologies and applications, such as those pertaining to radiation dose optimization, image quality assessment, and image deformation from cardiac and respiratory motion. The simulator would enable task-based design and evaluation of new CT systems and artificial intelligence (AI)-based training through generating large-scale realistic image datasets that replicate the realism of clinical images with the added advantage of known ground truth. The CT simulation platform, combined with the suite of virtual patients (TRD1) and virtual readers (TRD3) offered by the Center, form the essential toolset to enable virtual imaging trials in CT.

摘要 – TRD2：虚拟扫描仪虚拟成像试验 (VIT) 为计算机断层扫描 (CT) 研究提供了强大的替代方案由于试验是在计算机中进行的，虚拟试验需要快速且现实的方法。然而，由于代表性有限，当前的 CT 模拟器不足以满足这一需求。实际 CT 采集过程的复杂性和使用蒙特卡罗方法的低速模拟器是最佳的。准确地模拟图像采集过程，但对于模拟高分辨率图像来说速度太慢。替代射线追踪方法速度更快，但无法提供吸收辐射剂量的实际估计，这是 CT 成像中非常重要的一个因素，大多数模拟器的特定建模能力都受到进一步限制。 CT 品牌和型号，这对于代表实际的临床 CT 成像场景至关重要。该项目开发并提供了一个新的 CT 模拟平台，以满足所需的吞吐量和真实感该平台结合了高空间/时间细节（由射线提供）的优点。追踪）、精确的辐射剂量和散射估计（由蒙特卡罗提供）、速度（由 GPU 提供）计算和熟练的编程）和特异性（基于精确系统的 CT 子组件建模） CT 制造商的规格）已经为一台 CT 扫描仪制作了原型，该项目将扩展将原型开发为适用于多个 CT 系统的综合 CT 模拟器平台。该项目的具体目标是 (1) 对 CT 采集子组件进行详细建模；(2) 对 CT 进行建模；用于估计主要信号、散射和辐射剂量的采集方案；(3) 实施以下过程：集成、图像形成和验证；(4) 构建模块化接口以实现有效利用仿真将包括制造商特定的、用户定义的和通用的（即制造商- 中性）CT 系统和重建算法、探测器几何结构和模型（包括光子计数探测器），用户完全控制采集规范（即来自 TRD1、CT 扫描仪的虚拟患者输入，协议、kV、mA、recon 等），以及用户友好的模块化界面，具有 GUI 和基于脚本的实用程序。这项工作将提供首个快速、准确的 CT 模拟器，具有扫描仪特定的、用户可使用的功能。可定制的通用 3D 和 4D 建模功能，可以模拟重建图像用户将能够利用模拟器来研究各种 CT 技术。和应用，例如与辐射剂量优化、图像质量评估相关的应用心脏和呼吸运动引起的图像变形将能够实现基于任务的设计和通过生成大规模数据来评估新的 CT 系统和基于人工智能 (AI) 的训练真实的图像数据集，可复制临床图像的真实性，并具有已知地面的附加优势 CT 模拟平台与虚拟患者 (TRD1) 和虚拟读者 (TRD3) 套件相结合。该中心提供的工具集构成了实现 CT 虚拟成像试验的基本工具集。