Accuracy and Precision in CT Quantification of COPD Through Virtual Imaging Trials

通过虚拟成像试验对 COPD 进行 CT 定量的准确性和精确度

• 批准号: 10640999
• 负责人: Ehsan Abadi
• 金额: $ 43.76万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10640999
• 关键词: Algorithms; Anatomy; Artificial Intelligence; Biological Markers; Cause of Death; Chronic Obstructive Pulmonary Disease; Communities; Comparative Study; Complement; Complex; Computed Tomography Scanners; Computer Models; Coupled; Data; Data Set; Densitometry; Diagnosis; Diagnostic; Diagnostic Procedure; Disease; Disease model; Effectiveness; Environmental Risk Factor; Evaluation; Exposure to; Goals; Image; Interstitial Lung Diseases; Libraries; Longitudinal Studies; Lung; Lung diseases; Magnetic Resonance Imaging; Measurement; Methods; Modality; Modeling; Monitor; Patient imaging; Patients; Persons; Photons; Physiology; Positioning Attribute; Prevalence; Protocols documentation; Provider; Pulmonary Emphysema; Radiation exposure; Recording of previous events; Reporting; Reproducibility; Research; Resolution; Role; Severities; Severity of illness; Smoking; Spirometry; Symptoms; System; Technology; Time; Tube; Variant; X-Ray Computed Tomography; artificial intelligence algorithm; cohort; disease diagnosis; human model; image processing; imaging biomarker; improved; in silico; in vivo; insight; quantitative imaging; radiation absorbed dose; reconstruction; tool; verification and validation; virtual; virtual imaging; virtual patient; voltage

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of death. Increasing in prevalence, COPD is a major burden to patients and providers. Computed tomography (CT) can provide valuable information about the structural and functional abnormalities of the disease as demonstrated in numerous studies where quantitative CT is deployed to characterize and evaluate the treatment. For instance, the COPDGene study has recently shown the substantial role of quantitative CT in the redefinition of COPD diagnosis, and in evaluating the progression of emphysema over time. However, these biomarkers vary across different scanners, settings, and patient attributes. There is a crucial need to manage this variability by optimizing and harmonizing CT images for reliable biomarker quantifications across both current and emerging scanners. This goal is not possible through conventional methods of using physical phantoms or patient images. Physical phantoms are often oversimplified and not representative of the complex anatomy and physiology of COPD patients. Patient images are ground-truth-limited, i.e., the exact anatomy and physiology of the patient is not fully known. Further, patient-based comparisons require multiple acquisitions of the same subjects across different scanners and settings. This is not ethically possible since repeated imaging increases the absorbed radiation dose. These challenges can be overcome through the use of virtual imaging trials (VITs) where studies are performed in silico using computational models of patients and scanners. VITs can provide reliable and practical solution to the challenge of COPD imaging provided realistic models of patients and scanners. Such models are currently lacking in the context of COPD. We develop and then utilize realistic virtual imaging toolsets to systematically evaluate and optimize CT biomarkers in COPD patients across scanners, imaging parameters, and patient attributes. We develop the first library of realistic COPD patient models with diverse attributes and severities. Coupled with accurate models of different scanners, the phantoms will be used to generate sets of ground-truth-known virtual CT cases, to be disseminated to the research community and to be used to systematically evaluate the effects of current and emerging scanners, various patient attributes, and the effects of image processing algorithms (through a national challenge), on the accuracy and precision of COPD biomarkers. Further, we develop and optimize a truth-based artificial intelligence-based algorithm for COPD quantifications. We optimize the algorithm for accuracy and reproducibility, taking advantage of the ground-truth known simulated images . We then harmonize CT settings across different scanners to accurately and precisely assess COPD imaging biomarkers for both single time-point and longitudinal studies. The studies will be done for the top two image processing algorithms, identified in the challenge, as well as our developed algorithm. Through these efforts, the project will position CT as a more reliable method for improved characterization and monitoring of COPD.

慢性阻塞性肺疾病（COPD）是死亡的主要原因。 COPD的患病率增加 是患者和提供者的主要负担。计算机断层扫描（CT）可以提供有价值的信息 关于该疾病的结构和功能异常，如许多研究所证明的那样 部署定量CT来表征和评估治疗。例如，Copdgene研究 最近已经显示了定量CT在COPD诊断的重新定义中的重要作用，在 评估肺气肿的进展。但是，这些生物标志物在不同的不同 扫描仪，设置和患者属性。通过优化和 在当前和新兴扫描仪中都可以协调CT图像，以实现可靠的生物标志物量化。 通过使用物理幻像或患者图像的常规方法不可能进行此目标。身体的 幻影通常过于简单，不代表COPD的复杂解剖学和生理学 患者。患者图像是基于真正真实的限制的，即，患者的确切解剖学和生理学不是 完全知道。此外，基于患者的比较需要对相同受试者进行多次收购 不同的扫描仪和设置。从道德上讲这是不可能的，因为重复成像增加了吸收的 辐射剂量。可以通过使用虚拟成像试验（VIT）来克服这些挑战 使用患者和扫描仪的计算模型在计算机中进行研究。 VIT可以提供可靠的 对COPD成像挑战的实际解决方案提供了患者和扫描仪的现实模型。 此类模型目前在COPD的背景下缺乏。 我们开发然后利用现实的虚拟成像工具集来系统地评估和优化CT 跨扫描仪，成像参数和患者属性的COPD患者的生物标志物。我们开发 具有不同属性和严重性的现实COPD患者模型的第一个库。与准确的结合 不同扫描仪的模型，幻影将用于生成一组接地真实的虚拟CT 案件，将其传播到研究界，并用于系统地评估 电流和新兴扫描仪，各种患者属性以及图像处理算法的影响 （通过国家挑战），关于COPD生物标志物的准确性和精度。此外，我们发展并 优化基于真理的基于人工智能的COPD量化算法。我们优化 利用基本真相已知的模拟图像的精确性和可重复性算法 。我们 然后在不同扫描仪上协调CT设置，以准确，精确评估COPD成像 单个时间点和纵向研究的生物标志物。 研究将对前两个图像进行 在挑战中确定的处理算法以及我们开发的算法。通过这些努力， 该项目将将CT定位为改进COPD表征和监视的更可靠的方法。

项目成果

Inter- and intra-scan variability for lung imaging quantifications via CT.

通过 CT 进行肺部成像量化的扫描间和扫描内变异性。

• DOI: 10.1117/12.2613191
• 发表时间: 2022
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Shankar,SachinS;Hoffman,EricA;Atha,Jarron;Sieren,JessicaC;Samei,Ehsan;Abadi,Ehsan
• 通讯作者: Abadi,Ehsan