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Reliable Human-Model Observers for Emission Tomography

可靠的人体模型发射断层扫描观察者

基本信息

批准号：
8541012
负责人：
Howard Carl Gifford
金额：
$ 36.18万
依托单位：
UNIVERSITY OF HOUSTON
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-09-01 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8541012
关键词：
Agreement Algorithms Attention Characteristics Clinical Collimator Computer Assisted Data Deoxyglucose Dependence Detection Development Diagnostic Disease Management Early Diagnosis Early identification Emission-Computed Tomography Ensure Evaluation Eye Fluorine Functional Imaging Goals Grant Human Hybrids Image Indium-111 Investigation Laboratories Lead Location Machine Learning Malignant Neoplasms Measures Methodology Methods Metric Modality Modeling Morphology Neuroendocrine Tumors Pattern Performance Photons Positron-Emission Tomography Process Research Role Scanning Slice Stress System Systems Development Technology Testing Time Training Work base cancer diagnosis cancer type design digital image processing imaging modality improved interest mathematical model new technology novel public health relevance radiologist simulation single photon emission computed tomography tomography tool tumor visual search

项目摘要

DESCRIPTION (provided by applicant): Our overall objective is to develop numerical observers for dependable technology evaluations in emission tomography. Positron emission tomography (PET) and single-photon emission tomography (SPECT) are the primary clinical modalities for imaging many types of cancer. However, early de- tection often presents the best chances of surviving cancer whereas these imaging modalities have limited diagnostic utility for small tumors. Systematic task-based developmental assessments could facilitate early identification of promising new technology for improving the diagnostic capabilities of these modalities. Yet, assessments with human observers are generally impractical for developmental use. Moreover, available mathematical models (or numerical observers) intended to predict human performance-what we refer to as human-model observers-present significant limits, including con- straints on the types of diagnostic tasks that can be considered. Partly because of these constraints, existing human-model observers frequently require revalidation given any change to the imaging pro- cess. Our approach to observer development is founded on the concept of task equivalence, whereby the task for the numerical observer mirrors the desired clinical task as closely as possible. In this grant, we propose a novel observer framework that is influenced by descriptions of radiologists' visual-search (VS) processes, in which an initial global scan of an image identifies candidate locations deserving closer inspection. We shall use the VS paradigm to investigate the hypotheses that task equivalence i) can lead to a human-observer model that reliably generalizes to a wide range of diagnostic tasks, and ii) is necessary to ensure truly relevant task-based evaluations. We shall test these hypotheses through observer studies with fluorine-18 deoxyglucose (FDG) whole-body PET and SPECT In-111 imaging of neuroendocrine tumors (NETs). A state-of-the-art model observer for developmental stud- ies should be capable of detection-localization tasks, and our observer studies will be analyzed with jackknife FROC (JAFROC) methodology. The specific aims of this work are to: 1) determine what features of FDG-PET image slices attract initial human-observer attention; 2) develop a VS numerical observer for tumor detection-localization tasks in FDG-PET; 3) test the VS observer against humans in a JAFROC detection-localization study featuring hybrid PET images; 4) investigate generalizations of the VS observer to SPECT and 3D detection-localization tasks; and 5) compare system optimiza- tions for oncologic SPECT obtained from the VS and existing numerical observers. The application is optimization of a parallel-hole collimator design for In-111 NET imaging. PUBLIC HEALTH RELEVANCE: Functional imaging with positron emission tomography (PET) and single-photon emission tomog- raphy (SPECT) has a significant role in cancer diagnosis and management. Still, early detection offers the best chances for surviving many cancers and refining the diagnostic capabilities of these modali- ties for small tumors continues to be a major research focus. This work is focused on the development of assessment methods for assisting in the early identification of technological advances that could improve the diagnostic utility of PET and SPECT.

描述（由申请人提供）：我们的总体目标是开发数字观测器，用于发射断层扫描中的可靠技术评估。正电子发射断层扫描（PET）和单光子发射断层扫描（SPECT）是成像许多类型的癌症的主要临床模式。然而，早期检测通常是癌症存活的最佳机会，而这些成像方式对小肿瘤的诊断效用有限。系统的基于任务的发展评估可以促进早期识别有前途的新技术，以提高这些模式的诊断能力。然而，与人类观察员的评估通常是不切实际的发展用途。此外，现有的数学模型（或数值观测器）旨在预测人类的表现，我们称之为人类模型的替代品，目前显着的限制，包括约束类型的诊断任务，可以考虑。部分由于这些限制，现有的人体模型观察者经常需要重新验证给定的成像过程的任何变化。我们的观察员发展的方法是建立在任务等效的概念，即任务的数值观察员反映所需的临床任务尽可能密切。在这项授权中，我们提出了一种新的观察员框架，该框架受到放射科医生的视觉搜索（VS）过程的描述的影响，在该过程中，图像的初始全局扫描识别值得更仔细检查的候选位置。我们将使用VS范式来研究以下假设：任务等效性i）可以导致可靠地推广到广泛的诊断任务的人类观察者模型，ii）对于确保真正相关的基于任务的评估是必要的。我们将通过对神经内分泌肿瘤（NETs）进行氟-18脱氧葡萄糖（FDG）全身PET和SPECT In-111成像的观察者研究来验证这些假设。一个国家的最先进的模型观察员的发展研究应该能够检测定位任务，我们的观察员研究将分析与刀切FROC（JAFROC）方法。这项工作的具体目标是：1）确定FDG-PET图像切片的哪些特征吸引了最初的人类观察者的注意; 2）开发用于FDG-PET中肿瘤检测-定位任务的VS数值观察者; 3）在具有混合PET图像的JAFROC检测-定位研究中针对人类测试VS观察者; 4）研究VS观察者对SPECT和3D检测-定位任务的推广;和5）比较从VS和现有数值观测器获得的肿瘤SPECT的系统优化。该应用程序是优化的平行孔准直器的设计，在-111 NET成像。公共卫生相关性：正电子发射断层扫描（PET）和单光子发射断层扫描（SPECT）的功能成像在癌症诊断和治疗中具有重要作用。尽管如此，早期检测为许多癌症的生存提供了最好的机会，并且改进这些模式对小肿瘤的诊断能力仍然是主要的研究焦点。这项工作的重点是开发评估方法，以帮助早期识别技术进步，可以提高PET和SPECT的诊断效用。