Reliable Human-Model Observers for Emission Tomography

可靠的人体模型发射断层扫描观察者

• 批准号: 7948792
• 负责人: Howard Carl Gifford
• 金额: $ 54.68万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7948792
• 关键词: Agreement; Algorithms; Arts; Attention; Characteristics; Clinical; Collimator; Computer Assisted; Computer Systems Development; 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; Technology; Testing; Time; Training; Work; base; cancer diagnosis; cancer type; design; digital; imaging modality; improved; interest; mathematical model; new technology; novel; public health relevance; radiologist; simulation; single photon emission computed tomography; tomography; tool; tumor; visual search

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)：我们的总体目标是为发射断层扫描中可靠的技术评估培养数字观察员。正电子发射断层扫描(PET)和单光子发射断层扫描(SPECT)是许多类型癌症的主要临床成像方式。然而，早期检测往往是癌症存活的最好机会，而这些成像方法对小肿瘤的诊断作用有限。系统的以任务为基础的发展评估有助于及早确定有希望的新技术，以提高这些模式的诊断能力。然而，人类观察者的评估通常不适用于发展用途。此外，旨在预测人类表现的现有数学模型(或数字观察者)--我们称为人体模型观察者--存在重大限制，包括对可考虑的诊断任务类型的限制。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，因为成像过程有任何变化。我们开发观察者的方法建立在任务等价性的概念上，即数字观察者的任务尽可能接近地反映所需的临床任务。在这项授权中，我们提出了一个受放射科医生视觉搜索(VS)过程描述影响的新的观察者框架，在该框架中，对图像的初始全局扫描确定了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：1)任务等价性可以导致可靠地概括到广泛的诊断任务的人-观察者模型，以及2)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18F脱氧葡萄糖(FDG)全身PET和SPECT in-111神经内分泌肿瘤(Net)成像的观察者研究来验证这些假设。一个最先进的发展研究模型观察者应该能够执行探测定位任务，我们的观察者研究将使用刀刃FROC(JAFROC)方法进行分析。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数值观测器；3)在以混合PET图像为特色的JAFROC检测-定位研究中测试VS观测器与人类；4)研究VS观测器对SPECT和3D检测-定位任务的推广；以及5)比较从VS和现有的数字观察者获得的肿瘤学SPECT的系统优化。该应用是In-111网络成像平行孔准直器设计的优化。 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，早期发现为许多癌症的生存提供了最好的机会，完善这些模式对小肿瘤的诊断能力仍然是一个主要的研究重点。这项工作的重点是开发评估方法，以帮助及早确定可以提高正电子发射计算机断层扫描和SPECT诊断效用的技术进步。