Satisfaction of Search in Breast Cancer Detection

乳腺癌检测搜索满意度

• 批准号: 10368982
• 负责人: Andrew R Hollingworth
• 金额: $ 60.39万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-15 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10368982
• 关键词: Benign; Breast Cancer Detection; Caliber; Cause of Death; Chest; Cognitive; Collaborations; Collection; Data; Databases; Detection; Development; Diagnosis; Diagnostic; Digital Breast Tomosynthesis; Digital Mammography; Dimensions; Disease; Eye; Film; Foundations; Future; Goals; High Prevalence; Human; Image; Impairment; Incidence; Institution; Investigation; Knowledge; Lead; Lesion; Location; Malignant - descriptor; Malignant Neoplasms; Mammography; Measures; Medical Imaging; Memory; Methods; Modality; Participant; Positioning Attribute; Prevalence; Probability; Pupil; ROC Curve; Radiology Specialty; Reader; Reading; Reporting; Research; Research Personnel; Resources; Screening for cancer; Signal Detection Analysis; Source; Stimulus; Structure; Techniques; Technology; Thoracic Radiography; Three-Dimensional Image; Training; Training Programs; Triplet Multiple Birth; Visual; Woman; Work; X-Ray Computed Tomography; X-Ray Tomography; base; breast cancer diagnosis; breast density; breast imaging; cancer type; case control; cognitive capacity; expectation; experimental study; imaging modality; improved; interest; malignant breast neoplasm; novel; premature; programs; radiologist; response; satisfaction; screening; standard of care; visual search; visual tracking

PROJECT SUMMARY/ABSTRACT Breast cancer has the highest incidence of cancer for women in the U.S. and across the world. Despite advances in technology—from film-screen images to Full Field Digital Mammography (FFDM) and now to Digital Breast Tomosynthesis (DBT)—the yearly miss rate has remained stubbornly stable, ranging between 10-30% at screening. Technology alone is not reducing errors of omission; we need to understand the specific challenges faced by the human readers interpreting the images, and the specific errors that they lead to. Satisfaction of Search (SOS) refers to the fact that, after having detected a first lesion in a case, the miss rate for additional lesions in the same case is substantially elevated. This specific type of error has been shown to account for 30% of misses in the domains of Radiology where it has been studied, including chest radiography and Computed Tomography. And yet, it has never been studied in the domain of breast cancer. Thus, there is a critical need to determine how SOS contributes to errors in breast cancer screening. In the present project we will determine the rates of occurrence and the underlying causes of SOS in FFDM and DBT. We have devised a novel method that overcomes limitations of previous methods and that is optimized for use in FFDM and DBT. Previous approaches to studying SOS involved the photographic addition of artificial lesions to images, which is not feasible for breast imaging. Instead, we will construct a database of naturally occurring cases that is structured for studying SOS. This will involve the collection of multiple-lesion cases and controlled single-lesions cases, where the former are matched with the latter on key diagnostic dimensions, such as lesion type, lesion size, and breast density. In two main experiments (one with FFDM and one with DBT), radiologists will read cases from the experimental set, marking the locations and diagnoses for benign and malignant lesions. Signal-detection analyses over dual- and single-lesion cases will be used to estimate the rate of SOS. Eye position and pupil diameter will be tracked as participants read each case. These data will allow us to assess the prevalence of different known causes of SOS: (a) premature termination, in which search following first lesion detection is less comprehensive compared with single-lesion control cases; (b) perceptual set, in which, after having detected a first lesion, participants are biased to find subsequent lesions with similar perceptual features, leading to reduced sensitivity in the detection of perceptually dissimilar targets; and (c) resource depletion, in which the demands of maintaining information about a first-detected lesion in memory reduce available perceptual/cognitive resources, thereby reducing the efficiency of subsequent search. Understanding the rates and underlying causes of SOS in breast cancer detection will lay the foundation for planned future work to develop training programs and best practices that mitigate the specific causes of SOS errors and thereby reduce miss rates in breast cancer screening.

项目概要/摘要 乳腺癌是美国乃至全世界女性癌症发病率最高的癌症。 技术进步——从胶片屏幕图像到全场数字乳腺X线摄影（FFDM），现在到 数字乳腺断层合成 (DBT)——每年的漏诊率一直保持稳定，介于 筛选时仅靠技术并不能减少10-30%；我们需要了解具体情况。 人类读者在解读图像时面临的挑战，以及它们导致的具体错误。 搜索满意度（SOS）是指在检测到病例中的第一个病变后， 同一病例中其他病变的漏诊率大大提高。 研究显示，在放射学领域（包括胸部）中，有 30% 的失误是由该因素造成的 然而，它从未在乳腺癌领域进行过研究。 因此，迫切需要确定 SOS 如何导致乳腺癌筛查错误。 在本项目中，我们将确定 SOS 的发生率和根本原因 我们设计了一种克服以前方法局限性的新方法。 针对 FFDM 和 DBT 的使用进行了优化，之前研究 SOS 的方法涉及摄影加法。 将人工病变转化为图像，这对于乳腺成像来说是不可能的，相反，我们将构建一个数据库。 为研究 SOS 而构建的自然发生的病例，这将涉及收集多个病变。 病例和对照单病灶病例，前者与后者在关键诊断上相匹配 尺寸，例如病变类型、病变大小和乳房密度 在两个主要实验中（一个使用 FFDM 和一个使用 FFDM）。 一个带有 DBT 的），放射科医生将从实验集中读取病例，标记位置和诊断 良性和恶性病变的信号检测分析将用于双病变和单病变病例。 当参与者阅读每个案例时，将跟踪估计 SOS 的发生率。 这些数据将使我们能够评估 SOS 的不同已知原因的患病率：(a) 早产 终止，其中第一个病变检测后的搜索与单个病变相比不太全面 控制案例；（b）感知组，其中，在检测到第一个病变后，参与者倾向于发现 随后的病变具有相似的感知特征，导致检测灵敏度降低 感知上不同的目标；以及（c）资源枯竭，其中维护信息的需求 关于内存中首次检测到的病变会减少可用的感知/认知资源，从而减少 了解乳腺癌中 SOS 的发生率和根本原因。 检测将为计划的未来工作奠定基础，以制定培训计划和最佳实践， 减少 SOS 错误的具体原因，从而降低乳腺癌筛查的漏诊率。