Observer Studies Involving Search: Modeling and Analysis

涉及搜索的观察者研究：建模和分析

• 批准号: 8426180
• 负责人: DEV P CHAKRABORTY
• 金额: $ 38.1万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8426180
• 关键词: Address; Algorithms; Anatomy; Award; Biopsy; Breast; Chest; Clinical; Clinical Data; Clinical Trials; Complex; Computer software; Data; Data Analyses; Data Correlations; Data Set; Detection; Diagnostic; Digital Mammography; Early Diagnosis; Early treatment; Equipment; Funding; Goals; Gold; Healthcare; Human; Image; International; Journals; Left; Lesion; Location; Malignant Neoplasms; Mammography; Measurement; Measures; Methodology; Methods; Modality; Modeling; Outcome; Paper; Patients; Peer Review; Performance; Planning Techniques; Prospective Studies; Publishing; Receiver Operating Characteristics; Reporting; Research; Research Personnel; Rewards; Running; Sample Size; Simulate; Specific qualifier value; System; Techniques; Testing; Validation; Woman; Work; base; case-based; clinically relevant; computer aided detection; cost effective; data acquisition; data modeling; design; image processing; malignant breast neoplasm; novel; prospective; public health relevance; radiologist; response; screening; symposium; tool; virtual

DESCRIPTION (provided by applicant): The research involves measuring imaging system performance in tasks such as detecting breast cancer. Receiver operating characteristic (ROC) methodology, the current gold-standard, uses patient-level information that a woman has suspected breast cancer. The location-specific free-response ROC (FROC) method uses additional location-level information in the radiologist's report, e.g., the cancer is in the left breast and is present at a particular location. Progress during the funded period has resulted in a novel perceptually-based FROC model and data simulator and several validated methods for analyzing data which are applicable to human observers and computer aided detection (CAD) algorithms. Papers using the PI's ideas and software are being presented in increasing numbers at conferences and in journals, and his work has generated healthy debate. The overall goal of the competing renewal project is to continue advancing the state-of-the-art in this field by addressing a number of limitations of current methods. Specific Aim 1: The figure-of-merit (FOM) is a critical determinant of statistical power and clinical relevance but all current FOMs are lesion-based and cases with more lesions contribute more to the FOM than cases with fewer lesions, and clinically less important lesions contribute equally as more important ones; we will develop novel case-based FOMs that overcome these limitations. Specific Aim 2: A realistic simulator yields confidence in methodology validation using that simulator. We will extend the current simulator by incorporating more realistic correlation effects and we will develop methodology to calibrate the simulator to real datasets thereby allowing the methodology developer to tune the simulator to specific applications. The simulator will be used to validate the different methods of analysis developed in Aim 1. Specific Aim 3: We will address several practical issues with current FROC methodology: arbitrariness of the proximity criterion, i.e., how close a mark must be to a lesion in order to credit the observer for a true detection; lack of sample-size estimation methodology for planning prospective studies; and lack of methods for analyzing clinically realistic data acquisition scenarios such as multiple views and breasts and multiple lesion types per case. Specific Aim 4: We will validate the methodology using independently acquired ROC, FROC and outcome-data in mammography. Outcome is defined as GOOD for normal cases returned to screening or abnormal cases sent to biopsy and BAD otherwise. We will test the hypothesis that FROC better correlates with outcome and yields greater statistical power than ROC. The significance is that the field is increasingly moving towards location-specific analyses, because of its intrinsic appeal and clinical realism, therefore methodology capable of analyzing the complex data, well outside the scope of the current gold-standard, is urgently needed. Patients benefit from better designed and optimized equipment leading to early diagnosis and treatment of cancers. Health care benefits because more efficient and cost-effective studies become possible which could serve as surrogates for expensive clinical trials.

描述（由申请人提供）：该研究涉及测量成像系统在检测乳腺癌等任务中的性能。接受者操作特征 (ROC) 方法是当前的黄金标准，它使用女性疑似患有乳腺癌的患者级别信息。特定位置自由响应 ROC (FROC) 方法使用放射科医生报告中的附加位置级别信息，例如，癌症位于左乳房并存在于特定位置。资助期间取得的进展产生了一种新颖的基于感知的 FROC 模型和数据模拟器，以及几种适用于人类观察者和计算机辅助检测（CAD）算法的经过验证的数据分析方法。使用 PI 的想法和软件的论文在会议和期刊上发表的数量越来越多，他的工作也引起了积极的争论。竞争性更新项目的总体目标是通过解决当前方法的许多局限性，继续推进该领域的最先进技术。具体目标 1：品质因数 (FOM) 是统计功效和临床相关性的关键决定因素，但所有当前的 FOM 都是基于病变的，病变较多的病例比病变较少的病例对 FOM 的贡献更大，临床上不太重要的病变与更重要的病变的贡献相同；我们将开发新颖的基于案例的 FOM 来克服这些限制。具体目标 2：真实的模拟器可以让人们对使用该模拟器进行方法验证产生信心。我们将通过结合更真实的相关效应来扩展当前的模拟器，并且我们将开发将模拟器校准到真实数据集的方法，从而允许方法开发人员将模拟器调整到特定的应用程序。模拟器将用于验证目标 1 中开发的不同分析方法。具体目标 3：我们将解决当前 FROC 方法的几个实际问题：邻近标准的任意性，即标记必须与病变有多近才能相信观察者的真实检测；缺乏用于规划前瞻性研究的样本量估计方法；缺乏分析临床实际数据采集场景的方法，例如多个视图和乳房以及每个病例的多种病变类型。具体目标 4：我们将使用独立获得的 ROC、FROC 和乳房 X 线摄影结果数据来验证该方法。对于返回筛查的正常病例或送去活检的异常病例，结果定义为“良好”，否则定义为“不良”。我们将测试以下假设：FROC 与结果的相关性更好，并且比 ROC 产生更大的统计功效。重要的是，由于其内在的吸引力和临床现实性，该领域越来越多地转向特定地点的分析，因此迫切需要能够分析远远超出当前黄金标准范围的复杂数据的方法。患者受益于更好设计和优化的设备，从而实现癌症的早期诊断和治疗。医疗保健受益，因为更有效和更具成本效益的研究成为可能，可以作为昂贵的临床试验的替代品。

项目成果

Dose reduction and its influence on diagnostic accuracy and radiation risk in digital mammography: an observer performance study using an anthropomorphic breast phantom.

数字乳房X线照相术中剂量减少及其对诊断准确性和辐射风险的影响：使用拟人化乳房模型的观察者表现研究。

• DOI: 10.1259/bjr/29933797
• 发表时间: 2007
• 期刊: The British journal of radiology
• 作者: Svahn,T;Hemdal,B;Ruschin,M;Chakraborty,DP;Andersson,I;Tingberg,A;Mattsson,S
• 通讯作者: Mattsson,S

Counterpoint to "Performance assessment of diagnostic systems under the FROC paradigm" by Gur and Rockette.

与 Gur 和 Rockette 的“FROC 范式下诊断系统的性能评估”相对应。

• DOI: 10.1016/j.acra.2008.12.011
• 发表时间: 2009
• 期刊: Academic radiology
• 影响因子: 4.8
• 作者: Chakraborty,DevP

On the choice of acceptance radius in free-response observer performance studies.

关于自由响应观察者性能研究中接受半径的选择。

• DOI: 10.1259/bjr/42313554
• 发表时间: 2013
• 期刊: The British journal of radiology
• 作者: Haygood,TM;Ryan,J;Brennan,PC;Li,S;Marom,EM;McEntee,MF;Itani,M;Evanoff,M;Chakraborty,D
• 通讯作者: Chakraborty,D

Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom: A crossed-modality JAFROC observer study.

• DOI: 10.1118/1.4941017
• 发表时间: 2016-03
• 期刊: Medical physics
• 影响因子: 3.8
• 作者: Thompson JD;Chakraborty DP;Szczepura K;Tootell AK;Vamvakas I;Manning DJ;Hogg P
• 通讯作者: Hogg P

An alternate method for using a visual discrimination model (VDM) to optimize soft-copy display image quality.

使用视觉辨别模型 (VDM) 优化软拷贝显示图像质量的替代方法。

• DOI: 10.1889/1.2372426
• 发表时间: 2006
• 期刊: Journal of the Society for Information Display
• 影响因子: 2.3
• 作者: Chakraborty,DevP