Shutter-Speed DCE-MRI Discrimination of Benign and Malignant Breast Disease

快门速度 DCE-MRI 乳腺良恶性疾病鉴别

• 批准号: 7313975
• 负责人: WEI HUANG
• 金额: $ 37.62万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-17 至 2008-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7313975
• 关键词: Accounting; Angiogenesis Inhibitors; Animals; Anxiety; Arteries; Benign; Biopsy; Bolus Infusion; Breast; Breast Cancer Detection; Breast Diseases; Cancer Etiology; Cessation of life; Characteristics; Clinical; Computer software; Data; Data Analyses; Dependence; Dependency; Diagnostic radiologic examination; Discrimination; Dose; Drug Kinetics; Equilibrium; Human Pathology; Image; Injection of therapeutic agent; Intervention; Lead; Lesion; Magnetic Resonance Imaging; Malignant - descriptor; Malignant Neoplasms; Mammary Ultrasonography; Measurement; Medical Care Costs; Methods; Modality; Modeling; Monitor; Needles; Neoplasms in Vascular Tissue; Numbers; Pathology; Patient Care; Patients; Pharmacotherapy; Physiologic pulse; Physiological; Population; Predictive Value; Procedures; Property; Protocols documentation; Pulse taking; Rate; Reagent; Resolution; Schedule; Sensitivity and Specificity; Signal Transduction; Site; Slice; Specificity; Speed; Standards of Weights and Measures; Statistically Significant; Techniques; Time; Tissues; Water; Weight; Woman; base; breast cancer diagnosis; breast lesion; cancer therapy; data acquisition; desire; experience; improved; malignant breast neoplasm; pharmacokinetic model; simulation; skills; tumor

DESCRIPTION (provided by applicant): The general aim of this project is to improve dynamic contrast enhanced (DCE) MRI capability for benign and malignant breast disease discrimination, using a new analytical pharmacokinetic approach - the Shutter- Speed Model (SSM). Breast cancer is the second leading cause of cancer death in women. Though MRI has higher sensitivity than mammography and ultrasound for breast cancer detection, all three imaging modalities have limited specificities. This leads to possibly unnecessary (benign) biopsies, as well as undesirable complications and patient care consequences. There are three basic approaches for analyzing DCE MRI signal time-courses: qualitative subjective assessment, empirical quantitation, and analytical modeling. The last is most desirable, since the pharmacokinetic parameters extracted should be independent of data acquisition details, contrast reagent (CR) dose and injection rate, personal skill, etc. The conventional analysis - the Standard Model (SM) - ignores equilibrium transcytolemmal water exchange effects during CR bolus passage through the lesion, which can lead to significant underestimation, and CR dose- and injection rate-dependence, of the pharmacokinetic parameters, and thus low specificity. Preliminary SSM analyses (accounting for water exchange effects) of DCE MRI data from 22 patients eliminate the CR administration dependencies, and show perfect sensitivity and specificity. The specific aims are: 1.) Evaluate the hypothesis that SSM analyses of DCE MRI data will significantly improve benign and malignant breast disease discrimination (compared to the SM approach) in a statistically significant population. 2.) Determine the SSM pharmacokinetic parameter thresholds that separate benign and malignant breast lesions with highest positive predictive value without sacrificing sensitivity. 3.) Evaluate the effects of varying temporal resolution and arterial input function determination on 1.) and 2.). T1-weighted gradient echo DCE MRI data from patients with clinically suspicious lesions will be collected during their scheduled MRI-guided preoperative needle localization or biopsy procedures, and will be analyzed with both SM and SSM. The pharmacokinetic parameters will be correlated with pathology results for statistical analyses. If successful, this SSM method may potentially be incorporated into clinical breast MRI protocols to reduce possibly unnecessary (benign) biopsies, and may be valuable in monitoring cancer treatment.

描述(由申请人提供)：该项目的总体目标是利用一种新的分析药代动力学方法--快门-速度模型(SSM)，提高动态对比增强(DCE)对乳腺良恶性疾病的鉴别能力。乳腺癌是女性癌症死亡的第二大原因。虽然MRI在检测乳腺癌方面比乳房X光照相和超声波具有更高的敏感性，但这三种成像方式的特异性都有限。这可能导致不必要的(良性)活检，以及不良的并发症和病人护理后果。分析DCE MRI信号时程的基本方法有三种：定性主观评估、经验定量和分析建模。最后一种是最理想的，因为提取的药代动力学参数应该与数据采集细节、造影剂(CR)剂量和注射速率、个人技能等无关。传统的分析-标准模型(SM)-忽略了CR团注通过病变时的平衡跨细胞膜水交换效应，这可能导致对药代动力学参数的严重低估，以及CR剂量和注射速率的依赖，从而降低特异性。对22例患者的DCE MRI数据进行SSM初步分析(考虑水交换效应)，消除了CR给药的依赖性，并显示出完美的敏感性和特异性。具体目标是：1.评估假设，即DCE MRI数据的SSM分析将显著改善在具有统计意义的人群中的乳腺良恶性疾病的辨别能力(与SM方法相比)。2.)确定SSM药代动力学参数阈值，在不牺牲敏感性的情况下，区分具有最高阳性预测值的乳腺良恶性病变。3.)评估不同的时间分辨率和动脉输入功能决定对1的影响。)和2.)。临床可疑病变患者的T1加权梯度回波DCE MRI数据将在预定的MRI引导的术前针定位或活组织检查过程中收集，并将使用SM和SSM进行分析。药代动力学参数将与病理结果相关联，以进行统计分析。如果成功，这种SSM方法可能会被纳入临床乳腺MRI方案，以减少可能不必要的(良性)活检，并可能在监测癌症治疗方面有价值。