Minimizing Uncertainty in Breast Ultrasound Imaging with Real-Time Coherence-Based Beamforming

通过基于实时相干的波束形成最大限度地减少乳房超声成像的不确定性

• 批准号: 10417922
• 负责人: Muyinatu A. Lediju Bell
• 金额: $ 35.2万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10417922
• 关键词: Accounting; Acoustics; Anxiety; Benign; Biopsy; Biostatistics Core; Breast; Breast Cancer Detection; Cancer Patient; Clinic; Clinical; Clinical Pathways; Collaborations; Complex; Cyst; Data; Developing Countries; Development; Diagnosis; Diagnostic; Disease; Early Diagnosis; Environment; Equipment; Faculty; Goals; Healthcare; Healthcare Systems; Hospitals; Human body; Image; Imaging Techniques; Imaging technology; In Situ; Investigation; Length; Letters; Liquid substance; Liver; Malignant - descriptor; Malignant Neoplasms; Malignant neoplasm of liver; Malignant neoplasm of pancreas; Malignant neoplasm of testis; Mammary Ultrasonography; Mammography; Mass in breast; Methods; Morbidity - disease rate; Organ; Pancreas; Pathology; Pathway interactions; Patients; Performance; Procedures; Publishing; Reader; Real-Time Systems; Recording of previous events; Research; Research Personnel; Resource Allocation; Resources; Series; Solid; Speed; Techniques; Technology; Testing; Time; Ultrasonography; Uncertainty; United States; Universities; Wait Time; Woman; Work; base; breast malignancies; cancer diagnosis; clinical care; deep learning; deep neural network; experience; follow-up; imaging modality; imaging scientist; improved; innovation; malignant breast neoplasm; men; mortality; neural network architecture; novel; novel strategies; photoacoustic imaging; radiologist; rural area; screening; success; tool; ultrasound

Project Summary Approximately 280,000 women are expected to be diagnosed with breast cancer in the United States in 2021 and more than 40,000 will die from the disease. It is well documented that early detection results in improved morbidity and mortality. Ultrasound imaging is an important screening and diagnostic breast cancer detection tool, particularly for women with dense breasts when mammography tends to be suboptimal. While suspicious findings may be clarified with ultrasound imaging, a subset of ultrasound images yield inconclusive results, ne- cessitating biopsies or follow-up imaging, which increase patient anxiety and places additional burdens on the time available for clinical care and the resource allocations of our healthcare system. One reason for this out- standing challenge is that dense breasts tend to create images with significant acoustic clutter, which confounds the differentiation of an otherwise anechoic mass (which is indicative of a benign cyst) from a truly hypoechoic mass (which could be indicative of malignancy). In addition, it can be difficult to distinguish a complicated cyst (which has internal echoes due to proteinaceous material and is benign) from either a solid mass or a complex cystic and solid mass (which could be malignant) using standard ultrasound imaging methods alone. The objective of this proposal is to develop new, real-time ultrasound imaging technology that will simplify clin- ical workflows by distinguishing fluid-filled masses from solid masses and from complex cystic and solid masses, which all appear hypoechoic in traditional ultrasound B-mode images. Our novel approach, Robust Short-Lag Spatial Coherence (R-SLSC) imaging, has demonstrated feasibility to make this distinction by incorporating coherence-based beamforming to augment existing beamforming methods available in clinical ultrasound scan- ners. Aim 1 will focus on development of a real-time system for implementing matched B-mode and R-SLSC imaging. Aim 2 will evaluate and compare real-time system performance. Aim 3 will assess the ability of our novel methods to distinguish fluid from solid or complex cystic and solid masses utilizing a combination of quanti- tative analyses and task-oriented reader studies. Aim 4 will investigate advanced methods to retrieve coherence information and diagnostic information regarding mass contents from ultrasound channel data, including recently discovered options that rely on coherence lengths and lag-one coherence values without requiring reader input. Successful completion of these aims will lead to a real-time, ultrasound-based tool to confidently distinguish solid from fluid hypoechoic breast masses and provide a more simplified clinical workflow for the most challenging of these cases. In addition, results from the proposed studies will be applicable to clarifying the content of masses that may appear in multiple organs throughout the human body (e.g., testicular, liver, or pancreatic masses).

项目摘要 预计2021年美国将有约28万名女性被诊断出患有乳腺癌 超过4万人将死于这种疾病据文献记载，早期检测导致改善的 发病率和死亡率。超声成像是一种重要的乳腺癌筛查和诊断检测方法 这是一个非常有用的工具，特别是对于乳房致密的女性，当乳房X光检查往往不是最佳的时候。虽然可疑 发现可以用超声成像澄清艾德，超声图像的子集产生不确定的结果， 重复活检或随访成像，这增加了患者的焦虑，并给患者带来额外的负担。 临床护理的可用时间和我们医疗系统的资源分配。其中一个原因是- 一个长期的挑战是，致密的乳房往往会产生具有明显声学杂乱的图像，这会使人混淆。 鉴别其他无回声肿块（这是良性囊肿的指示）与真正的低回声肿块 肿块（可能是恶性肿瘤的指示）。此外，很难区分复杂的囊肿， （由于蛋白质物质而具有内部回声，并且是良性的） 囊性和实性肿块（可能是恶性的），仅使用标准超声成像方法。 该提案的目的是开发新的实时超声成像技术，以简化临床检查。 临床工作通过区分液体填充的肿块与实性肿块以及复杂的囊性和实性肿块来进行， 它们在传统的超声B模式图像中都表现为低回声。我们的新方法，鲁棒短滞后 空间相干（R-SLSC）成像已经证明了通过结合 基于相干性的波束形成，以增强临床超声扫描中可用的现有波束形成方法- 纳斯目标1的重点是开发一个实时系统，用于实现匹配的B模式和R-SLSC 显像目标2将评估和比较实时系统性能。目标3将评估我们的 本发明提供了一种新的方法，该方法利用定量和定量分析的组合来区分囊液与实体或复杂的囊实性肿块， 任务分析和任务导向的读者研究。目标4将研究检索相干性的先进方法 关于来自超声通道数据的质量内容的信息和诊断信息，包括最近 发现了依赖于相干长度和滞后一相干值而不需要读者输入的选项。 这些目标的成功完成将导致一个实时的，基于超声波的工具， 并提供了一个更简单的艾德临床工作流程， 这些案件。此外，拟议研究的结果将适用于澄清质量含量 可能出现在整个人体的多个器官中（例如，睾丸、肝脏或胰腺肿块）。