Development of Methods for a Simplified and Reliable Prostate Cancer MRI Exam

开发简化且可靠的前列腺癌 MRI 检查方法

• 批准号: 10412925
• 负责人: Stephan E Maier
• 金额: $ 45.76万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10412925
• 关键词: Architecture; Area; Biological Markers; Biopsy; Clinical; Complex; Consequentialism; Data; Development; Diagnosis; Diagnostic Imaging; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Economics; Enrollment; Exhibits; Fingerprint; Image; Indolent; International; Investigation; Joints; Lesion; Link; Machine Learning; Magnetic Resonance Imaging; Malignant neoplasm of prostate; Maps; Measurement; Measures; Microscopic; Monitor; Nature; Noise; Operative Surgical Procedures; Patients; Performance; Physiologic pulse; Play; Process; Prostate; Protocols documentation; Qualitative Evaluations; Quality of life; Radical Prostatectomy; Recommendation; Relaxation; Reproducibility; Research; Resolution; Risk; Role; Sampling; Scanning; Sensitivity and Specificity; Signal Transduction; Staging; System; Techniques; Testing; Time; Tissues; Training; Translating; Tweens; Variant; Weight; cancer diagnosis; contrast imaging; cost; imaging modality; improved; magnetic field; method development; neural network; novel; novel strategies; quantitative imaging; radio frequency; rectal

Abstract Non-invasive, multi-parametric characterization of prostate cancer (PC), with magnetic resonance imaging (MRI) methods, is an active area of research with great potential for providing improved diagnosis and treatment monitoring. The PI-RADSv2 assessment system that was established by an international team of experts recognizes the value of quantitative images in PC diagnosis, but relies largely on qualitative evaluation of weighted images. Although this grading approach achieves reasonably good separation be- tween normal and abnormal prostate tissue, it does not achieve adequate separation between indolent and aggressive disease, with the risk that more unnecessary and costly surgery is performed with poten- tially dire consequences on patient quality of life. High-value protocols, without need for an invasive and costly endo-rectal radio-frequency coil are being investigated. This comes at the cost of extended scan time and reduced image quality in terms of spatial resolution, signal-to-noise ratio and signal bias, which negatively impacts sensitivity and specificity of multi-parametric MRI. With the pronounced increase of multi-parametric MRI exams, there is also the desire to integrate the support by the most recent revolution in diagnostic imaging, i.e., machine learning. It becomes increasingly clear, that in order to avoid having to train neural networks for each specific system and protocol, reproducible and thus preferably quantitative imaging protocols are essential. To overcome these limitations, we propose both pulse sequence develop- ment, investigation of ADC validity and reproducibility and novel post-processing strategies. The overall objective is to demonstrate the added value of lesion characterization with quantitative values and at the same time understand and minimize the influence of protocol choices and scan hardware, hence improve overall reproducibility. Specific Aim 1 will focus on the development of a low distortion MR imaging sequence for rapid concurrent quantification of T2 and diffusion signal decay. Specific Aim 2 will examine ADC variations that result from changes in diffusion time over a range that is typical with present day clinical MR systems. Specific Aim 3 introduces advanced handling of low noise diffusion data, which will be indispensable for achieving high accuracy and precision with non-invasive and economic external coils. Specific Aim 4 introduces a novel ADC computation approach that fully captures the complex diffusion signal decays in tissues and at the same time is largely protocol and system independent. Moreover, re- sulting images and quantitative maps processed according this approach, exhibit considerably lower noise, which can be traded for higher spatial resolution or shorter scan duration. In combination, the consis- tently quantitative nature of the data and its ubiquitous validity and comparability will greatly facilitate the establishment of recommendations for disease-related thresholds. Ultimately this may permit much more reliable differentiation of aggressive from indolent disease.

摘要 使用磁共振成像对前列腺癌（PC）进行非侵入性多参数表征 (MRI)方法，是一个活跃的研究领域，具有提供改进的诊断和 治疗监测。由国际团队建立的PI-RADSv 2评估系统 的专家认识到定量图像在PC诊断中的价值，但在很大程度上依赖于定性 加权图像的评价。虽然这种分级方法实现了相当好的分离， 在正常和异常前列腺组织之间，它不能实现无痛性前列腺组织之间的充分分离。 和侵略性疾病，风险是更多的不必要的和昂贵的手术进行的潜力- 对患者生活质量造成严重后果。高价值的协议，无需侵入性和 正在研究昂贵的直肠内射频线圈。这是以扩展扫描为代价的 在空间分辨率、信噪比和信号偏置方面， 对多参数MRI的灵敏度和特异性产生负面影响。随着 多参数MRI检查，也有希望整合支持的最新革命 在诊断成像中，即，机器学习越来越明显的是，为了避免 为每个特定系统和协议训练神经网络，可重复，因此最好是定量的 成像协议是必不可少的。为了克服这些局限性，我们建议两个脉冲序列开发- 方法、ADC有效性和再现性的研究以及新的后处理策略。整体 目的是通过定量值证明病变表征的附加价值， 同时了解协议选择和扫描硬件的影响并将其最小化，从而提高 整体再现性。具体目标1将侧重于开发低失真MR成像 用于快速同时量化T2和扩散信号衰减的序列。具体目标2将审查 ADC变化是由当前典型范围内的离散时间变化引起的 临床MR系统。Speci fic Aim 3引入了先进的低噪声数据处理技术， 对于使用非侵入性和经济的外部线圈实现高精度和精密度是必不可少的。 Speci fic Aim 4引入了一种新颖的ADC计算方法，可完全捕获复杂的ADC 信号在组织中衰减，同时在很大程度上与协议和系统无关。此外，再- 根据该方法处理的结果图像和定量图，表现出相当低的噪声， 这可以换取更高的空间分辨率或更短的扫描持续时间。结合起来，consis- 数据的明确量化性质及其普遍存在的有效性和可比性将大大有助于 确定与疾病有关的阈值的建议。最终，这可能会使许多 更可靠地区分侵袭性和惰性疾病。