Robust quantitative MR imaging markers of response to therapy in Crohn’s Disease

克罗恩病治疗反应的稳健定量 MR 成像标记

• 批准号: 10371208
• 负责人: Sila Kurugol
• 金额: $ 39.83万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10371208
• 关键词: Abdominal Pain; Acceleration; Adult; Affect; Aftercare; Biological; Biological Markers; Brain; Cell Proliferation; Characteristics; Child; Clinical; Clinical Markers; Coin; Computer software; Contrast Media; Crohn' s disease; Deposition; Diagnostic; Diffusion; Digestive System Disorders; Disease; Disease Management; Disease remission; Endoscopy; Estimation Techniques; Evaluation; Fever; Gadolinium; Goals; Health Care Costs; Hemorrhagic colitis; Hospital Costs; Hospitalization; Image; Image Analysis; Image Enhancement; Imaging Techniques; Immunomodulators; Individual; Inflammation; Intestines; Ionizing radiation; Laboratory Markers; Machine Learning; Magnetic Resonance; Magnetic Resonance Imaging; Malaise; Maps; Measurement; Methods; Modeling; Monitor; Morphologic artifacts; Motion; Mucous Membrane; Operative Surgical Procedures; Outcome; Patient Outcomes Assessments; Patients; Perfusion; Pharmaceutical Preparations; Physiological; Predisposition; Prevalence; Procedures; Protocols documentation; Quality of life; Radiation; Relapse; Reporting; Reproducibility; Respiration; Safety; Software Tools; Standardization; Structure; Symptoms; Techniques; Testing; Time; Tissues; Treatment Efficacy; base; burden of illness; cell motility; chronic inflammatory disease; clinical decision-making; clinical practice; clinical remission; contrast enhanced; deep learning; deep learning model; density; diagnostic accuracy; diffusion weighted; economic impact; efficacy evaluation; gut inflammation; healing; imaging biomarker; imaging modality; imaging software; improved; indexing; individual patient; individualized medicine; molecular marker; novel; open source; quantitative imaging; response; response biomarker; soft tissue; software development; success; tool; treatment response; treatment strategy; water diffusion

Project Summary: Crohn's disease (CD) is a chronic inflammatory disease of the gastrointestinal tract that has a prevalence of over 800,000 in the US alone. The economic impact is disproportionally high because it affects primarily young individuals. The characteristic periods of remission and relapse necessitate frequent hospitalizations. There has been a recent shift in clinical practice from a reactive to a proactive CD treatment strategy, recently coined as “treat-to-target”, where patients are treated to achieve not only an initial response-to-therapy, but also longer clinical remissions and improved mucosal healing. However, this approach requires the regular assessment of disease activity using objective markers enabling treatments to be tailored to the individual patient. Therefore, there is an unmet need for new tools to improve diagnostic accuracy, to quantify disease burden, and to monitor treatment efficacy. Our application in response to PAR-19-056, “Robust quantitative MR imaging markers of response to therapy in Crohn's disease” is aimed at developing and evaluating noninvasive, contrast and radiation-free quantitative imaging markers for assessing disease activity and for monitoring response to therapy. Currently available non-contrast MR imaging (MRI) sequences such as diffusion-weighted MRI (DW-MRI) and the calculated apparent diffusion coefficient (ADC) maps are attractive but limited in providing robust and reproducible markers. Different imaging protocols or different scanners result in different ADC values. Our primary goal is to develop robust and reliable quantitative DW-MR imaging markers for the non-contrast and non-invasive assessment of CD. The proposed novel MRI acquisition and model fitting techniques will provide measurements of slow and fast diffusion as well as fraction of fast diffusion, as highly accurate, quantitative biomarkers for cell proliferation, density and size, and tissue perfusion—all indices that characterize the extent of disease activity (i.e., inflammation) in the tissue micro-structure of the bowel. To achieve this goal, we will first develop and implement an advanced distortion and motion corrected (DiMoCo) DW-MRI technique and a spatially constrained probabilistic intravoxel incoherent motion (SPIM) model to compute robust and reproducible markers. Next, we will reduce the imaging time with estimated x4 acceleration with an accelerated image acquisition and a new, advanced deep learning-based parameter estimation technique. The proposed imaging techniques and software tools will provide robust quantitative markers, thereby enabling the accurate assessment of CD activity and response to therapy. They will also reduce the need for invasive endoscopy procedures as well as the total number of other tests typically ordered for monitoring disease, effectively reducing both the disease burden and the overall cost of healthcare. Another important goal is to develop and broadly disseminate open source software that will enable the standardized evaluation of other diseases presently evaluated with DW-MRI that would benefit from the advanced diagnostic and assessment capabilities of the proposed DiMoCo SPIM-DW-MRI technique.

项目概要： 克罗恩病（CD）是一种胃肠道慢性炎症性疾病， 仅在美国就超过80万。经济影响非常大，因为它主要影响年轻人 个体缓解和复发的特征期需要频繁住院治疗。那里 是最近临床实践中从被动到主动CD治疗策略的转变， 作为“达标治疗”，患者接受治疗不仅要达到最初的治疗反应，还要达到 更长的临床缓解期和改善的粘膜愈合。但是，这种方法需要定期 使用客观标志物评估疾病活动，使治疗能够针对个人 病人因此，对新工具的需求尚未得到满足，以提高诊断准确性，量化疾病， 负担，并监测治疗效果。我们的应用程序响应PAR-19-056，“稳健 克罗恩病治疗反应的定量磁共振成像标记物”旨在开发 以及评估非侵入性、造影剂和无辐射的定量成像标记物， 疾病活动和监测对治疗的反应。当前可用的非造影剂MR成像 (MRI)序列，如扩散加权MRI（DW-MRI）和计算的表观扩散系数 (ADC)图谱是有吸引力的，但在提供鲁棒的和可再现的标记方面是有限的。不同的成像方案 或者不同的扫描器导致不同的ADC值。我们的主要目标是开发强大而可靠的 定量DW-MR成像标记物，用于CD的非造影剂和非侵入性评估。拟议 新的MRI采集和模型拟合技术也将提供慢扩散和快扩散的测量 作为快速扩散的分数，作为细胞增殖、密度和大小的高度准确的定量生物标志物， 和组织灌注-表征疾病活动程度的所有指标（即，炎症） 肠道的微观结构为了实现这一目标，我们将首先开发和实施一种先进的扭曲 和运动校正（DiMoCo）DW-MRI技术和空间约束概率体素内 非相干运动（SPIM）模型来计算鲁棒的和可再现的标记。接下来，我们将减少 通过加速图像采集和新的高级深度成像， 基于学习的参数估计技术。拟议的成像技术和软件工具将 提供稳健的定量标志物，从而能够准确评估CD活性和对 疗法它们还将减少对侵入性内窥镜检查程序的需求以及其他检查的总数。 通常用于监测疾病的测试，有效地降低了疾病负担和总成本 医疗保健。另一个重要目标是开发和广泛传播开放源码软件， 使目前使用DW-MRI评估的其他疾病的标准化评估能够受益于 提出的DiMoCo SPIM-DW-MRI技术的先进诊断和评估能力。