Label-free measurement of blood lipids with hyperspectral short-wave infrared spatial frequency domain imaging to improve cardiovascular disease risk prediction and treatment monitoring

利用高光谱短波红外空间频域成像对血脂进行无标记测量，以改善心血管疾病风险预测和治疗监测

• 批准号: 10178014
• 负责人: Darren Michael Roblyer
• 金额: $ 20.92万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10178014
• 关键词: 3D Print; Address; Affect; Algorithms; Area; Benchmarking; Biological; Biological Markers; Blood; Blood Pressure; Blood Tests; Blood Vessels; Cardiovascular Diseases; Cessation of life; Cholesterol; Classification; Clinical; Clinical Research; Collagen; Custom; Data; Development; Devices; Economics; Event; Fatty acid glycerol esters; Feasibility Studies; Feedback; Funding; Future; Geography; Goals; Gold; Guidelines; High Density Lipoproteins; Home; Hydration status; Image; Imaging Techniques; Individual; Infrastructure; Intervention; LDL Cholesterol Lipoproteins; Label; Laboratories; Lasers; Lead; Light; Lighting; Lipids; Lipoproteins; Liquid substance; Low-Density Lipoproteins; Measurement; Measures; Medical; Menstrual cycle; Methodology; Methods; Modeling; Monitor; Near-infrared optical imaging; Optics; Pain; Patient Monitoring; Patient-Focused Outcomes; Patients; Pattern; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Property; Reagent; Research; Resolution; Resources; Risk; Scanning; Short Waves; Skin; Sleep Apnea Syndromes; Spatial Frequency Domain Imaging; Speed; System; Technology; Test Result; Testing; Thick; Time; Tissue Extracts; Triglycerides; Variant; Water; Work; base; blood lipid; cardiovascular disorder risk; cardiovascular risk factor; circadian; classification algorithm; clinical translation; cost; diet and exercise; digital; economic cost; equipment training; follow-up; heart rhythm; improved; improved outcome; in vivo; innovation; instrumentation; laboratory equipment; negative affect; patient stratification; portability; research clinical testing; risk prediction; risk stratification; screening; simulation; technology development; tool; volunteer

ABSTRACT: Cardiovascular disease (CVD) reportedly causes 31% of global deaths with overwhelming personal and economic costs, the latter estimated as $400 billion annually in the US. Lack of regular screening contributes to severe undertreatment for CVD, with some estimates finding only 1/3 of eligible patients taking preventative medications. One of the most important biomarkers for CVD, elevated blood lipids, requires invasive blood draws followed by lab-based testing. These requirements limit access to screening for many at-risk patients in low resource settings, and make frequent longitudinal monitoring impractical for everyone. Worse still, recent data shows that the temporal dynamics of blood lipids, including postprandial increases, circadian, ultradian (<24 hr cycles), and fluctuations during menstrual cycle, all negatively affect the accuracy of blood lipid test results. Non- invasive methods that more immediately and continuously track blood-lipids would transform CVD monitoring for those at risk. The goal of this project is to develop the first non-invasive optical technology for measuring blood lipids. To accomplish this goal, we will develop a new imaging technique called Short-Wave Infrared Spatial Frequency Domain Imaging (SWIR-SFDI). SWIR-SFDI leverages spectroscopic SWIR patterned illumination combined with model-based analysis to extract tissue optical properties as well as lipid and water concentrations. Compared to both visible (VIS) and near infrared (NIR) imaging, the SWIR wavelength band potentially provides better quantification of lipids and deeper imaging. In this project, we propose to develop SWIR-SFDI instrumentation and processing methodology to demonstrate that triglycerides (TG), cholesterol, LDL-C, and HDL-C, all of which are strong predictors of CVD risk, can be tracked longitudinally with high accuracy. We will fabricate a mobile hyperspectral SWIR-SFDI system with an innovative dual digital micromirror device (DMD) configuration for rapid wavelength tuning and spatial light patterning between 700 – 1600 nm at high speed. Performance benchmarks include: spectral resolution <6 nm FWHM, 10-𝜆 acquisition < 5 sec, μa and μs´ errors <3%, drift (7 hr) <2%. We will also develop a 2-layer skin-model to improve in vivo blood lipid quantification and develop methodology for spectral classification and quantification of TG, cholesterol, LDL-C, and HDL-C and test the accuracy of these algorithms in simulation and by fabricating 3-D printed vascularized phantoms with a range of skin types. Finally, we will conduct a normal volunteer feasibility study to assess the ability of SWIR- SFDI to accurately track postprandial lipids in comparison to traditional laboratory measurement from invasive blood draws. Completion of these aims will enable our team to progress to a larger R01-funded, hypothesis- driven clinical study following the period of this project. Over the longer term, SWIR-SFDI has the potential to transform CVD lipid testing and improve outcomes for patients through: 1.) Better risk-stratification for patients based on frequent measurements, 2.) Unprecedented characterization of circadian and ultradian lipid cycles, 3). More accessible monitoring during therapy, and 4) Development of at-home or wearable blood lipid monitors.

摘要： 据报道，心血管疾病（CVD）导致全球31%的死亡，其中绝大多数人和 经济成本，后者估计为4000亿美元，每年在美国。缺乏定期检查有助于 CVD治疗严重不足，一些估计发现只有1/3的合格患者服用预防性药物， 药物治疗CVD最重要的生物标志物之一，血脂升高，需要侵入性抽血 然后进行实验室测试这些要求限制了许多低风险患者接受筛查的机会。 资源设置，并使频繁的纵向监测对每个人都不切实际。更糟糕的是，最近的数据 显示血脂的时间动态，包括餐后增加、昼夜节律、超昼夜（<24小时 周期）以及月经周期期间的波动，都对血脂检测结果的准确性产生负面影响。非 更直接和连续跟踪血脂的侵入性方法将改变CVD监测， 那些处于危险之中的人。该项目的目标是开发第一种用于测量血液的非侵入式光学技术 脂质。为了实现这一目标，我们将开发一种新的成像技术，称为短波红外空间 频域成像（SWIR-SFDI）。SWIR-SFDI利用光谱SWIR图案化照明 与基于模型的分析相结合，以提取组织光学特性以及脂质和水浓度。 与可见光（维斯）和近红外（NIR）成像相比，SWIR波长带潜在地提供 更好的脂质定量和更深的成像。在这个项目中，我们建议开发SWIR-SFDI 仪器和处理方法，以证明甘油三酯（TG）、胆固醇、LDL-C和 HDL-C，所有这些都是CVD风险的强预测因子，可以高准确性地纵向跟踪。我们将 利用创新的双数字偏振器件（DMD）制造移动的高光谱SWIR-SFDI系统 用于在700 - 1600 nm之间高速进行快速波长调谐和空间光图案化的配置。 性能基准包括：光谱分辨率<6 nm FWHM，10-nm采集< 5 sec，μa和μs ′误差 <3%，漂移（7小时）<2%。我们还将开发一个2层皮肤模型，以改善体内血脂定量， 开发TG、胆固醇、LDL-C和HDL-C的光谱分类和定量方法， 测试这些算法在模拟中的准确性，并通过使用 各种皮肤类型。最后，我们将进行正常的志愿者可行性研究，以评估SWIR的能力- 与传统的实验室测量相比，SFDI可以准确地跟踪餐后血脂， 抽血这些目标的完成将使我们的团队能够发展到一个更大的R 01资助的，假设- 在本项目结束后进行的临床研究。从长远来看，SWIR-SFDI有潜力 通过以下方式改变CVD血脂检测并改善患者的结局：1.）更好地对患者进行风险分层 基于频繁的测量，2.）前所未有的昼夜节律和超昼夜脂质周期的表征，3）。 治疗期间更容易监测，以及4）开发家用或可穿戴血脂监测仪。