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

摘要： 据报道，心血管疾病(CVD)导致了全球31%的死亡，其中压倒性的个人和 经济成本，后者估计在美国每年为4000亿美元。缺乏定期筛查是导致 严重的心血管疾病治疗不足，一些估计发现只有三分之一的符合条件的患者服用预防性药物 药物。心血管疾病最重要的生物标志物之一，血脂升高，需要有创性抽血。 然后是基于实验室的测试。这些要求限制了许多低风险患者的筛查机会。 资源设置，并使频繁的纵向监测对每个人来说都是不现实的。更糟糕的是，最近的数据 显示血脂的时间动态，包括餐后升高、昼夜节律、超短程(24小时) 月经周期)和月经周期的波动都会对血脂检测结果的准确性产生负面影响。非- 更即时和持续跟踪血脂的侵入性方法将改变心血管疾病的监测 那些处于危险中的人。该项目的目标是开发第一个用于血液测量的非侵入性光学技术 脂类。为了实现这一目标，我们将开发一种名为短波红外空间成像的新技术 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肪和水分浓度。 与可见光(VIS)和近红外(NIR)成像相比，SWIR波长波段潜在地提供了 更好的脂类量化和更深层次的成像。在这个项目中，我们建议发展SWIR-SFDI 仪器和处理方法，以证明甘油三酯(TG)、胆固醇、低密度脂蛋白胆固醇和 高密度脂蛋白胆固醇都是心血管疾病风险的有力预测指标，可以高精度地纵向追踪。我们会 利用创新的双数字微镜器件(DMD)制作移动高光谱SWIR-SFDI系统 配置用于快速波长调谐和高速在700-1600 nm之间的空间光图案。 性能基准包括：光谱分辨率&lt；6 nm半高宽，10-𝜆采集&lt；5秒，μa和μS的误差 &lt；3%，漂移(7小时)&lt；2%。我们还将开发一种两层皮肤模型，以改进体内血脂定量和 开发甘油三酯、胆固醇、低密度脂蛋白胆固醇和高密度脂蛋白胆固醇的光谱分类和定量方法 通过模拟和制作带有血管的3D打印模型来测试这些算法的准确性 皮肤类型的范围。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- SFDI准确跟踪餐后血脂与传统实验室侵入性测量的比较 鲜血会吸引人。完成这些目标将使我们的团队能够进展到一个更大的R01资助的假设- 跟踪本项目期间的驱动临床研究。从长远来看，SWIR-SFDI有可能 改变心血管疾病血脂测试，通过以下方式改善患者的预后：1.)为患者提供更好的风险分层 基于频繁的测量，2.)史无前例的昼夜和超常脂质循环的特征，3)。 在治疗过程中更方便地进行监测，以及4)开发家用或可穿戴式血脂监测仪。

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.