Tissue oximetry parameter detection based on near-infrared spectroscopy has the advantages of being rapid,real-time,and non-invasive,and has been widely used in clinics with important application values.Near-infrared spectroscopic tissue oximetry requires a combination of different wavelengths of near-infrared light to calculate the concentration of oxyhaemoglobin and reduced haemoglobin,but the combination of wavelengths currently used to detect oximetry information is not uniform.The wavelength selection of the light source is directly related to the accuracy of the extraction of tissue blood oxygenation parameters.In order to improve the measurement accuracy,a wavelength selection method based on condition number was established in this study and experimentally verified by tissue mimicry and in vivo experiments.The experimental results show that when the absorption and scattering coefficients of tissue mimics are changed,the error of total haemoglobin concentration calculated by the smallest conditioned number group is the smallest,and the error calculated by the largest conditioned number group is the largest.In the in vivo experiment,when the collected spectral signals were denoised,the smallest conditioned number group calculated oxygen saturation with small error and the largest conditioned number group inverted oxygen saturation with the largest error,which is in accordance with the underlying theory of conditioned numbers.Therefore,it is feasible to optimize and select the wavelength using the conditional number method,which improves the tolerance of error in the calculation of optical parameters into physiological parameters,and provides a methodological basis for the rational selection of wavelength for tissue blood oxygen detection.

The peripheral retinal refractive state plays an important role in eye growth and development and is closely related to the development of myopia. Existing methods for measuring the peripheral retinal refractive state are cumbersome and can only detect in a limited range. To address the above shortcomings, this paper proposes a retinal refractive state detection method using optical refractive compensation imaging. First, a series of defocus images is captured using an optical system, and then the images are enhanced and filtered. Subsequently, the Sobel function is applied to calculate sharpness, and the asymmetric Gaussian (AG) model is employed for peak fitting, allowing for the determination of the fundus retina's overall refractive compensation value. We performed consistency analysis on the central and peripheral diopters with autorefractor KR-8900 (Topcon, Japan) and WAM-5500 (Grand Seiko, Japan), respectively. The intraclass correlation coefficients (ICCs) are all greater than 0.9, showing good consistency. This is a promising alternative to the current techniques for assessing the refraction of the peripheral retina.

Excessive bacterial load will not only cause delayed wound healing and local or systemic inflammatory reaction, but also threaten the life safety of patients in severe cases. Therefore,a new method that can detect wound bacteria quickly and directly is needed. Traditional bacterial detection methods are mainly visual observation of clinical symptoms (including fever,redness and swelling,pus exudate, etc.) and microbial swab sampling, but these two methods are usually subjective and timeconsuming. The results of the same clinical symptom observed by doctors with different experiences may be different,and in some cases the infection may not show obvious symptoms. Therefore, it is often subjective to judge the infection by observing the clinical symptoms with naked eyes and may cause misdiagnosis. Swab sampling is often plagued by false negative,and different sampling methods and selection of sampling areas will affect the results of sampling and culture. False negative areas or missed areas may contain a large number of bacteria. The missing of a large number of bacteria in these areas may lead to repeated wound healing,causing great pain to patients and great burden on the medical and health system. In addition,longer culture time is also a pain point for swab sampling,because it may cause inaccurate culture results and miss the best treatment opportunity. Relevant studies have found that bacteria can emit fluorescence by themselves under the excitation of 405 nm light source,without using contrast agents. The purpose of this study is to design a fluorescence detection imaging device based on the principle of spontaneous fluorescence of bacteria,which provides a fast and direct new method for wound bacteria detection. In this study,a bacterial fluorescence imaging system is developed. The light source module of the system consists of two LED with a central wavelength of 405 nm and LED driver modules. After calibration and parameter setting,the light source driver works in constant current mode to ensure stable operation of the light source. When the light source shines on the wound bacteria,it can stimulate the spontaneous fluorescence of bacteria almost in a moment. The customized dual band filter is used to receive bacterial fluorescence and filter out the interference of reflected light from the light source. The transmission band of the filter is selected according to the results of the three-dimensional fluorescence spectrum of bacteria. In the dark environment,the smartphone imaging mode is set to night mode,the shutter speed is set to 3 s,the automatic white balance is set,and each sample is collected five times to reduce experimental error. Porphyrin fluorescence images are converted into three-dimensional intensity images to verify the imaging uniformity of the device. The fluorescence region is detected by region extraction algorithm,and the bacterial fluorescence is quantified. The signal area is extracted by using the Hough circle detection and edge contour extraction method as well as the mask method obtained by using the binary function. The gray value of all pixels in the signal area is traversed and the average value is calculated, which is taken as the quantitative result of the relative fluorescence intensity of bacteria. Finally,a linear rule between the fluorescence intensity and the concentration is obtained by linear fitting of the quantitative result. The experimental results of three-dimensional fluorescence spectrum of bacteria provide an important basis for the selection of excitation and emission bands in this study. It can be seen from the porphyrin three- dimensional intensity map that,except for the projection points of the two light sources,the uniformity of the signal area is good. This indicates that the two LED light sources used in the device can uniformly excite the fluorescent signal area,and the fluorescent image with good quality can be obtained without using the whole row of ring LEDs as light,which greatly reduces the power consumption and heat generation of the system. The result of image processing proves that regular and irregular signal regions can be extracted with the device. The regular region extraction algorithm can accurately extract the fluorescent signal region,avoid the fluorescent interference of the culture dish wall,and effectively improve the calculation accuracy of the relative signal strength. The gradient concentration of Escherichia coli and Staphylococcus aureus shows that there is a good linear relationship between the bacterial fluorescence intensity and the bacterial quantity under the experimental bacterial concentration. Combined with the bacterial plate counting experiment,the minimum detection limit of the system is 105 CFU/ mL,which indicates that the system can effectively detect the infection of wounds. Through linear fitting of the calculation results,it can be obtained that there is a linear relationship between bacterial fluorescence intensity and concentration,and the minimum detection limit of the system can be calculated according to the linear relationship. The device provides a new means for the bacterial detection of the wound,with high detection sensitivity to meet the bacterial load identification of the infected wound. There is no need for swab sampling and fluorescent labeling,and the detection procedure is simple and easy to operate. The extraction of signal region can clearly and intuitively show the location of bacteria,which can provide effective reference information for wound debridement and targeted drug administration. This study only conducts quantitative detection of bacteria in vitro,and further measurement of bacteria in vivo is needed. In addition,future efforts should include the development of a smartphone app that integrates existing processing algorithms to further simplify the process and enable rapid in vivo detection of wound bacteria.

Objective The Muller matrix, as a method for characterizing the polarization properties of samples, contains complete information about the polarization properties of samples, and it has become an important indicator for characterizing pathological tissues in basic and preclinical studies. However, in the traditional polarized light imaging method for measuring the Muller matrix, the scattering depth of polarized light in collagen tissue cannot be controlled. The obtained Muller matrix information is the average of unknown depths in collagen tissue, and it is impossible to accurately measure the Muller matrix information of the pathological tissue area. Polarized spatial frequency domain imaging (PSFDI), which combines spatial frequency domain imaging (SFDI) and polarized light imaging, is applied to measure the optical properties of biological tissues accurately.Methods SFDI relates the spatial frequency of the projected stripe pattern to the penetration depth of the detected light, and the imaging depth can be controlled by controlling the spatial frequency of the projected light. We designed and validated a polarization SFDI system that uses the SFDI technique to control the imaging depth, projects the streak pattern onto the surface of the measured tissue, constructs a polarizer and detector to modulate the polarization state of the polarized light, and then acquires the image data using a CMOS camera and calculates the Mueller matrix information.Results and Discussions Experimental results showed that the grey -scale plate diffuse reflectance measured by the polarization SFDI system was linearly correlated with the standard value (R2=0.99988). The depolarization coefficient tends to be proportional to the fat emulsion volume fraction, the two-way attenuation coefficient increases with the increase of two-way attenuation owing to the two-way attenuator, and the accurate measurement of the phase delay of the quarter -wave and full -wave plates indicates that the system can accurately measure the sample polarization parameters. A comparison of uniform light field illumination and polarization -sensitive SFDI shows that the latter effectively controls the depth and accurately measures the shallow Mueller matrix of the sample. The results of this study are expected to effectively improve the accuracy of the detection of polarization characteristics of superficial tissues and promote early tumor detection.Conclusions In this study, a PSFDI system is developed based on polarized light imaging and SFDI, and the device structure, measurement method, and data processing method are introduced. By performing the error calibration of the PSFDI device, the measurement error of the device can be less than 2%. By performing Mueller matrix imaging on tissues, we verified the reliability of the device to measure tissue polarization Mueller and the accuracy of the Mueller matrix decomposition; hence, PSFDI can be used to obtain the optical properties of various samples. The PSFDI can accurately image pathological regions, providing accurate physiological parameters for pathological analysis, and it has a wide range of biomedical applications.

There is an urgent need for a mass population screening tool for diabetes. Skin tissue contains a large number of endogenous fluorophores and physiological parameter markers related to diabetes. We built an excitation-emission spectrum measurement system with the excited light sources of 365, 395, 415, 430, and 455 nm to extract skin characteristics. The modeling experiment was carried out to design and verify the accuracy of the recovery of tissue intrinsic discrete three-dimensional fluorescence spectrum. Blood oxygen modeling experiment results indicated the accuracy of the physiological parameter extraction algorithm based on the diffuse reflectance spectrum. A community population cohort study was carried out. The tissue-reduced scattering coefficient and scattering power of the diabetes were significantly higher than normal control groups. The Gaussian multi-peak fitting was performed on each excitation-emission spectrum of the subject. A total of 63 fluorescence features containing information such as Gaussian spectral curve intensity, central wavelength position, and variance were obtained from each person. Logistic regression was used to construct the diabetes screening model. The results showed that the area under the receiver operating characteristic curve of the model for predicting diabetes was 0.816, indicating a high diagnostic value. As a rapid and non-invasive detection method, it is expected to have high clinical value.

Objective Brain blood oxygen monitoring based on near infrared spectroscopy can display the state of oxygen supply and demand in the brain noninvasively, continuously and in real time. It is very important for brain protection in surgery and has high application value in many departments of the hospital. Differential pathlength factor (DPF) is one of the important variables for calculating cerebral oxygen saturation. Because photons propagate in human skin tissues with forward scattering characteristics and absorption and scattering occur continuously in the propagation process, the actual propagation path length of photons is not equal to the distance between the light source and the detector, so a DPF should be introduced to correct the propagation path length. The traditional method to obtain the DPF is to first simulate the propagation trajectories of photons in biological tissues through Monte Carlo modeling of light transport in multi-layered tissues, and then give the DPF according to the simulation information of each photon. The amount of calculation in this process is large and the simulated order of magnitude of photon is at least one million, which make it difficult to extract the photon propagation information related to the DPF. It takes a lot of time to calculate each DPF, and batch operation cannot be realized. Therefore, a DPF is usually set as a constant in the existing algorithms of near-infrared cerebral oxygen monitoring instrument. However, a DPF is related to the optical parameters and thickness of each layer of one brain tissue. There are great differences in the optical parameters and thicknesses of different individual brain tissues, resulting in great individual differences in the DPF. If it is set as a constant, the actual measurement will not accurately reflect the changes of cerebral blood oxygen parameters of different individuals. Methods In view of the above shortcomings, a fast DPF quantitative calculation method is proposed in this paper. First, 120 groups of people aged at 0--50 years are selected as the initial variables of the experimental samples, and 120 groups of DPF values are simulated and calculated in the MCML program as the initial experimental variables, of which 90 groups are used as the training dataset and 30 groups are used as the test dataset. Because the optical parameters of each layer of the brain tissue for the experimental input data vary greatly and the anisotropy factor and the refractive index of each layer of the brain tissue are close, in order to improve the experimental accuracy and prevent overfitting of the regression simulator, the mean normalization and the principal component analysis are used to preprocess the experimental input data. Second, support vector machine (SVM) combined with grid search (GS) is used to establish the prediction model of brain tissue differential pathlength factor based on GS-SVM. Support vector machine can quickly map the original samples to a high-dimensional linear feature space through a radial kernel function, and effectively classify and regress the data. The grid optimization algorithm finds the appropriate penalty parameter C and the parameter g of the Gaussian kernel function by traversing the grid, so as to minimize the mean square error of the regression simulator. Finally, the prediction model is used to back judge the test dataset and its results are compared with the prediction results of the back propagation artificial neural network (BP-ANN ). The number of hidden layers is set to two, and the same training set and test set in the GS-SVM prediction model are used. Results and Discussions The results show that, compared with the results of Monte Carlo simulation, the mean square errors (MSE) of the GS-SVM prediction model and the BP-ANN prediction model are 0.0268 and 0.25, and the correlation coefficients (R2) are 0.97 and 0.92, respectively (Fig. 3). The prediction result of the brain tissue differential pathlength factor quantitative model based on GS-SVM is better than that based on BP-ANN (Table 3 ), which is significantly correlated with the result of the Monte Carlo simulation (Fig. 4). In the Win10 system under the operating platform with i5-9500 CPU and 8 GB memory, it takes about 4 min to calculate a single DPF using Monte Carlo simulation. The calculation time under different parameters is different. The total time for calculating 120 groups of data is about 8 h, totaling 28943 s, in contrast, it takes only 1.52 s to calculate 120 groups of DPF based on the GS-SVM model and the calculation speed is significantly improved. Conclusions In this paper, a brain tissue differential pathlength factor prediction model based on GS-SVM is established to quickly predict the DPF value of a brain tissue, and this method is compared with the BP-ANN prediction model. The results show that the grid optimization algorithm can automatically and accurately optimize the penalty parameter C and the parameter g of the Gaussian kernel function. The prediction results of the brain tissue differential pathlength factor prediction model based on GS-SVM are better than those based on BP-ANN, and have significant correlation with the prediction results of the Monte Carlo simulation method. It is expected to replace the Monte Carlo simulation method for batch calculation of DPF values. It can be applied in the near infrared cerebral oxygen monitoring instrument to make the calculation of physiological parameters of cerebral oxygen metabolism more rapid and accurate.

空间频域成像(spatial frequency domain imaging,SFDI)作为一种新颖的光学成像技术,主要采用结构光与特定的光传输模型相结合,在检测组织形态结构的同时能够提供组织的光学和生理参数信息,具有快速、宽场、无创、非接触、定量检测等特点,广泛应用于生物医学基础研究和临床诊疗等多个领域.本文就SFDI技术的基本原理和方法,以及其在临床常见疾病中的应用现状与研究进展作一综述,旨在为临床相关疾病的诊疗提供一种科学、新颖、可靠的评估方法.

SIGNIFICANCE:Optical properties (absorption coefficient and scattering coefficient) of tissue are the most critical parameters for disease diagnosis-based optical method. In recent years, researchers proposed spatial frequency domain imaging (SFDI) to quantitatively map tissue optical properties in a broad field of contactless imaging. To solve the limitations in wavebands unsuitable for silicon-based sensor technology, a compressed sensing (CS) algorithm is used to reproduce the original signal by a single-pixel detectors. Currently, the existing single-pixel SFDI method mainly uses a random sampling policy to extract and recover signals in the acquisition stage. However, these methods are memory-hungry and time-consuming, and they cannot generate discernible results under low sampling rate. Explorations on high performance and efficiency single-pixel SFDI are of great significance for clinical application. AIM:Fourier single-pixel imaging can reconstruct signals with less time and space costs and has fewer reconstruction errors. We focus on an SFDI algorithm based on Fourier single-pixel imaging and propose our Fourier single-pixel image-based spatial frequency domain imaging method (FSI-SFDI). APPROACH:First, we use Fourier single-pixel imaging algorithm to collect and compress signals and SFDI algorithm to generate optical parameters. Given the basis that the main energy of general image signals is concentrated in the range of low frequency of Fourier frequency domain, our FSI-SFDI uses a circular-sampling scheme to sample data points in the low-frequency region. Then, we reconstruct the image details from these points by optimization-based inverse-FFT method. RESULTS:Our algorithm is tested on simulated data. Results show that the root mean square error (RMSE) of optical parameters is lower than 5% when the data reduction is 92%, and it can generate discernible optical parameter image with low sampling rate. We can observe that our FSI-SFDI primarily recovers the optical properties while keeping the RMSE under the upper bound of 4.5% when we use an image with 512  ×  512 resolution as the example for calculation and analysis. Not only that but also our algorithm consumes less space and time for an image with 256  ×  256 resolution, the signal reconstruction takes only 1.65 ms, and requires less RAM memory. Compared to CS-SFDI method, our FSI-SFDI can reduce the required number of measurements through optimizing algorithm. CONCLUSIONS:Moreover, FSI-SFDI is capable of recovering high-quality resolvable images with lower sampling rate, higher-resolution images with less memory and time consumed than previous CS-SFDI method, which is very promising for clinical data collection and medical analysis.

There is a great demand for the rapid and non-invasive atherosclerosis screening method. Cholesterol content in the epidermis of the skin is an early biomarker for atherosclerosis. Risk assessment of atherosclerosis can be achieved by measuring cholesterol in the epidermis. Here, we synthesised a new fluorescent digitonin derivative (FDD) for the non-invasive detection of skin cholesterol. The results of fluorescence spectroscopy studies indicated that the probe exhibited desirable selectivity for cholesterol. The proof-of-concept preclinical study confirmed that FDD can detect different concentrations of skin cholesterol; patients diagnosed with atherosclerotic cardiovascular disease and the at-risk atherosclerosis group exhibited higher skin cholesterol content than the normal group. The area under the ROC curve for distinguishing the normal/disease group was 0.9228 (95% confidence interval, 0.8938 to 0.9518), and the area under the ROC curve for distinguishing the normal/risk group was 0.9422 (95% confidence interval, 0.9178 to 0.9665). We anticipate that this non-invasive skin cholesterol test may be used as a risk assessment tool for atherosclerosis screening in a large population for further examination and intervention in high-risk populations.

Background Lipid management is the first line of treatment for decreasing the incidence of cardiovascular events in patients with coronary heart disease (CHD), and a variety of indicators are used to evaluate lipid management. This work analyses the differences in LDL-C and apoB for lipid management evaluation, as well as explores the feasibility of skin cholesterol as a marker that can be measured non-invasively for lipid management. Methods The prospective study enrolled 121 patients who had been diagnosed with acute coronary syndrome (ACS) at the department of emergency medicine of the First Affiliated Hospital of the USTC from May 2020 to January 2021, and the patients were grouped into Group I ( n =53) and Group II ( n =68) according to whether they had comorbid hyperlipidemia and/or diabetes mellitus. All patients were administered 10 mg/day of rosuvastatin and observed for 12 weeks. Lipid management was assessed on the basis of LDL-C and apoB, and linear correlation models were employed to assess the relationship between changes in these well accepted markers to that of changes in skin cholesterol. Results Out of 121 patients with ACS, 53 patients (43.80 %) had combined hyperlipidemia and/or diabetes mellitus (Group I), while 68 patients (56.20 %) did not (Group II). Cardiovascular events occur at earlier ages in patients with CHD who are comorbid for hyperlipidemia and/or diabetes ( P <0.05). LDL-C attainment rate is lower than apoB attainment rate with rosuvastatin therapy ( P <0.05), which is mainly attributable to patients with low initial LDL-C. Skin cholesterol reduction correlated with LDL-C reduction. (r=0.501, P <0.001) and apoB reduction (r=0.538, P <0.001). Skin cholesterol reduction continued over all time points measured. Conclusions Examination of changes in apoB levels give patients with low initial LDL-C more informative data on lipid management than LDL-C readings. In addition, non-invasive skin cholesterol measurements may have the potential to be used independently for lipid management evaluation.

Objective Skin cholesterol is an important biomarker for early atherosclerosis screening. Atherosclerosis is the leading cause of disability and death from cardiovascular disease. Effective control of pathogenic factors in the early pathological stage may delay or prevent the development of asymptomatic atherosclerosis into cardiovascular diseases. Thus, skin cholesterol detection becomes relevant in the prevention of cardiovascular diseases. Traditional skin cholesterol detection methods, such as skin biopsy or tape stripping, are invasive and usually time consuming. Alternatively, the recent three-drop method is being widely studied. In this method, three specific concentrations of reagents that bind to skin cholesterol are used on the skin surface of a subject, and atherosclerosis can be diagnosed by analyzing the reagent color changes. However, the three-drop method is sensitive to the application habits of the operator. Moreover, the detection reagents contain enzymes, polymers, and small molecule compounds, hindering quality control and increasing the sensitivity to environmental factors such as temperature and pH levels. We report a non-invasive skin cholesterol detection technique based on fluorescent spectrometry. By measuring the fluorescence spectrum of fluorescent-labeled skin, the cholesterol content can be calculated from the fluorescence spectra. This method corrects the influence of temperature on the test results and provides stability under various environmental conditions. Moreover, the skin cholesterol content can be obtained within 4 minutes. The proposed method provides a rapid non-invasive and stable method for skin cholesterol detection and corresponding applications including early atherosclerosis screening. Methods The proposed non-invasive skin cholesterol detection system is composed of a light source, fiber probe, spectrometer, photodiode, infrared temperature sensor, and computer. The fluorescence fluctuation of the detection reagent caused by temperature variation is corrected by establishing the relation between temperature and the fluorescence intensity of the detection reagent. To confirm the accuracy of the proposed skin cholesterol detection system, we extract skin cholesterol with absolute ethanol after the non-invasive measurement. The cholesterol content in the extraction liquid is determined by gas chromatography, and the correlation between the two results are analyzed. Finally, the clinical applicability of the proposed system is confirmed by measuring skin cholesterol content from both healthy subjects and subjects with high risk of presenting atherosclerosis. Results ant Discussions The schematic of the proposed non-invasive skin cholesterol detection system based on fluorescent spectrometry is shown in Fig. 1. The system accurately detects skin cholesterol content after correcting for temperature. The average fluorescence intensity of the detection reagent in the 462-520 nm wavelength band decreases with increasing temperature, resulting in a significant negative correlation between fluorescence intensity and temperature (r = 0.995, p<0.0001). This relation can be used to establish a calibration curve to correct for temperature (Fig. 5). We recruited 80 subjects to verify the accuracy of the proposed system. The skin cholesterol content measured using the proposed temperature-corrected system is highly correlated (correlation coefficient of 0.905) with that measured using gas chromatography (Fig. 6). These results verify the accuracy of the proposed system to measure skin cholesterol. To verify whether the proposed system can distinguish healthy subjects from subjects with high risk of presenting atherosclerosis, we used the system in 43 and 46 subjects from the respective groups. There is a significant difference in skin cholesterol content between the healthy and high risk samples (p = 0.0004) (Fig. 7). The proposed non-invasive skin cholesterol detection system can screen subjects with high risk of presenting atherosclerosis. Nevertheless, clinical trials are required for verification given the small sample size used in this study. Conclusions We propose a rapid non-invasive detection system for skin cholesterol based on fluorescent spectrometry. The system quickly provides the skin cholesterol content on-site from the fluorescence spectrum of detection reagents that specifically bind to skin cholesterol. The proposed system performs temperature correction to prevent deviations of the measurement results and improve accuracy and stability. The system and its detection accuracy are verified through comparisons with skin cholesterol results obtained from gas chromatography. The proposed system may be used to screen people with high risk of presenting atherosclerosis by detecting skin cholesterol content in healthy subjects and subjects at high risk. Overall, the proposed system can detect skin cholesterol accurately, non-invasively, and quickly. We expect that the widespread adoption of this technology will contribute to the prevention and control of cardiovascular diseases.

目的:在冠心病患者随访中应用皮肤胆固醇无创检测系统检测皮肤胆固醇水平,探讨皮肤胆固醇在冠心病慢病管理中的应用价值.方法:本研究为短期、非干预性、前瞻性研究,入选2020年5月-2020年11月在中国科学技术大学附属第一医院住院治疗的急性冠状动脉综合征患者102例,所有患者均采用瑞舒伐他汀10 mg/d作为起始降脂方案,在入院次日、第2周、第4周、第8周、第12周空腹测定血脂及皮肤胆固醇,并根据随访4周时低密度脂蛋白胆固醇(LDL-C)是否达标分为降脂达标组以及降脂未达标组.结果:线性相关分析显示,皮肤胆固醇降幅与LDL-C降幅呈正相关(r=0.528,P＜0.001).在同一随访节点,降脂达标组皮肤胆固醇降幅中位数较未达标组高(P＜0.05).降脂达标组皮肤胆固醇降幅随时间延长逐渐上升,LDL-C降幅总体呈上升趋势;降脂未达标组皮肤胆固醇降幅、LDL-C降幅随时间延长上升不明显.结论:急性冠状动脉综合征患者皮肤胆固醇降幅与血清LDL-C降幅呈正相关,提示皮肤胆固醇在急性冠状动脉综合征慢性期管理中的潜在应用能力.

目的:利用皮肤胆固醇无创检测系统检测不同狭窄程度冠状动脉(冠脉)病变患者的皮肤胆固醇水平,探索皮肤胆固醇含量与冠脉狭窄程度的关系及其在冠心病风险筛查领域中的应用价值.方法:本研究为前瞻性研究,入选中国科学技术大学附属第一医院2020年5月-2021年1月拟诊冠心病的住院患者168例,所有纳入患者近1个月内均未服用任何他汀类及其他降脂药物,住院当天接受皮肤胆固醇含量检测,住院期间完成冠脉造影,通过定量冠脉造影系统(QCA)评估冠脉狭窄严重程度,根据患者的基本临床信息,计算患者的弗明汉评分,分析皮肤胆固醇含量与冠脉狭窄严重程度以及弗明汉评分之间的相关性.结果:皮肤胆固醇含量随着冠脉狭窄严重程度的增加而增加;弗明汉评分超过10％的人群皮肤胆固醇含量显著高于弗明汉评分低于10％的人群;总胆固醇(TC)、甘油三酯(TG)、低密度脂蛋白胆固醇(LDL-C)和高密度脂蛋白胆固醇(HDL-C)水平与皮肤胆固醇含量没有显著的相关性.结论:皮肤胆固醇含量与冠脉狭窄严重程度以及弗明汉评分呈正相关,提示皮肤胆固醇含量在冠心病风险筛查领域中的应用前景良好.

Objective The technique called flow-mediated NADH fluorescence measurement is used to reflect tissue microcirculation function, which has important value for early screening of cardiovascular disease. However, due to the obvious difference in the extinction coefficients of oxyhemoglobin and deoxyhemoglobin in the visible and near-infrared bands, the tissue absorption coefficient will change constantly during the blood flow-mediated process. The excitation light and emission fluorescence of fluorescent molecules are affected by the tissue absorption coefficient. The current flow-mediated tissue fluorescence detection technology only measures the change in total tissue fluorescence intensity during brachial artery occlusion and release and does not account for the interference of tissue absorption coefficient changes caused by changes in oxygen saturation on NADH fluorescence measurement. Therefore, this problem may directly lead to blood flow-mediated tissue fluorescence technology failing to achieve an accurate measurement, thus limiting the clinical application of the technology. Methods First, we created the flow-mediated tissue fluorescence measurement system. The tissue absorption coefficient was calculated using a combination of tissue fluorescence and diffuse reflectance measurements. To improve the detection system's accuracy, a steady-state tissue intrinsic fluorescence recovery method was used to correct the interference of absorption coefficient changes during the process of brachial artery occlusion and release on NADH fluorescence measurement. Second, we carried out the validation experiments of biological tissue solid phantom with different optical parameters and blood oxygen phantom simulating the physiological process of brachial artery occlusion and release. Furthermore, we validated the flow-mediated tissue fluorescence measurement system's accuracy by comparing the corrected and uncorrected changes in blood flow-mediated tissue fluorescence in normal subjects. Results and Discussions The results of tissue solid phantom experiments with different optical parameters showed when the values of alpha and beta are 0. 67 and 0. 31, respectively, the small coefficient of variation of fluorescence intensity of the same concentration, the large linear correlation coefficient of gradient fluorescence intensity and concentration, and the closest curve shape could be satisfied at the same time (Fig. 2). After obtaining the optimal combination of alpha and beta, the fluorescence spectra of tissue phantom were recovered. The fluorescence intensity of NADH after recovery was linearly correlated with its concentration (R-2 = 0.99), which indicated that the recovery effect was better (Fig. 3). The results of blood oxygen phantom experiments showed that with the increase of sodium sulfite treatment time, oxygen saturation decreased significantly until stable. After being recharged, O-2 returned to its baseline level and then decreased for the second time. The results demonstrated that the system could accurately extract the physiological parameters of a blood phantom. We found that changes in tissue oxygen saturation could interfere with NADH fluorescence detection, whereas the corrected intrinsic fluorescence spectrum of NADH was unaffected by changes in oxygen saturation (Fig. 5). Finally, the blood flow-mediated tissue fluorescence system was used to measure the diffuse reflectance and fluorescence of four subjects during the brachial artery occlusion and release process. The low flow response (LFR) and high flow response (HFR) of four subjects were calculated separately. The results showed that the average values of LFR and HFR were 19.8% and 13. 6 %, respectively. In vivo experiments showed that after spectral recovery, the LFR and HFR decreased by 22. 8% and 22. 1%, respectively (Table 1). This change could be explained by the interference of oxygen saturation on the measured NADH fluorescence. Conclusions The extraction of tissue optical parameters and the recovery of intrinsic fluorescence in steady-state tissue fluorescence technology were introduced into flow-mediated tissue fluorescence measurement in this study to achieve the dynamic measurement of tissue intrinsic fluorescence spectrum in the blood flow-mediated process. The tissue phantom experiment of the distribution of different absorption, scattering, and gradient fluorescence characteristics was validated using the flow-mediated tissue fluorescence and diffuse reflectance measurement system. The results showed that the coefficient of variation of fluorescence intensity of tissue phantom with the same concentration of fluorescence components was approximately 36% under different absorption and scattering characteristics, whereas the coefficient of variation of intrinsic fluorescence intensity was less than 10%. The results demonstrated that the recovery algorithm reduced the impact of absorption and scattering properties on the detection of the intrinsic fluorescence spectrum. Furthermore, there was a significant positive linear correlation between the intensity of the intrinsic tissue fluorescence spectrum and the concentration of fluorescent components, indicating that the intrinsic tissue fluorescence spectrum could be used to detect fluorescent components quantitatively. The results of blood oxygen phantom experiments showed that the change of blood oxygen saturation would interfere with the fluorescence measurement, and the corrected tissue intrinsic fluorescence spectrum was independent of the change of oxygen saturation, which further verified the reliability of the algorithm. Finally, it was found through in vivo experiments that the blood flow-mediated tissue fluorescence may better reflect changes in NADH fluorescence in tissues by introducing the tissue optical parameters extraction and tissue intrinsic fluorescence spectrum recovery algorithm, which was expected to effectively improve the accuracy of this technology's tissue microcirculation function evaluation.

Background: Establishing a high-accuracy and non-invasive method is essential for evaluating cardiovascular disease. Skin cholesterol is a novel marker for assessing the risk of atherosclerosis and can be used as an independent risk factor for early assessment of atherosclerotic risk. Methods: we propose a non-invasive skin cholesterol detection method based on absorption spectroscopy. Detection reagents specifically bind to skin cholesterol and react with indicator to produce colored products, the skin cholesterol content can be obtained through absorption spectrum information of colored products detected by noninvasive technology. Gas chromatography is used to measure cholesterol extracted from the skin to verify the accuracy of the noninvasive test method. A total of 163 subjects were divided into normal group(n=58), disease group (n=26) and risk group(n=79). All subjects underwent noninvasive skin cholesterol test. The diagnostic accuracy of the measured value was analyzed by receiver-operating characteristic (ROC) curve. Results: The proposed method is able to identify porcine skin containing gradient concentration of cholesterol and the values measured by non-invasive detection method were significantly correlated with gas chromatography measured results (r=0.9074, n=73, p<0.001). We further evaluated the method on patients with atherosclerosis and high risk population as well as normal group, patients and high risk atherosclerosis group exhibited higher skin cholesterol content than normal group (all P< 0.001). The area under the ROC curve for distinguishing Normal/Disease group was 0.8243(95% confidence interval, 0.7165 to 0.9321), however, the area under the ROC curve for distinguishing Normal/Risk group was 0.8488(95% confidence interval, 0.7793 to 0.9182). Conclusions: The method demonstrated its capability of detecting different concentration of skin cholesterol. This non-invasive skin cholesterol detection system may potentially be used as a risk assessment tool for atherosclerosis screening, especially in a large population.

Tissue phantoms with different optical parameters arc designed to study the influence of absorption and scattering on tissue fluorescence and diffuse reflection spectra. An empirical recovery algorithm is optimized to correct the influence of absorption and scattering and obtain the intrinsic fluorescence spectrum of tissues. The results reveal that the empirical recovery algorithm (experience parameters k(x) and k(m) arc 0. 9 and 0-.8, respectively) can effectively reduce the influence of absorption and scattering on the fluorescence intensity, and the fluorescence intensity is linearly correlated with the concentration of fluorescence components. When we apply spectral recovery algorithm to the screening of diabetes based on skin tissue fluorescence spectrum, the results reveal that, comparing to the fluorescence spectrum before recovery, the area under receiver operating characteristic (ROC) curve increases from 0.51 to 0.81; besides, the sensitivity also increases from 38.6% to 77.6% when the specificity is 70.6%. Therefore, this study makes a major contribution to research on clinical application by optimizing fluorescence spectrum empirical recovery algorithm with tissue phantoms.

Using STM32 microprocessor, a non-invasive skin cholesterol detection system based on absorption spectroscopy was designed. The relative cholesterol content of human skin was indirectly obtained by absorption spectrum information of colored products which was detected by micro-spectrometer. The system was designed with a high-precision adjustable LED constant current source, and the fluctuation range of LED light intensity is controlled within ±1%. A liquid limit device with a simple structure, a small amount of reagents, and no need for an exact detection reagent volume was also designed to achieve accurate measurement of the measured liquid concentration. By detecting the concentration of CuSO4 solution, the accuracy of the system for quantitative detection of different concentrations of solution was verified. Using this system to detect the skin cholesterol of patients with atherosclerotic disease and control population, the test results have statistically significant differences, which preliminarily verifies that system can be used for human skin cholesterol detection.