Evaluation of algorithms for microperfusion assessment by fast simulations of laser Doppler power spectral density

Diagnosis of Skin Vascular Complications Revealed by Time-Frequency Analysis and Laser Doppler Spectrum Decomposition

Nowadays, photonics-based techniques are used extensively in various applications, including functional clinical diagnosis, progress monitoring in treatment, and provision of metrological control. In fact, in the frame of practical implementation of optical methods, such as laser Doppler flowmetry (LDF), the qualitative interpretation and quantitative assessment of the detected signal remains vital and urgently required. In the conventional LDF approach, the key measured parameters, index of microcirculation and perfusion rate, are proportional to an averaged concentration of red blood cells (RBC) and their average velocity within a diagnostic volume. These quantities compose mixed signals from different vascular beds with a range of blood flow velocities and are typically expressed in relative units. In the current paper we introduce a new signal processing approach for the decomposition of LDF power spectra in terms of ranging blood flow distribution by frequency series. The developed approach was validated in standard occlusion tests conducted on healthy volunteers, and applied to investigate the influence of local pressure rendered by a probe on the surface of the skin. Finally, in limited clinical trials, we demonstrate that the approach can significantly improve the diagnostic accuracy of detection of microvascular changes in the skin of the feet in patients with Diabetes Mellitus type 2, as well as age-specific changes. The results obtained show that the developed approach of LDF signal decomposition provides essential new information about blood flow and blood microcirculation and has great potential in the diagnosis of vascular complications associated with various diseases.

Laser Doppler Spectrum Analysis Based on Calculation of Cumulative Sums Detects Changes in Skin Capillary Blood Flow in Type 2 Diabetes Melitus

In this article, we introduce a new method of signal processing and data analysis for the digital laser Doppler flowmetry. Our approach is based on the calculation of cumulative sums over the registered Doppler power spectra. The introduced new parameter represents an integral estimation for the redistribution of moving red blood cells over the range of speed. The prototype of the device implementing the technique is developed and tested in preliminary clinical trials. The methodology was verified with the involvement of two age groups of healthy volunteers and in a group of patients with type 2 diabetes mellitus. The main practical result of the study is the development of a set of binary linear classifiers that allow the method to identify typical patterns of the microcirculation for the healthy volunteers and diabetic patients based on the presented diagnostic algorithm.

False spectra formation in the differential two-channel scheme of the laser Doppler flowmeter

Noise in the differential two-channel scheme of a classic laser Doppler flowmetry (LDF) instrument was studied. Formation of false spectral components in the output signal due to beating of electrical signals in the differential amplifier was found out. The improved block-diagram of the flowmeter was developed allowing to reduce the noise.

Assessment of speed distribution of red blood cells in the microvascular network in healthy volunteers and type 1 diabetes using laser Doppler spectra decomposition

We applied a recently reported method of decomposition of laser Doppler power density spectra for in vivo monitoring of speed distributions of red blood cells (RBCs) in the microvascular network. The spectrum decomposition technique allows us to derive the distribution of RBC speed (in absolute units (mm s(-1))) versus RBC concentration (in arbitrary units). We carried out postocclusive reactive hyperaemia (PORH) test in 15 healthy volunteers and 21 diabetic patients in which the duration of type 1 diabetes was longer than 10 years. Measurements were carried out simultaneously with the use of a typical laser Doppler commercial instrument and speed resolved laser Doppler instrument utilizing the new technique based on decomposition of the laser Doppler spectra. We show that for the classical laser Doppler instrument, none of the PORH parameters revealed a statistical significance of difference between the groups analyzed. In contrast, the RBC speed distributions obtained from laser Doppler spectra during rest in the control group and type 1 diabetes are statistically significant. This result suggests that speed distribution measurements in the rest state (without any kind of stimulation test) allows for the assessment of microcirculation disorders. Measurements carried out in healthy subjects show that the first moment of speed distributions (mean speed of the distributions) is 2.32 ± 0.54 mm s(-1) and 2.57 ± 0.41 mm s(-1) for optodes located on the toe and finger of the hand, respectively. Respective values in type 1 diabetes were higher: 3.00 ± 0.36 mm s(-1) and 3.10 ± 0.48 mm s(-1).

Estimation of scattering phase function utilizing laser Doppler power density spectra

A new method for the estimation of the light scattering phase function of particles is presented. The method allows us to measure the light scattering phase function of particles of any shape in the full angular range (0°-180°) and is based on the analysis of laser Doppler (LD) power density spectra. The theoretical background of the method and results of its validation using data from Monte Carlo simulations will be presented. For the estimation of the scattering phase function, a phantom measurement setup is proposed containing a LD measurement system and a simple model in which a liquid sample flows through a glass tube fixed in an optically turbid material. The scattering phase function estimation error was thoroughly investigated in relation to the light scattering anisotropy factor g. The error of g estimation is lower than 10% for anisotropy factors larger than 0.5 and decreases with increase of the anisotropy factor (e.g. for g = 0.98, the error of estimation is 0.01%). The analysis of influence of the noise in the measured LD spectrum showed that the g estimation error is lower than 1% for signal to noise ratio higher than 50 dB.

Study of time reversibility/irreversibility of cardiovascular data: theoretical results and application to laser Doppler flowmetry and heart rate variability signals

Time irreversibility can be qualitatively defined as the degree of a signal for temporal asymmetry. Recently, a time irreversibility characterization method based on entropies of positive and negative increments has been proposed for experimental signals and applied to heart rate variability (HRV) data (central cardiovascular system (CVS)). The results led to interesting information as a time asymmetry index was found different for young subjects and elderly people or heart disease patients. Nevertheless, similar analyses have not yet been conducted on laser Doppler flowmetry (LDF) signals (peripheral CVS). We first propose to further investigate the above-mentioned characterization method. Then, LDF signals, LDF signals reduced to samples acquired during ECG R peaks (LDF_R(ECG) signals) and HRV recorded simultaneously in healthy subjects are processed. Entropies of positive and negative increments for LDF signals show a nonmonotonic pattern: oscillations--more or less pronounced, depending on subjects--are found with a period matching the one of cardiac activity. However, such oscillations are not found with LDF_R(ECG) nor with HRV. Moreover, the asymmetry index for LDF is markedly different from the ones of LDF_R(ECG) and HRV. The cardiac activity may therefore play a dominant role in the time irreversibility properties of LDF signals.