Vessel packaging effect in laser speckle contrast imaging and laser Doppler imaging

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.

Laser speckle contrast analysis (LASCA) technology for the semiquantitative measurement of angiogenesis in in-ovo-tumor-model

BACKGROUND

The process of angiogenesis is a key element for tumor growth and proliferation and therefore one of the determining factors for aggressiveness and malignancy. A better understanding of the underlying processes of tumor induced angiogenesis is crucial for superior cancer treatment. Furthermore, the PeriCam perfusion speckle imager (PSI) system high resolution (HR) model by PERIMED presents a noninvasive method for semi-quantitative measurement of blood perfusion, based on laser speckle contrast analysis (LASCA). Aim of the present study was to utilize the chick chorioallantoic membrane (CAM) model as an in-ovo-tumor-model which enables rapid neovascularization of tumors while allowing real-time observation of the microcirculation via LASCA.

METHODS

Fertilized chicken eggs were grafted with embryonal/alveolar rhabdomyosarcoma cells or primary sarcoma tumors. The blood perfusion was measured before and after tumor growth using LASCA. The procedure is accelerated and simplified through the integrated PIMSoft software which provides real-time graphs and color-coded images during the measurement.

RESULTS

Sarcoma cells and primary sarcoma tumors exhibited satisfactory growth processes on the CAM. LASCA visualized microcirculation accurately and enabled an extensive investigation of the angiogenic potential of sarcoma cells on the CAM. We were able to show that sarcoma cells and primary sarcoma tumors induced larger quantities of neovasculature on the CAM than the controls.

CONCLUSIONS

The utilization of LASCA for the investigation of tumor angiogenesis within the CAM model appears to be a highly beneficial, cost-efficient and easily practicable procedure. The proposed model can be used as a drug-screening model for individualized cancer therapy, especially with regards to anti-angiogenic agents.

Establishment of a Novel Fetal Growth Restriction Model and Development of a Stem-Cell Therapy Using Umbilical Cord-Derived Mesenchymal Stromal Cells

Fetal growth restriction (FGR) is a major complication of prenatal ischemic/hypoxic exposure and affects 5%-10% of pregnancies. It causes various disorders, including neurodevelopmental disabilities due to chronic hypoxia, circulatory failure, and malnutrition via the placenta, and there is no established treatment. Therefore, the development of treatments is an urgent task. We aimed to develop a new FGR rat model with a gradual restrictive load of uterus/placental blood flow and to evaluate the treatment effect of the administration of umbilical cord-derived mesenchymal stromal cells (UC-MSCs). To create the FGR rat model, we used ameroid constrictors that had titanium on the outer wall and were composed of C-shaped casein with a notch and center hole inside that gradually narrowed upon absorbing water. The ameroid constrictors were attached to bilateral ovarian/uterine arteries on the 17th day of pregnancy to induce chronic mild ischemia, which led to FGR with over 20% bodyweight reduction. After the intravenous administration of 1 × 10⁵ UC-MSCs, we confirmed a significant improvement in the UC-MSC group in a negative geotaxis test at 1 week after birth and a rotarod treadmill test at 5 months old. In the immunobiological evaluation, the total number of neurons counted via the stereological counting method was significantly higher in the UC-MSC group than in the vehicle-treated group. These results indicate that the UC-MSCs exerted a treatment effect for neurological impairment in the FGR rats.

Machine learning in multiexposure laser speckle contrast imaging can replace conventional laser Doppler flowmetry

Laser speckle contrast imaging (LSCI) enables video rate imaging of blood flow. However, its relation to tissue blood perfusion is nonlinear and depends strongly on exposure time. By contrast, the perfusion estimate from the slower laser Doppler flowmetry (LDF) technique has a relationship to blood perfusion that is better understood. Multiexposure LSCI (MELSCI) enables a perfusion estimate closer to the actual perfusion than that using a single exposure time. We present and evaluate a method that utilizes contrasts from seven exposure times between 1 and 64 ms to calculate a perfusion estimate that resembles the perfusion estimate from LDF. The method is based on artificial neural networks (ANN) for fast and accurate processing of MELSCI contrasts to perfusion. The networks are trained using modeling of Doppler histograms and speckle contrasts from tissue models. The importance of accounting for noise is demonstrated. Results show that by using ANN, MELSCI data can be processed to LDF perfusion with high accuracy, with a correlation coefficient R  =  1.000 for noise-free data, R  =  0.993 when a moderate degree of noise is present, and R  =  0.995 for in vivo data from an occlusion-release experiment.