Time-resolved fluorescence intensity issued from a heterogeneous slab: Sensitivity characterization

Optical imaging using fluorescent contrast agents has become an interesting tool to differentiate diseased lesions from normal tissue. However, several sensitivity characterizations may strongly influence the time-dependent fluorescence measurements. Herein, we present a numerical model based on the finite element method that allows the simulation of time-resolved reflectance and transmittance signals from heterogeneous media mimicking breast tissues with an embedded fluorescent object (tumor). The influence, on the computed signals, of several tumor depths, as well as various fluorophore concentrations and several fluorescent markers targeting are analyzed. The results show the possibility of uncoupling location depth from the shape of the target. Therefore, the analysis of the time to reach half the maximum intensity is validated as a good localization scheme. Then, the transmitted data show that the maximal detected intensity at the bottom of the medium is very sensitive to the dye concentration but not to the tumor shape. Moreover, the strong competition between concentration determination and fluorophore distribution is presented. These results will lead to a better detection and localization of tumors

Optimisation of movement detection and artifact removal during laser speckle contrast imaging

Introduction Laser speckle contrast imaging (LSCI) allows an easy non-contact monitoring of the cutaneous blood flow (CBF), but is highly sensitive to movement artifacts (ARTm). Subtraction of a signal recorded on an adhesive opaque surface (AOS) close to the area of interest was reported as a mean of reducing noise from the raw skin LSCI (LSCIsk) signal, provided an individual calibration was performed. Assuming that AOS = a · CBF + b · ARTm, an ideal patch should completely block the light reflection due to CBF and thus be insensitive to skin blood flow changes (“a” ~ 0), while keeping a reflection signal amplitude similar to the one from the skin in case of artifact (“b” ~ 1). This ideal AOS has not been determined and may discriminate flow from movements during LSCI recordings. Materials and methods We tested different AOSs to determine their “a” and “b” parameters in 35 and 34 healthy volunteers, respectively. The AOS surface providing results as close as possible to an ideal AOS, was used for a point-by-point de-noising of post occlusive reactive hyperemia (PORH) on two different days in 15 new subjects. Correlation of raw, smoothed (average smoothing over 1 s intervals) and denoised signals was tested through a cross-correlation analysis of the two POHR tests. Results The optimal “a” and “b” values were obtained with a homemade bilayer adhesive patch (a = 0.06 ± 0.05 and b = 1.03 ± 0.17) whereas other tested AOS had “a” values ranging from 0.05 to 0.23 and “b” values ranging from 2.69 to 3.82. Using the bilayer adhesive patch the cross-correlation between the two tests of POHR increased from 0.330 ± 0.128 for raw, to 0.461 ± 0.168 for smoothed and 0.649 ± 0.128 for denoised signals respectively (p < 0.05 from raw coefficients). Conclusion The home-made bilayer adhesive seems the optimal AOS for the removal of ARTm from the LSCIsk signal while respecting CBF signal. This specific AOS allows for an efficient de-noising of LSCI measurements without the need for individual calibration

A new method to determine arterial distensibility in small arteries

Several methods allow to measure arterial distensibilty. One of them consists in estimating the direct distensibility (D) from diameter and distending blood pressure. Herein, we propose a new method to assess the distensibility in small arteries which is based on spectral analysis of time motion mode ultrasound images of radial arteries. A Fourier transform was performed on intensity of upper and lower walls. Spectral amplitude at heart frequency from both wall spectra was estimated and summed (SumAmp). SumAmp was then compared with direct distensibility. A significant correlation was found between SumAmp and D (r = 0.7, p = 0.02)

Effets de la fluorescence résiduelle dans les tissus biologiques sur les signaux de fluorescence résolus temporellement par la méthode des éléments finis

RésuméUn modèle numérique basé sur la méthode des éléments finis est proposé afin d’analyser l’influence, sur les signaux de fluorescence résolus dans le temps, de la fluorescence résiduelle présente dans les milieux environnant une lésion tumorale. Nous appliquons une méthode de soustraction des données dans le cas d’une concentration imparfaite des agents de fluorescence au sein de la tumeur. Nous montrons ainsi les limites de la méthode de soustraction pour un faible contraste de fluorescence tumeur/milieu ambiant. En particulier, nous analysons l’extraction du temps de demi-montée et du maximum de l’intensité de fluorescence en fonction de la profondeur de la cible fluorescente. A computational model based on finite element method is derived to examine how the simulated time-dependent signals are related to the presence of residual fluorescence in biological media surrounding a fluorescent object. We apply a subtraction technique on recorded data when imperfect uptake of fluorescing agent into the tumor is considered. We show the limits of the subtracting method for low target: background fluorescent absorption contrast by extracting the time to reach the half maximum and analyzing the maximum of the time-resolved signals versus target depth

Multiscale Poincaré plot analysis of time series from laser speckle contrast imaging data

The monitoring of microvascular blood flow is of importance for research and clinical purposes because, for some pathologies as diabetes, the microcirculation may be affected long before organ dysfunctions are diagnosed. Laser speckle contrast imaging (LSCI) is gaining an increased interest to monitor microvascular blood flow (peripheral cardiovascular data). However, in spite of this and by opposition to central cardiovascular data as electrocardiograms, very few studies have been conducted on the analysis of LSCI through scales. We therefore propose to process LSCI data with a multiscale approach relying on Poincaré plots. For this purpose, we first study multiscale Poincaré (MSP) plots of simulated signals (synthetic white and 1/f noise time series). Then, MSP plots of LSCI time series recorded in 24 healthy volunteers are generated and analyzed. Furthermore, this analysis on real-life data is also conducted to study the role played by age on the results. Thus, the subjects were divided into two age groups: 13 young subjects (mean age = 23.8 ± 3.2 years old) and 11 elderly subjects (mean age = 56.9 ± 6.7 years old). Our results show properties that may reveal a weak fractal structure for LSCI data. Moreover, we find no statistical difference (p ≥ 0.05) for the descriptors of MSP plots between the two age groups. MSP plots may become a simple-to-implement visualization tool to provide new insights into biomedical data across scales

Laser speckle contrast imaging of skin changes in arteriovenous malformation

Laser speckle contrast imaging of skin changes in arteriovenous malformation

Aging effect on microcirculation: a multiscale entropy approach on laser speckle contrast images

Purpose: It has long been known that age plays a crucial role in the deterioration of microvessels. The assessment of such deteriorations can be achieved by monitoring microvascular blood flow. Laser speckle contrast imaging (LSCI) is a powerful optical imaging tool that provides two-dimensional information on microvascular blood flow. The technique has recently been commercialized, and hence, few works discuss the postacquisition processing of laser speckle contrast images recorded in vivo. By applying entropy-based complexity measures to LSCI time series, we present herein the first attempt to study the effect of aging on microcirculation by measuring the complexity of microvascular signals over multiple time scales. Methods: Forearm skin microvascular blood flow was studied with LSCI in 18 healthy subjects. The subjects were subdivided into two age groups: younger (20–30 years old, n = 9) and older (50–68 years old, n = 9). To estimate age-dependent changes in microvascular blood flow, we applied three entropy-based complexity algorithms to LSCI time series. Results: The application of entropy-based complexity algorithms to LSCI time series can differentiate younger from older groups: the data fluctuations in the younger group have a significantly higher complexity than those obtained from the older group. Conclusions: The effect of aging on microcirculation can be estimated by using entropy-based complexity algorithms to LSCI time series